Notice of Pre-AIA or AIA Status
The present application, filed on or after March 16, 2013, is being examined under the first inventor to file provisions of the AIA .
DETAILED ACTION
1. This is a first non-final Office Action on the merits for application 18893518. Claims 1-20 are canceled. Claims 21-40 are pending examination.
Double Patenting
2. The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP § 2146 et seq. for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The actual filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/apply/applying-online/eterminal-disclaimer.
Claims 21-40 are rejected on the ground of nonstatutory double patenting as being unpatentable over Claim 1-24 of U.S. Patent No. 12,169,845. Although the claims at issue are not identical, they are not patentably distinct from each other because the claims are directed to the same subject matter, perform similar method steps and a person of ordinary skill in the art would not be free to practice one of the claimed inventions without infringing upon the other inventions.
Application number: 18893518
21. (Previously Presented) An apparatus comprising:a communications interface;a memory storing instructions; and at least one processor coupled to the communications interface and to the memory, the at least one processor being configured to execute the instructions to:receive query data from a device via the communications interface, the query data comprising a value of a query parameter;based on the query data, obtain first elements of aggregated review data from the memory, each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty, and the data exchanges being during a prior temporal interval; and transmit, to the device via the communications interface, response data that includes at least a subset of the first elements of aggregated review data that are consistent with the query parameter value.
Patent number: 12,169,845
1. An apparatus comprising:
a communications interface;
a memory storing instructions; and
at least one processor coupled to the communications interface and to the memory, the at least one processor being configured to execute the instructions to:
receive, via the communications interface and from a computing system operable by a first counterparty, a message associated with an exchange of data involving the first counterparty and a second counterparty, the message comprising elements of message data disposed within corresponding message fields, the message data characterizing a real-time payment requested from the second counterparty by the first counterparty, the message data comprising a uniform resource locator associated with formatted data characterizing the exchange of data, and the formatted data being maintained by a computing system operable by the first counterparty;
based on the uniform resource locator, perform operations that request and receive at least a portion of the formatted data from the computing system via the communications interface;
determine a first identifier of the first counterparty based on the portion of the formatted data, and transmit, via the communications interface, notification data to a device operable by the second counterparty, the notification data comprising the first identifier and digital content, and the notification data causing an application program executed at the device to present the first identifier and at least a portion of the digital content within a digital interface;
receive, from the device via the communications interface, confirmation data indicative of an approval of an execution of the data exchange by the second counterparty and review data indicative of a review associated with the data exchange;
based on the confirmation data, store the first identifier and the review data in the memory and perform operations that execute the data exchange;
receive query data from the device via the communications interface, the query data comprising at least one of a portion of a counterparty identifier, a value of a counterparty characteristic, or a value of a geographic characteristic;
based on the received query data, obtain elements of aggregated review data characterizing one or more prior reviews associated with a plurality of candidate counterparties over a prior temporal interval, each of the elements of aggregated review data comprising an identifier of a corresponding one of the plurality of candidate counterparties, a value of at least one of a corresponding counterparty or geographic characteristic, and an aggregate value representative of the one or more prior reviews associated with the corresponding candidate counterparty over the prior temporal interval, and based on the aggregated review data, determine that a subset of the candidate counterparties are consistent with the query data; and
transmit, to the device via the communications interface, response data that includes at least a portion of the aggregated review data associated with the subset of the candidate counterparties, the device being configured to present a graphical representation of the least a portion of the response data within an additional digital interface.
32. (Previously Presented) A computer-implemented method, comprising: receiving query data from a device using at least one processor, the query data comprising a value of a query parameter; based on the query data, obtaining, using the at least one processor, first elements of aggregated review data from a data repository, each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty, and the data exchanges being during a prior temporal interval; and transmitting, using the at least one processor, response data that includes at least a subset of the first elements of aggregated review data that are consistent with the query parameter value.
13. A computer-implemented method, comprising:
receiving, using at least one processor, and from a computing system operable by a first counterparty, a message associated with an exchange of data involving the first counterparty and a second counterparty, the message comprising elements of message data disposed within corresponding message fields, the message data characterizing a real-time payment requested from the second counterparty by the first counterparty, the message data comprising a uniform resource locator associated with formatted data characterizing the exchange of data, and the formatted data being maintained by a computing system operable by the first counterparty;
based on the uniform resource locator, performing operations, using the at least one processor, that request and receive at least a portion of the formatted data from the computing system;
using the at least one processor, determining a first identifier of the first counterparty based on the portion of the formatted data, and transmitting notification data to a device operable by the second counterparty, the notification data comprising the first identifier and digital content, and the notification data causing an application program executed at the device to present the first identifier and at least a portion of the digital content within a digital interface;
receiving, from the device, and using the at least one processor, confirmation data indicative of an approval of an execution of the data exchange by the second counterparty and review data indicative of a review associated with the data exchange; and
based on the confirmation data, and using the at least one processor, storing the first identifier and the review data with a data repository, and performing operations that execute the data exchange;
receiving query data from the device using the at least one processor, the query data comprising at least one of a portion of a counterparty identifier, a value of a counterparty characteristic, or a value of a geographic characteristic;
based on the received query data, and using the at least one processor, obtaining elements of aggregated review data characterizing one or more prior reviews associated with a plurality of candidate counterparties over a prior temporal interval, each of the elements of aggregated review data comprising an identifier of a corresponding one of the plurality of candidate counterparties, a value of at least one of a corresponding counterparty or geographic characteristic, and an aggregate value representative of the one or more prior reviews associated with the corresponding candidate counterparty over the prior temporal interval, and based on the aggregated review data, determining that a subset of the candidate counterparties are consistent with the query data; and
transmitting, to the device, and using the at least one processor, response data that includes at least a portion of the aggregated review data associated with the subset of the candidate counterparties, the device being configured to present a graphical representation of the least a portion of the response data within an additional digital interface.
40. (Previously Presented) A device, comprising: a communications interface; a memory storing instructions; and at least one processor coupled to the communications interface and to the memory, the at least one processor being configured to execute the instructions to: transmit query data to a computing system via the communications interface, the query data comprising a value of a query parameter, and the computing system being configured to, based on the query data, obtain elements of aggregated review data from a data repository, each of the elements of aggregated review data being associated with a candidate counterparty, each of the elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty, and the data exchanges being during a prior temporal interval; receive, from the computing system via the communications interface, response data that includes at least a subset of the elements of aggregated review data that are consistent with the query parameter value; and perform operations that present a graphical representation of the least a portion of the response data within a digital interface.
20. A tangible, non-transitory computer-readable medium storing instructions that, when executed by at least one processor, cause the at least one processor to perform a method, comprising:
receiving, from a computing system operable by a first counterparty, a message associated with an exchange of data involving the first counterparty and a second counterparty, the message comprising elements of message data disposed within corresponding message fields, the message data characterizing a real-time payment requested from the second counterparty by the first counterparty, the message data comprising a uniform resource locator associated with formatted data characterizing the exchange of data, and the formatted data being maintained by a computing system operable by the first counterparty;
based on the uniform resource locator, performing operations, using the at least one processor, that request and receive at least a portion of the formatted data from the computing system;
determining an identifier of the first counterparty based on the portion of the formatted data, and transmitting notification data to a device operable by the second counterparty, the notification data comprising the identifier and digital content, and the notification data causing an application program executed at the device to present the identifier and at least a portion of the digital content within a digital interface;
receiving, from the device, confirmation data indicative of an approval of an execution of the data exchange by the second counterparty and review data indicative of a review associated with the data exchange;
based on the confirmation data, storing the identifier and the review data with a data repository, and performing operations that execute the data exchange;
receiving, from the device, query data that includes at least one of a portion of a counterparty identifier, a value of a counterparty characteristic, or a value of a geographic characteristic;
based on the received query data, obtaining elements of aggregated review data characterizing one or more prior reviews associated with a plurality of candidate counterparties over a prior temporal interval, each of the elements of aggregated review data comprising an identifier of a corresponding one of the plurality of candidate counterparties, a value of at least one of a corresponding counterparty or geographic characteristic, and an aggregate value representative of the one or more prior reviews associated with the corresponding candidate counterparty over the prior temporal interval, and based on the aggregated review data, determining that a subset of the candidate counterparties are consistent with the query data; and
transmitting, to the device response data that includes at least a portion of the aggregated review data associated with the subset of the candidate counterparties, the device being configured to present a graphical representation of the least a portion of the response data within an additional digital interface.
As to the independent claims:
Limitations presented in claim 22 is an obvious variation of additional limitations presented in patented claim 1.
Limitations presented in claim 23 is an obvious variation of additional limitations presented in patented claim 1.
Limitations presented in claim 24 is an obvious variation of additional limitations presented in patented claim 1.
Limitations presented in claim 25 is an obvious variation of additional limitations presented in patented claim 1.
Limitations presented in claim 26 is an obvious variation of additional limitations presented in patented claim 1.
Limitations presented in claim 27 is an obvious variation of additional limitations presented in patented claim 1.
Instant claim 28 is an obvious variation of patented claim 26.
Instant claim 29 is an obvious variation of patented claim 4.
Instant claim 30 is an obvious variation of patented claim 3.
Instant claim 31 is an obvious variation of patented claim 21.
Limitations presented in claim 33 is an obvious variation of additional limitations presented in patented claim 13.
Limitations presented in claim 34 is an obvious variation of additional limitations presented in patented claim 13.
Limitations presented in claim 35 is an obvious variation of additional limitations presented in patented claim 13.
Limitations presented in claim 36 is an obvious variation of additional limitations presented in patented claim 13.
Limitations presented in claim 37 is an obvious variation of additional limitations presented in patented claim 13.
Limitations presented in claim 38 is an obvious variation of additional limitations presented in patented claim 13.
Instant claim 39 is an obvious variation of patented claim 17.
It would have been obvious to one having ordinary skill in the art to make the changes above in order to cover slightly broader limitations. Furthermore, the claimed elements perform the same function as before.
Claim Rejections - 35 USC § 101
3. 35 U.S.C. 101 reads as follows:
Whoever invents or discovers any new and useful process, machine, manufacture, or composition of matter, or any new and useful improvement thereof, may obtain a patent therefor, subject to the conditions and requirements of this title.
Claims 21-40 are rejected under 35 U.S.C. 101 because the claimed invention is directed to a judicial exception (i.e., a law of nature, a natural phenomenon, or an abstract idea) without significantly more.
Claim(s) 32 is/are drawn to method (i.e., a process), claim(s) 21, and 40 is/are drawn to a system (i.e., a machine/manufacture). As such, claims 21, 32, and 40 is/are drawn to one of the statutory categories of invention.
Claims 21-40 are directed to transmitting reviews for a counterparty from different users based on query data parameter received from an interface of a user. Specifically, claim(s) 21, 32, and 40 recite(s) receive query data from via the communications interface, the query data comprising a value of a query parameter; based on the query data, obtain first elements of aggregated review data, each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty, and the data exchanges being during a prior temporal interval; and transmit, via the communications interface, response data that includes at least a subset of the first elements of aggregated review data that are consistent with the query parameter value, which is grouped within the Methods Of Organizing Human Activity and is similar to the concept of (commercial or legal interactions including agreements in the form of contracts, legal obligations, advertising, marketing or sales activities or behaviors business relations) grouping of abstract ideas in prong one of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 54 (January 7, 2019)). Accordingly, the claims recite an abstract idea (See pages 7, 10, Alice Corporation Pty. Ltd. v. CLS Bank International, et al., US Supreme Court, No. 13-298, June 19, 2014; 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 53-54 (January 7, 2019)).
The Claim limitations are listed under Methods Of Organizing Human Activity, and grouped as following:
receive query data from via the communications interface, the query data comprising a value of a query parameter; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations),
based on the query data, obtain first elements of aggregated review data, each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty, and the data exchanges being during a prior temporal interval; and which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations),
transmit, via the communications interface, response data that includes at least a subset of the first elements of aggregated review data that are consistent with the query parameter value; which is similar to the concept of (advertising, marketing or sales activities or behaviors business relations).
This judicial exception is not integrated into a practical application because, when analyzed under prong two of step 2A of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 54-55 (January 7, 2019)), the additional element(s) of the claim(s) such as device, memory, processor, apparatus merely use(s) a computer as a tool to perform an abstract idea and/or generally link(s) the use of a judicial exception to a particular technological environment. Specifically, the device, memory, processor, apparatus perform(s) the steps or functions of receive query data from via the communications interface, the query data comprising a value of a query parameter; based on the query data, obtain first elements of aggregated review data, each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty, and the data exchanges being during a prior temporal interval; and transmit, via the communications interface, response data that includes at least a subset of the first elements of aggregated review data that are consistent with the query parameter value. The use of a processor/computer as a tool to implement the abstract idea and/or generally linking the use of the abstract idea to a particular technological environment does not integrate the abstract idea into a practical application because it requires no more than a computer performing functions that correspond to acts required to carry out the abstract idea. The additional elements do not involve improvements to the functioning of a computer, or to any other technology or technical field (MPEP 2106.05(a)), the claims do not apply or use the abstract idea to effect a particular treatment or prophylaxis for a disease or medical condition (Vanda Memo), the claims do not apply the abstract idea with, or by use of, a particular machine (MPEP 2106.05(b)), the claims do not effect a transformation or reduction of a particular article to a different state or thing (MPEP 2106.05(c)), and the claims do not apply or use the abstract idea in some other meaningful way beyond generally linking the use of the abstract idea to a particular technological environment, such that the claim as a whole is more than a drafting effort designed to monopolize the exception (MPEP 2106.05(e) and Vanda Memo). Therefore, the claims do not, for example, purport to improve the functioning of a computer. Nor do they effect an improvement in any other technology or technical field. Accordingly, the additional elements do not impose any meaningful limits on practicing the abstract idea, and the claims are directed to an abstract idea.
The claim(s) does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 56 (January 7, 2019)), the additional element(s) of using a device, memory, processor, apparatus to perform the steps amounts to no more than using a computer or processor to automate and/or implement the abstract idea of transmitting reviews for a counterparty from different users based on query data parameter received from an interface of a user. As discussed above, taking the claim elements separately, the device, memory, processor, apparatus perform(s) the steps or functions of receive query data from via the communications interface, the query data comprising a value of a query parameter; based on the query data, obtain first elements of aggregated review data, each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty, and the data exchanges being during a prior temporal interval; and transmit, via the communications interface, response data that includes at least a subset of the first elements of aggregated review data that are consistent with the query parameter value. These functions correspond to the actions required to perform the abstract idea. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of transmitting reviews for a counterparty from different users based on query data parameter received from an interface of a user. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)). Therefore, the claim is not patent eligible.
As for dependent claims 22-31, and 33-39 further describe the abstract idea of transmitting reviews for a counterparty from different users based on query data parameter received from an interface of a user. Claim(s) 22-31, and 33-39 does/do not include additional elements that are sufficient to amount to significantly more than the judicial exception because, when analyzed under step 2B of the Alice/Mayo test (See 2019 Revised Patent Subject Matter Eligibility Guidance, 84 Fed. Reg. 50, 52, 56 (January 7, 2019)), the additional element(s) of using apparatus, device, memory, processor to perform the steps amounts to no more than using a computer or processor to automate and/or implement the abstract idea of transmitting reviews for a counterparty from different users based on query data parameter received from an interface of a user. As discussed above, taking the claim elements separately, the apparatus, device, memory, processor perform(s) the steps or functions of wherein: configured to execute an application program; and the response data causes the executed application program to present a graphical representation of a portion of the response data within a digital interface; further configured to execute the instructions to: determine, based on the first elements of aggregated review data, that at least one of the candidate counterparties is consistent with the query parameter value; and obtain the subset of the first elements of aggregated review data associated with the at least one of the candidate counterparties; wherein: the at least one query parameter value comprises a value of a geographic characteristic; each of the first elements of aggregated review data comprises a candidate value of a geographic characteristic; further configured to execute the instructions to determine, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on a comparison between the value of the geographic characteristic and the candidate value; wherein: the query parameter value comprises at least one of a portion of a counterparty identifier or a value of a counterparty characteristic; each of the first elements of aggregated review data comprises at least one of a candidate counterparty identifier or a candidate value of a characteristic associated with the corresponding candidate counterparty; and further configured to execute the instructions to determine, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on at least one of (i) a comparison between the portion of the counterparty identifier and the candidate counterparty identifier or (ii) a comparison between the value of the counterparty characteristic and the candidate value; wherein: each of the first elements of aggregated review data comprises a counterparty identifier; further configured to execute the instructions to generate the response data, the response data comprising the counterparty identifier and the aggregate value associated with each of the subset of the candidate counterparties; execute the instructions to: receive, from the communications interface, confirmation data indicative of an approval of an execution of an additional exchange of data involving a first counterparty and review data characterizing a review associated with the additional data exchange; and based on the confirmation data, store an identifier of the first counterparty and the review data; wherein: the review data comprises a first value characterizing the review associated with the additional data exchange; further configured to execute the instructions to: obtain elements of additional review data characterizing one or more prior reviews associated with prior data exchanges involving the first counterparty during the prior temporal interval, the elements of additional review data comprising second values characterizing corresponding ones of the prior reviews; generate an additional aggregate value representative of the first value and the second values associated with at least a subset of the prior reviews; and based on the confirmation data, generate a second element of aggregated review data that includes the additional aggregate value, and store the identifier of the first counterparty and the second element of aggregated review data; and the subset of the first elements of aggregated review data comprises the second element of aggregated review data; further configured to execute the instructions to: based on the confirmation data, obtain elements of message data associated with the additional data exchange, the message data comprising the identifier of the first counterparty and a parameter value of the additional data exchange; and perform operations that execute the data exchange in accordance with the parameter value; further configured to execute the instructions to: receive, via the communications interface, a message associated with the additional data exchange, the message comprising the elements of message data disposed within corresponding message fields, and the message fields being structured in accordance with a standardized data-exchange protocol; obtain, mapping data associated with the message fields of the received message; and perform operations that obtain the elements of message data from message fields based on the mapping data, and that store the elements of message data; wherein: the additional data exchange involves the first counterparty and a second counterparty, being operable by the second counterparty; execute an application program, the executed additional application program causing to initiate the additional data exchange; and further configured to execute the instructions to: determine a value of a parameter of the additional data exchange based on an application of a trained machine learning or artificial intelligence process to textual content associated with at least one of the elements of message data; and generate notification data comprising the identifier of the first counterparty and digital content, and to transmit the notification data via the communications interface prior to the execution of the additional data exchange. These functions correspond to the actions required to perform the abstract idea. Viewed as a whole, the combination of elements recited in the claims merely recite the concept of transmitting reviews for a counterparty from different users based on query data parameter received from an interface of a user. Therefore, the use of these additional elements does no more than employ the computer as a tool to automate and/or implement the abstract idea. The use of a computer or processor to merely automate and/or implement the abstract idea cannot provide significantly more than the abstract idea itself (MPEP 2106.05(I)(A)(f) & (h)). Therefore, the claim is not patent eligible.
Claim Rejections - 35 USC § 103
4. In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of pre-AIA 35 U.S.C. 103(a) which forms the basis for all obviousness rejections set forth in this Office action:
(a) A patent may not be obtained through the invention is not identically disclosed or described as set forth in section 102 of this title, if the differences between the subject matter sought to be patented and the prior art are such that the subject matter as a whole would have been obvious at the time the invention was made to a person having ordinary skill in the art to which said subject matter pertains. Patentability shall not be negative by the manner in which the invention was made.
A. Claims 21-23, 25-29, 32-34, and 36-40 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Yahia et al., (U.S. Patent Application Publication No. 20130138644) in view of Roberts, (U.S. Patent Application Publication No. 20160335683) in view of Suvajac et al., (U.S. Patent Application Publication No. 20200104911). As to Claim 21, Yahia teaches an apparatus comprising:a communications interface; (0063: communications interface),a memory storing instructions; and (0063: memory),at least one processor (0063: one or more processors to perform the functions of the invention) coupled to the communications interface (0063: communications interface), and to the memory (0063: memory), the at least one processor being configured to execute the instructions to: (0063: one or more processors to perform the functions of the invention),receive query data from a device (client device 110 and 112) via the communications interface (abstract: receiving a first query identifying a given content item… 0026: a user interface 101), the query data comprising a value (Fig. 5: rating example 3 out 5) of a query parameter; (0010: assigning a value to one or more of the one or more objective attributes… 0031: the objective attributes for a restaurant item of content may comprise: type of cuisine, the location, and the name of the chef. The corresponding values may comprise: French, Manhattan, and Jean Georges. According to another embodiment, the objective attributes for a movie item of content may comprise: title, actor, and genre. The corresponding values may comprise: Mission Impossible, Tom Cruise, and Action), (0047: a value for the objective attribute of the item of content is obtained… if the movie was Pirates of the Caribbean, values for the objective attributes may comprise "Pirates of the Caribbean" for the title, "Johnny Depp" for an actor, and "Adventure" for a genre. Additionally, if the restaurant was, for example, Daniel, values for the objective attributes may comprise, "Daniel" for the name of the restaurant, "French" for the type of cuisine, "Daniel Boulud" for the chef, "Upper East Side" for the neighborhood, and "Very Expensive" for the cost), and (0010: assigning a value to one or more of the one or more objective attributes, and identifying one or more subjective attributes associated with a given item in the initial collection of content items),based on the query data (abstract: receiving a query identifying a given content item… 0047: the movie was Pirates of the Caribbean, values for the objective attributes may comprise "Pirates of the Caribbean" for the title, "Johnny Depp" for an actor, and "Adventure" for a genre. Additionally, if the restaurant was, for example, Daniel, values for the objective attributes may comprise, "Daniel" for the name of the restaurant, "French" for the type of cuisine, "Daniel Boulud" for the chef, "Upper East Side" for the neighborhood, and "Very Expensive" for the cost), obtain first elements of aggregated review data from the memory (0056: collecting data on the user explicitly (e.g., asking him to rate certain items of content… 0063: from a memory), transmit, to the device via the communications interface (0044: generating the relevant context and transmits the relevant context as a result set of one or more attribute-value… display via the user interface 101 as an annotation for a given review… 0044: present the given item of content for display in conjunction with subjective and objective attributes of the item of content on a client device 110 and 112 via the network 109.), response data that includes at least a subset of the first elements of aggregated review data (0036: values may comprise the text of such a review or score of such a ranking) that are consistent with the query parameter value; (0036: a given item of content may also be associated with one or more subjective attributes and values. Subjective attributes may comprise user reviews or rankings, and subjective values may comprise the text of such a review or score of such a ranking. The subjective values of a given item of content are generally submitted by clients 110, 111 or 112 to the system. While subjective attributes according to one embodiment may be characterized as general user reviews or rankings of an item of content (e.g., an overall user review or score of a restaurant), the subjective attributes may also be broken down into components. For example, where the item of content is a restaurant, subjective attributes may comprise: quality of the food, decor, service, and cost. A given component may then be reviewed or scored independently. The reviewers of the items of content may comprise both professionals in the trade (e.g., newspaper columnists, magazine editors, and the like), as well as ordinary individuals that frequent the social review system 100. In accordance with one embodiment, ordinary individuals may elevate their status based on the previous number of reviews they have written or their familiarity with a specific item of content), and (0044: generating the relevant context and transmits the relevant context as a result set of one or more attribute-value… display via the user interface 101 as an annotation for a given review.), and (0037: The user interface 101 may present the given item of content for display in conjunction with subjective and objective attributes of the item of content on a client device 110 and 112 via the network 109. Upon a specified event, the user interface 101 may pass the query to the domain application processor 102 to determine whether context exists for the one or more subjective attributes of a given item of content).
Yahia does not teach each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty.
However Roberts teaches each of the first elements of aggregated review data being associated with a candidate counterparty (Examiners note: counterparty as mentioned in the spec is a merchant), (See Fig. 27: Merchant is Little taste of India which is associated with aggregated review data such as 3.0 stars from evan hayes and another review from Stu Roberts 4.5 star), each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty (can be the reviews listed from different people who tried the restaurant with the rating value), and (Fig. 27: review can include aggregated value is the avg rating on 2.9 and 3.0 of Fig. 27 1234 and has prior reviews such as prior review from evan hayes and another review from Stu Roberts 4.5 star), and (0046: display a user interface such as that shown in FIG. 27. The user interface of FIG. 27 displays a list of star ratings 1264 and associated reviews 1266 (collectively referred to as feedback) submitted by users 1268. The users 1268 and their associated star ratings 1264 and reviews 1266 are listed in order of descending correlation values 1234. In this way, the a user viewing the user interface of FIG. 27 is presented with the most relevant feedback from other users about the restaurant first with less relevant feedback about the restaurant being provide lower and/or later in the list of feedback. In some embodiments, a correlation relevancy value 1270 can be provided. In some embodiments, the correlation relevancy value 1270 can be provided as an output and/or function of an output of the recalculation module 120.).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia to include each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty of Roberts. Motivation to do so comes from the knowledge well known in the art that each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty would provide a value like rating that would help the user determine which counterparty to visit and that would promote an increase in the sales and would therefore make the method/system more profitable for the counterparty.
Yahia does not teach the data exchanges being during a prior temporal interval.
However Suvajac teaches the data exchanges being during a prior temporal interval; and (0003: determine a value characterizing the first counterparty performs the data exchange in accordance with the at least one parameter value during a temporal interval).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia to include the data exchanges being during a prior temporal interval of Suvajac. Motivation to do so comes from the knowledge well known in the art that the data exchanges being during a prior temporal interval would help in providing reviews and rating that are close in time and that would encourage the user to visit the counterparty which would therefore make the method/system more accurate.
As to Claim 22, Yahia, Roberts, and Suvajac teach the apparatus of claim 21.
Yahia further teaches wherein:the device is configured to execute an application program; and (0028: runs software applications, such as a web browser (not pictured), which provide for transmission of queries, as well as display of retrieved result sets comprising items of content with objective attributes , subjective attributes and annotations. Client 110, 111 and 112 initiates a query over the network 109 for a given item of content from a collection of items in a domain, such as, for example, a collection of movies or restaurants, on a social review system 100. A collection of items may comprise a subset of a universe of potential items of content and may have short descriptions, which users may perceive as meaningful for the purpose of rating or review.), the response data causes the executed application program to present a graphical representation of a portion of the response data within a digital interface; (See Fig. 5: application interface with graphical user interface for representation of movie and item reviews).
As to Claim 23, Yahia, Roberts, and Suvajac teach the apparatus of claim 21.
Yahia teaches wherein the at least one processor is further configured to execute the instructions to:determine, based on the first elements of aggregated review data, that at least one of the candidate counterparties is consistent with the query parameter value; and (See Fig. 5 502: Based on the first review for the Pirates of the Caribbean movie, displaying another review from a different reviewer and a third review from another reviewer), and (0060: For example, in the conclusion for the first review, the conclusion states that the "reviewer rated 10 action/adventure movies. He rates this movie better than 5 of them. He likes action/adventure less than the average reviewer." In the conclusion for the second review, the conclusion states that the "reviewer rated 5 movies starring Johnny Depp. He rates this movie better than 4 of them." These examples of context are determined by comparing a profile for the reviewer to the SMAC 510).
Roberts further teaches obtain the subset of the first elements of aggregated review data associated with the at least one of the candidate counterparties; (Fig. 27: review can include aggregated value is the avg rating on 2.9 and 3.0 of Fig. 27 1234 and has prior reviews such as prior review from evan hayes and another review from Stu Roberts 4.5 star), and (0046: display a user interface such as that shown in FIG. 27. The user interface of FIG. 27 displays a list of star ratings 1264 and associated reviews 1266 (collectively referred to as feedback) submitted by users 1268. The users 1268 and their associated star ratings 1264 and reviews 1266 are listed in order of descending correlation values 1234. In this way, the a user viewing the user interface of FIG. 27 is presented with the most relevant feedback from other users about the restaurant first with less relevant feedback about the restaurant being provide lower and/or later in the list of feedback. In some embodiments, a correlation relevancy value 1270 can be provided. In some embodiments, the correlation relevancy value 1270 can be provided as an output and/or function of an output of the recalculation module 120.).
It would have been obvious to one of ordinary skill in the art at the time of the invention to include obtain the subset of the first elements of aggregated review data associated with the at least one of the candidate counterparties. Motivation to do so comes from the knowledge well known in the art that obtain the subset of the first elements of aggregated review data associated with the at least one of the candidate counterparties would help provide more data that would help in determining a more accurate counterparty and that would therefore make the method/system more accurate.
As to Claim 25, Yahia, Roberts, and Suvajac teach the apparatus of claim 23.
Yahia further teaches wherein:the query parameter value comprises at least one of a portion of a counterparty identifier (can be cuisine in French, Manhattan, and Jean Georges or Daniel" for the name of the restaurant, "French" for the type of cuisine title, actor, and genre such as Tom cruise mission impossible) or a value of a counterparty characteristic (assigning a value to one or more of the one or more objective attributes); (0010: assigning a value to one or more of the one or more objective attributes… 0031: the objective attributes for a restaurant item of content may comprise: type of cuisine, the location, and the name of the chef. The corresponding values may comprise: French, Manhattan, and Jean Georges. According to another embodiment, the objective attributes for a movie item of content may comprise: title, actor, and genre. The corresponding values may comprise: Mission Impossible, Tom Cruise, and Action), (0047: a value for the objective attribute of the item of content is obtained… if the movie was Pirates of the Caribbean, values for the objective attributes may comprise "Pirates of the Caribbean" for the title, "Johnny Depp" for an actor, and "Adventure" for a genre. Additionally, if the restaurant was, for example, Daniel, values for the objective attributes may comprise, "Daniel" for the name of the restaurant, "French" for the type of cuisine, "Daniel Boulud" for the chef, "Upper East Side" for the neighborhood, and "Very Expensive" for the cost), and (0010: assigning a value to one or more of the one or more objective attributes, and identifying one or more subjective attributes associated with a given item in the initial collection of content items),each of the first elements of aggregated review data comprises at least one of a candidate counterparty identifier (See Fig. 5 502 second review: johnny depp is in the review) or a candidate value of a characteristic associated with the corresponding candidate counterparty; and (can be the rating 10 in Fig. 5 502),the at least one processor is further configured to execute the instructions to determine, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on at least one of (i) a comparison between the portion of the counterparty identifier and the candidate counterparty identifier (Examiner interpret this claim limitation to be: Fig. 5 500 pirates of the Caribbean is the first parameter element, and 502 second review has johnny depp which is consistent with the query parameter pirates of the Caribbean that has an actor called johnny depp which can be the identifier) or (ii) a comparison between the value of the counterparty characteristic and the candidate value.
As to Claim 26, Yahia, Roberts, and Suvajac teach the apparatus of claim 21.
Yahia further teaches wherein:each of the first elements of aggregated review data comprises a counterparty identifier; and (0031: can be cuisine in French, Manhattan, and Jean Georges or Daniel" for the name of the restaurant, "French" for the identifier counterparty or title, actor, and genre such as Tom cruise mission impossible),the at least one processor is further configured to execute the instructions to generate the response data (can be the displaying of the review), the response data comprising the counterparty identifier (Fig. 5: 500 Pirates of the Caribbean) and the aggregate value (can be the rating, See Fig. 5 502 the review rated 10…) associated with each of the subset of the candidate counterparties; (0010: assigning a value to one or more of the one or more objective attributes, and identifying one or more subjective attributes associated with a given item in the initial collection of content items… 0011: the values of one or more of the content items therein, and displaying the context in conjunction with the user review.).
As to Claim 27, Yahia, Roberts, and Suvajac teach the apparatus of claim 21.
Yahia further teaches wherein the at least one processor is further configured to execute the instructions to:receive, from the device via the communications interface, confirmation data indicative of an approval of an execution of an additional exchange of data involving a first counterparty and review data characterizing a review associated with the additional data exchange; and based on the confirmation data, store an identifier of the first counterparty and the review data with the memory; (0005: evaluating the numerous ratings and reviews entered by reviewers and users. For example, some reviewers are inconsistent, some have particular biases, and some have no appropriate frame of reference. Although some systems provide a measure of "usefulness" for a given review (e.g., "6 of 11 people found this review helpful"), or some other characteristic (e.g., allowing users to rate a review as useful, funny, or cool), these are merely simple aggregations of existing votes. Other systems provide for a trust system to rate reviewers, but this is a one-dimensional approach.), (0006: The ability of a user to interpret an opinion of a given reviewer is crucial to making a good decision. A user should interpret or weight a restaurant review that comes from a reviewer of discerning taste and familiarity with the relevant cuisine differently than a similar review coming for a random Web surfer that happened to wander into the restaurant. To mitigate this problem, most popular systems attempt to characterize reviewers, but this is limited in most cases to the total number of reviews written by the given reviewer. Even with the knowledge that the reviewer has written many previous reviews, it is still not a simplistic task to arrive at an informed decision. The ability for any individual to enter a review also exacerbates this problem.), and (claim 1: a user review personalized to prior user experience… stored in a user profile).
As to Claim 28, Yahia, Roberts, and Suvajac teach the apparatus of claim 27.
Roberts further teaches wherein:the review data comprises a first value characterizing the review associated with the additional data exchange; (See Fig. 27: first value data characterizing the review associated with additional data exchange can be the second rating from the second user evan hays of 3.0 star),the at least one processor is further configured to execute the instructions to:obtain elements of additional review data characterizing one or more prior reviews, the elements of additional review data comprising second values characterizing corresponding ones of the prior reviews; (Fig. 27: review can include aggregated value is the avg rating on 2.9 and 3.0 of Fig. 27 1234 and has prior reviews such as prior review from evan hayes and another review from Stu Roberts 4.5 star), and (0046: display a user interface such as that shown in FIG. 27. The user interface of FIG. 27 displays a list of star ratings 1264 and associated reviews 1266 (collectively referred to as feedback) submitted by users 1268. The users 1268 and their associated star ratings 1264 and reviews 1266 are listed in order of descending correlation values 1234. In this way, the a user viewing the user interface of FIG. 27 is presented with the most relevant feedback from other users about the restaurant first with less relevant feedback about the restaurant being provide lower and/or later in the list of feedback. In some embodiments, a correlation relevancy value 1270 can be provided. In some embodiments, the correlation relevancy value 1270 can be provided as an output and/or function of an output of the recalculation module 120.),generate an additional aggregate value representative of the first value and the second values associated with at least a subset of the prior reviews; and (Fig. 27: first value can be from a first user evan hayes with a 3.0 star and the second value can be from second user Stu Roberts with 4.5 star.),based on the confirmation data, generate a second element of aggregated review data that includes the additional aggregate value, and store the identifier of the first counterparty and the second element of aggregated review data within the memory; and the subset of the first elements of aggregated review data comprises the second element of aggregated review data; (Fig. 27: second element is the second value can be from second user Stu Roberts with 4.5 star. And identifier of the user is his name which can be stored and added to the review data of the restaurant).
It would have been obvious to one of ordinary skill in the art at the time of the invention to include based on the confirmation data, generate a second element of aggregated review data that includes the additional aggregate value, and store the identifier of the first counterparty and the second element of aggregated review data within the memory; and the subset of the first elements of aggregated review data comprises the second element of aggregated review data. Motivation to do so comes from the knowledge well known in the art that based on the confirmation data, generate a second element of aggregated review data that includes the additional aggregate value, and store the identifier of the first counterparty and the second element of aggregated review data within the memory; and the subset of the first elements of aggregated review data comprises the second element of aggregated review data would help provide more data that would help in determining a more accurate counterparty and that would therefore make the method/system more accurate.
Suvajac further teaches associated with prior data involving the first counterparty during the prior temporal interval (0003: determine a value characterizing the first counterparty performs the data exchange in accordance with the at least one parameter value during a temporal interval).
It would have been obvious to one of ordinary skill in the art at the time of the invention to include the data exchanges being during a prior temporal interval. Motivation to do so comes from the knowledge well known in the art that the data exchanges being during a prior temporal interval would help in providing reviews and rating that are close in time and that would encourage the user to visit the counterparty which would therefore make the method/system more accurate.
As to Claim 29, Yahia, Roberts, and Suvajac teach the apparatus of claim 27.
Yahia further teaches wherein the at least one processor is further configured to execute the instructions to:based on the confirmation data, obtain elements of message data associated with the additional data exchange from the memory, the message data comprising the identifier of the first counterparty and a parameter value of the additional data exchange; and perform operations that execute the data exchange in accordance with the parameter value; (0005: evaluating the numerous ratings and reviews entered by reviewers and users. For example, some reviewers are inconsistent, some have particular biases, and some have no appropriate frame of reference. Although some systems provide a measure of "usefulness" for a given review (e.g., "6 of 11 people found this review helpful"), or some other characteristic (e.g., allowing users to rate a review as useful, funny, or cool), these are merely simple aggregations of existing votes. Other systems provide for a trust system to rate reviewers, but this is a one-dimensional approach.), (0006: The ability of a user to interpret an opinion of a given reviewer is crucial to making a good decision. A user should interpret or weight a restaurant review that comes from a reviewer of discerning taste and familiarity with the relevant cuisine differently than a similar review coming for a random Web surfer that happened to wander into the restaurant. To mitigate this problem, most popular systems attempt to characterize reviewers, but this is limited in most cases to the total number of reviews written by the given reviewer. Even with the knowledge that the reviewer has written many previous reviews, it is still not a simplistic task to arrive at an informed decision. The ability for any individual to enter a review also exacerbates this problem.), and (claim 1: a user review personalized to prior user experience… stored in a user profile), (Examiner note: Based on the data collected from the user such as movie title or restaurant name, the additional data can be type of cuisine, the location, and the name of the chef., French, Manhattan which can help in displaying a specific restaurant that is French).
As to Claim 32, Yahia teaches a computer-implemented method, comprising:receiving query data from a device (client device 110 and 112) using at least one processor (abstract: receiving a first query identifying a given content item… 0026: a user interface 101), the query data comprising a value (Fig. 5: rating example 3 out 5) of a query parameter; (0010: assigning a value to one or more of the one or more objective attributes… 0031: the objective attributes for a restaurant item of content may comprise: type of cuisine, the location, and the name of the chef. The corresponding values may comprise: French, Manhattan, and Jean Georges. According to another embodiment, the objective attributes for a movie item of content may comprise: title, actor, and genre. The corresponding values may comprise: Mission Impossible, Tom Cruise, and Action), (0047: a value for the objective attribute of the item of content is obtained… if the movie was Pirates of the Caribbean, values for the objective attributes may comprise "Pirates of the Caribbean" for the title, "Johnny Depp" for an actor, and "Adventure" for a genre. Additionally, if the restaurant was, for example, Daniel, values for the objective attributes may comprise, "Daniel" for the name of the restaurant, "French" for the type of cuisine, "Daniel Boulud" for the chef, "Upper East Side" for the neighborhood, and "Very Expensive" for the cost), and (0010: assigning a value to one or more of the one or more objective attributes, and identifying one or more subjective attributes associated with a given item in the initial collection of content items),based on the query data (abstract: receiving a query identifying a given content item… 0047: the movie was Pirates of the Caribbean, values for the objective attributes may comprise "Pirates of the Caribbean" for the title, "Johnny Depp" for an actor, and "Adventure" for a genre. Additionally, if the restaurant was, for example, Daniel, values for the objective attributes may comprise, "Daniel" for the name of the restaurant, "French" for the type of cuisine, "Daniel Boulud" for the chef, "Upper East Side" for the neighborhood, and "Very Expensive" for the cost), obtaining, using the at least one processor (0056: collecting data on the user explicitly (e.g., asking him to rate certain items of content… 0063: from a memory),
transmitting, using the at least one processor, response data that includes at least a subset of the first elements of aggregated review data (0036: values may comprise the text of such a review or score of such a ranking) that are consistent with the query parameter value; (0036: a given item of content may also be associated with one or more subjective attributes and values. Subjective attributes may comprise user reviews or rankings, and subjective values may comprise the text of such a review or score of such a ranking. The subjective values of a given item of content are generally submitted by clients 110, 111 or 112 to the system. While subjective attributes according to one embodiment may be characterized as general user reviews or rankings of an item of content (e.g., an overall user review or score of a restaurant), the subjective attributes may also be broken down into components. For example, where the item of content is a restaurant, subjective attributes may comprise: quality of the food, decor, service, and cost. A given component may then be reviewed or scored independently. The reviewers of the items of content may comprise both professionals in the trade (e.g., newspaper columnists, magazine editors, and the like), as well as ordinary individuals that frequent the social review system 100. In accordance with one embodiment, ordinary individuals may elevate their status based on the previous number of reviews they have written or their familiarity with a specific item of content), and (0044: generating the relevant context and transmits the relevant context as a result set of one or more attribute-value… display via the user interface 101 as an annotation for a given review.), and (0037: The user interface 101 may present the given item of content for display in conjunction with subjective and objective attributes of the item of content on a client device 110 and 112 via the network 109. Upon a specified event, the user interface 101 may pass the query to the domain application processor 102 to determine whether context exists for the one or more subjective attributes of a given item of content.).
Yahia does not teach a first elements of aggregated review data from a data repository each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty.
However Roberts teaches first elements of aggregated review data from a data repository, (Examiners note: counterparty as mentioned in the spec is a merchant), (See Fig. 27: Merchant is Little taste of India which is associated with aggregated review data such as 3.0 stars from evan hayes and another review from Stu Roberts 4.5 star), each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty (Fig. 27: review can include aggregated value is the avg rating on 2.9 and 3.0 of Fig. 27 1234 and has prior reviews such as prior review from evan hayes and another review from Stu Roberts 4.5 star), and (0046: display a user interface such as that shown in FIG. 27. The user interface of FIG. 27 displays a list of star ratings 1264 and associated reviews 1266 (collectively referred to as feedback) submitted by users 1268. The users 1268 and their associated star ratings 1264 and reviews 1266 are listed in order of descending correlation values 1234. In this way, the a user viewing the user interface of FIG. 27 is presented with the most relevant feedback from other users about the restaurant first with less relevant feedback about the restaurant being provide lower and/or later in the list of feedback. In some embodiments, a correlation relevancy value 1270 can be provided. In some embodiments, the correlation relevancy value 1270 can be provided as an output and/or function of an output of the recalculation module 120.).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia to include a first elements of aggregated review data from a data repository each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty of Roberts. Motivation to do so comes from the knowledge well known in the art that a first elements of aggregated review data from a data repository each of the first elements of aggregated review data being associated with a candidate counterparty, each of the first elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty would provide a value like rating that would help the user determine which counterparty to visit and that would promote an increase in the sales and would therefore make the method/system more profitable for the counterparty.
Yahia does not teach the data exchanges being during a prior temporal interval.
However Suvajac teaches the data exchanges being during a prior temporal interval; and (0003: determine a value characterizing the first counterparty performs the data exchange in accordance with the at least one parameter value during a temporal interval).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia to include the data exchanges being during a prior temporal interval of Suvajac. Motivation to do so comes from the knowledge well known in the art that the data exchanges being during a prior temporal interval would help in providing reviews and rating that are close in time and that would encourage the user to visit the counterparty which would therefore make the method/system more accurate.
As to Claim 33, Yahia, Roberts, and Suvajac teach the computer-implemented method of claim 32.
Yahia further teaches wherein:the device is configured to execute an application program; and (0028: runs software applications, such as a web browser (not pictured), which provide for transmission of queries, as well as display of retrieved result sets comprising items of content with objective attributes , subjective attributes and annotations. Client 110, 111 and 112 initiates a query over the network 109 for a given item of content from a collection of items in a domain, such as, for example, a collection of movies or restaurants, on a social review system 100. A collection of items may comprise a subset of a universe of potential items of content and may have short descriptions, which users may perceive as meaningful for the purpose of rating or review.),the response data causes the executed application program to present a graphical representation of a portion of the response data within a digital interface; (See Fig. 5: application interface with graphical user interface for representation of movie and item reviews).
As to Claim 34, Yahia, Roberts, and Suvajac teach the computer-implemented method of claim 32.
Yahia teaches determining, based on the first elements of aggregated review data, and using the at least one processor, that at least one of the candidate counterparties is consistent with the query parameter value; and (See Fig. 5 502: Based on the first review for the Pirates of the Caribbean movie, displaying another review from a different reviewer and a third review from another reviewer), and (0060: For example, in the conclusion for the first review, the conclusion states that the "reviewer rated 10 action/adventure movies. He rates this movie better than 5 of them. He likes action/adventure less than the average reviewer." In the conclusion for the second review, the conclusion states that the "reviewer rated 5 movies starring Johnny Depp. He rates this movie better than 4 of them." These examples of context are determined by comparing a profile for the reviewer to the SMAC 510),obtaining, using the at least one processor, the subset of the first elements of aggregated review data associated with the at least one of the candidate counterparties; (0010: assigning a value to one or more of the one or more objective attributes, and identifying one or more subjective attributes associated with a given item in the initial collection of content items… 0011: the values of one or more of the content items therein, and displaying the context in conjunction with the user review.).
As to Claim 36, Yahia, Roberts, and Suvajac teach the computer-implemented method of claim 34.
Yahia further teaches wherein:the query parameter value comprises at least one of a portion of a counterparty identifier or a value of a counterparty characteristic; (assigning a value to one or more of the one or more objective attributes); (0010: assigning a value to one or more of the one or more objective attributes… 0031: the objective attributes for a restaurant item of content may comprise: type of cuisine, the location, and the name of the chef. The corresponding values may comprise: French, Manhattan, and Jean Georges. According to another embodiment, the objective attributes for a movie item of content may comprise: title, actor, and genre. The corresponding values may comprise: Mission Impossible, Tom Cruise, and Action), (0047: a value for the objective attribute of the item of content is obtained… if the movie was Pirates of the Caribbean, values for the objective attributes may comprise "Pirates of the Caribbean" for the title, "Johnny Depp" for an actor, and "Adventure" for a genre. Additionally, if the restaurant was, for example, Daniel, values for the objective attributes may comprise, "Daniel" for the name of the restaurant, "French" for the type of cuisine, "Daniel Boulud" for the chef, "Upper East Side" for the neighborhood, and "Very Expensive" for the cost), and (0010: assigning a value to one or more of the one or more objective attributes, and identifying one or more subjective attributes associated with a given item in the initial collection of content items),each of the first elements of aggregated review data comprises at least one of a candidate counterparty identifier (See Fig. 5 502 second review: johnny depp is in the review) or a candidate value of a characteristic associated with the corresponding candidate counterparty; and (can be the rating 10 in Fig. 5 502),determining comprises determining, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on at least one of (i) a comparison between the portion of the counterparty identifier and the candidate counterparty identifier (Examiner interpret this claim limitation to be: Fig. 5 500 pirates of the Caribbean is the first parameter element, and 502 second review has johnny depp which is consistent with the query parameter pirates of the Caribbean that has an actor called johnny depp which can be the identifier) or (ii) a comparison between the value of the counterparty characteristic and the candidate value.
As to Claim 37, Yahia, Roberts, and Suvajac teach the computer-implemented method of claim 32.
Yahia further teaches wherein:each of the first elements of aggregated review data comprises a counterparty identifier; and (0031: can be cuisine in French, Manhattan, and Jean Georges or Daniel" for the name of the restaurant, "French" for the identifier counterparty or title, actor, and genre such as Tom cruise mission impossible),the computer-implemented method further comprises generating the response data (can be the displaying of the review), using the at least one processor, the response data comprising the counterparty identifier (Fig. 5: 500 Pirates of the Caribbean) and the aggregate value can be the rating, See Fig. 5 502 the review rated 10…) associated with each of the subset of the candidate counterparties; (0010: assigning a value to one or more of the one or more objective attributes, and identifying one or more subjective attributes associated with a given item in the initial collection of content items… 0011: the values of one or more of the content items therein, and displaying the context in conjunction with the user review
As to Claim 38, Yahia, Roberts, and Suvajac teach the computer-implemented method of claim 32.
Yahia further teaches further comprising:receiving, from the device using the at least one processor, confirmation data indicative of an approval of an execution of an additional exchange of data involving a first counterparty and review data characterizing a review associated with the additional data exchange; and based on the confirmation data, storing an identifier of the first counterparty and the review data with the data repository; (0005: evaluating the numerous ratings and reviews entered by reviewers and users. For example, some reviewers are inconsistent, some have particular biases, and some have no appropriate frame of reference. Although some systems provide a measure of "usefulness" for a given review (e.g., "6 of 11 people found this review helpful"), or some other characteristic (e.g., allowing users to rate a review as useful, funny, or cool), these are merely simple aggregations of existing votes. Other systems provide for a trust system to rate reviewers, but this is a one-dimensional approach.), (0006: The ability of a user to interpret an opinion of a given reviewer is crucial to making a good decision. A user should interpret or weight a restaurant review that comes from a reviewer of discerning taste and familiarity with the relevant cuisine differently than a similar review coming for a random Web surfer that happened to wander into the restaurant. To mitigate this problem, most popular systems attempt to characterize reviewers, but this is limited in most cases to the total number of reviews written by the given reviewer. Even with the knowledge that the reviewer has written many previous reviews, it is still not a simplistic task to arrive at an informed decision. The ability for any individual to enter a review also exacerbates this problem.), and (claim 1: a user review personalized to prior user experience… stored in a user profile).
As to Claim 39, Yahia, Roberts, and Suvajac teach the computer-implemented method of claim 38.
Roberts further teaches wherein: the review data comprises a first value characterizing the review associated with the additional data exchange; (See Fig. 27: first value data characterizing the review associated with additional data exchange can be the second rating from the second user evan hays of 3.0 star),the computer-implemented method further comprises:obtaining, using the at least one processor, elements of additional review data characterizing one or more prior reviews associated with prior data exchanges involving the first counterparty
the elements of additional review data comprising second values characterizing corresponding ones of the prior reviews; (Fig. 27: review can include aggregated value is the avg rating on 2.9 and 3.0 of Fig. 27 1234 and has prior reviews such as prior review from evan hayes and another review from Stu Roberts 4.5 star), and (0046: display a user interface such as that shown in FIG. 27. The user interface of FIG. 27 displays a list of star ratings 1264 and associated reviews 1266 (collectively referred to as feedback) submitted by users 1268. The users 1268 and their associated star ratings 1264 and reviews 1266 are listed in order of descending correlation values 1234. In this way, the a user viewing the user interface of FIG. 27 is presented with the most relevant feedback from other users about the restaurant first with less relevant feedback about the restaurant being provide lower and/or later in the list of feedback. In some embodiments, a correlation relevancy value 1270 can be provided. In some embodiments, the correlation relevancy value 1270 can be provided as an output and/or function of an output of the recalculation module 120.),
generating, using the at least one processor, an additional aggregate value representative of the first value and the second values associated with at least a subset of the prior reviews; and (Fig. 27: first value can be from a first user evan hayes with a 3.0 star and the second value can be from second user Stu Roberts with 4.5 star.), based on the confirmation data, generating, using the at least one processor, a second element of aggregated review data that includes the additional aggregate value, and storing the identifier of the first counterparty and the second element of aggregated review data within the data repository using the at least one processor; and the subset of the first elements of aggregated review data comprises the second element of aggregated review data; (Fig. 27: second element is the second value can be from second user Stu Roberts with 4.5 star. And identifier of the user is his name which can be stored and added to the review data of the restaurant).
It would have been obvious to one of ordinary skill in the art at the time of the invention to include based on the confirmation data, generating, using the at least one processor, a second element of aggregated review data that includes the additional aggregate value, and storing the identifier of the first counterparty and the second element of aggregated review data within the data repository using the at least one processor; and the subset of the first elements of aggregated review data comprises the second element of aggregated review data. Motivation to do so comes from the knowledge well known in the art that based on the confirmation data, generating, using the at least one processor, a second element of aggregated review data that includes the additional aggregate value, and storing the identifier of the first counterparty and the second element of aggregated review data within the data repository using the at least one processor; and the subset of the first elements of aggregated review data comprises the second element of aggregated review data would help provide more data that would help in determining a more accurate counterparty and that would therefore make the method/system more accurate.
Suvajac further teaches the prior temporal interval (0003: determine a value characterizing that the first counterparty performs the data exchange in accordance with the at least one parameter value during a temporal interval).
It would have been obvious to one of ordinary skill in the art at the time of the invention to include the prior temporal interval. Motivation to do so comes from the knowledge well known in the art that the prior temporal interval would help in providing reviews and rating that are close in time and that would encourage the user to visit the counterparty which would therefore make the method/system more accurate.
As to Claim 40, Yahia teaches a device (client device 110 and 112), comprising:a communications interface; (0063: communications interface),a memory storing instructions; and (0063: memory),at least one processor (0063: one or more processors to perform the functions of the invention) coupled to the communications interface (0063: communications interface), and to the memory (0063: memory), the at least one processor being configured to execute the instructions to: (0063: one or more processors to perform the functions of the invention),transmit query data to a computing system via the communications interface (0044: generating the relevant context and transmits the relevant context as a result set of one or more attribute-value… display via the user interface 101 as an annotation for a given review… 0044: present the given item of content for display in conjunction with subjective and objective attributes of the item of content on a client device 110 and 112 via the network 109.), the query data comprising a value (Fig. 5: rating example 3 out 5) of a query parameter (0010: assigning a value to one or more of the one or more objective attributes… 0031: the objective attributes for a restaurant item of content may comprise: type of cuisine, the location, and the name of the chef. The corresponding values may comprise: French, Manhattan, and Jean Georges. According to another embodiment, the objective attributes for a movie item of content may comprise: title, actor, and genre. The corresponding values may comprise: Mission Impossible, Tom Cruise, and Action), (0047: a value for the objective attribute of the item of content is obtained… if the movie was Pirates of the Caribbean, values for the objective attributes may comprise "Pirates of the Caribbean" for the title, "Johnny Depp" for an actor, and "Adventure" for a genre. Additionally, if the restaurant was, for example, Daniel, values for the objective attributes may comprise, "Daniel" for the name of the restaurant, "French" for the type of cuisine, "Daniel Boulud" for the chef, "Upper East Side" for the neighborhood, and "Very Expensive" for the cost), and (0010: assigning a value to one or more of the one or more objective attributes, and identifying one or more subjective attributes associated with a given item in the initial collection of content items), and the computing system being configured to, based on the query data (abstract: receiving a query identifying a given content item… 0047: the movie was Pirates of the Caribbean, values for the objective attributes may comprise "Pirates of the Caribbean" for the title, "Johnny Depp" for an actor, and "Adventure" for a genre. Additionally, if the restaurant was, for example, Daniel, values for the objective attributes may comprise, "Daniel" for the name of the restaurant, "French" for the type of cuisine, "Daniel Boulud" for the chef, "Upper East Side" for the neighborhood, and "Very Expensive" for the cost), obtain elements of aggregated review data from a data repository (0056: collecting data on the user explicitly (e.g., asking him to rate certain items of content… 0063: from a memory), receive, from the computing system via the communications interface, response data that includes at least a subset of the elements of aggregated review data (0036: values may comprise the text of such a review or score of such a ranking) that are consistent with the query parameter value; and; (0036: a given item of content may also be associated with one or more subjective attributes and values. Subjective attributes may comprise user reviews or rankings, and subjective values may comprise the text of such a review or score of such a ranking. The subjective values of a given item of content are generally submitted by clients 110, 111 or 112 to the system. While subjective attributes according to one embodiment may be characterized as general user reviews or rankings of an item of content (e.g., an overall user review or score of a restaurant), the subjective attributes may also be broken down into components. For example, where the item of content is a restaurant, subjective attributes may comprise: quality of the food, decor, service, and cost. A given component may then be reviewed or scored independently. The reviewers of the items of content may comprise both professionals in the trade (e.g., newspaper columnists, magazine editors, and the like), as well as ordinary individuals that frequent the social review system 100. In accordance with one embodiment, ordinary individuals may elevate their status based on the previous number of reviews they have written or their familiarity with a specific item of content), and (0044: generating the relevant context and transmits the relevant context as a result set of one or more attribute-value… display via the user interface 101 as an annotation for a given review.), and (0037: The user interface 101 may present the given item of content for display in conjunction with subjective and objective attributes of the item of content on a client device 110 and 112 via the network 109. Upon a specified event, the user interface 101 may pass the query to the domain application processor 102 to determine whether context exists for the one or more subjective attributes of a given item of content.).
Yahia does not teach each of the elements of aggregated review data being associated with a candidate counterparty, each of the elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty.
However Roberts teaches each of the elements of aggregated review data being associated with a candidate counterparty (Examiners note: counterparty as mentioned in the spec is a merchant), (See Fig. 27: Merchant is Little taste of India which is associated with aggregated review data such as 3.0 stars from evan hayes and another review from Stu Roberts 4.5 star), each of the elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty, (can be the reviews listed from different people who tried the restaurant), and (Fig. 27: review can include aggregated value is the avg rating on 2.9 and 3.0 of Fig. 27 1234 and has prior reviews such as prior review from evan hayes and another review from Stu Roberts 4.5 star), and (0046: display a user interface such as that shown in FIG. 27. The user interface of FIG. 27 displays a list of star ratings 1264 and associated reviews 1266 (collectively referred to as feedback) submitted by users 1268. The users 1268 and their associated star ratings 1264 and reviews 1266 are listed in order of descending correlation values 1234. In this way, the a user viewing the user interface of FIG. 27 is presented with the most relevant feedback from other users about the restaurant first with less relevant feedback about the restaurant being provide lower and/or later in the list of feedback. In some embodiments, a correlation relevancy value 1270 can be provided. In some embodiments, the correlation relevancy value 1270 can be provided as an output and/or function of an output of the recalculation module 120.),
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia to include each of the elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty of Roberts. Motivation to do so comes from the knowledge well known in the art that each of the elements of aggregated review data comprising an aggregate value characterizing one or more prior reviews associated with exchanges of data that involve the candidate counterparty would provide a value like rating that would help the user determine which counterparty to visit and that would promote an increase in the sales and would therefore make the method/system more profitable for the counterparty.
Yahia does not teach the data exchanges being during a prior temporal interval.
However Suvajac teaches the data exchanges being during a prior temporal interval; and (0003: determine a value characterizing a probability that the first counterparty performs the data exchange in accordance with the at least one parameter value during a temporal interval).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia to include the data exchanges being during a prior temporal interval of Suvajac. Motivation to do so comes from the knowledge well known in the art that the data exchanges being during a prior temporal interval would help in providing reviews and rating that are close in time and that would encourage the user to visit the counterparty which would therefore make the method/system more accurate.
B. Claims 24 and 35 are rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Yahia et al., (U.S. Patent Application Publication No. 20130138644) in view of Roberts, (U.S. Patent Application Publication No. 20160335683) in view of Suvajac et al., (U.S. Patent Application Publication No. 20200104911) in view of Lessin, (U.S. Patent Application Publication No. 20140280322).
As to Claim 24, Yahia, Roberts, and Suvajac teach the apparatus of claim 23.
Yahia, Roberts, and Suvajac do not teach the at least one query parameter value comprises a value of a geographic characteristic; each of the first elements of aggregated review data comprises a candidate value of a geographic characteristic and the at least one processor is further configured to execute the instructions to determine, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on a comparison between the value of the geographic characteristic and the candidate value.
However Lessin teaches wherein:the at least one query parameter value comprises a value of a geographic characteristic; each of the first elements of aggregated review data comprises a candidate value of a geographic characteristic and the at least one processor is further configured to execute the instructions to determine, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on a comparison between the value of the geographic characteristic and the candidate value; (0022: A search results listing 110 for a search query 102 may include other objects maintained by the social networking system 100. For example, a search results listing 110 includes content posts by social networking system users, pages, groups, and other entities connected to viewing users in the social networking system 100, pages, groups, users, events, applications, topics, interests, entities, claims, and any other suitable objects maintained by the social networking system 100. For example, a user provides a search query 102 for "people nearby that are hungry." In this example, the query analysis module 114 interprets "nearby" as a location query and limits search results to users within a threshold geographic distance to the location associated with the searching user 124. A geographic location module 120 may retrieve the current geographic location of connected users 126 to the searching user 124 based on status updates, check in events, and/or other content items or communications with the social networking system 100 providing a geographic location to the social networking system 100. Other search queries may include specific geographic locations, such as "best restaurants in Palo Alto," or "fun things to do in Paris." Search results based on search queries 102 including a specific location include objects associated with the specific location, such as check-in events associated with the location specified by the search query 102, third-party website reviews associated with the specified location and stored by the social networking system 100, user-generated lists of activities associated with the specified location, or any other suitable object associated with the specified location).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia, Roberts, and Suvajac to include determine, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on a comparison between the value of the geographic characteristic and the candidate value of Lessin. Motivation to do so comes from the knowledge well known in the art that determine, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on a comparison between the value of the geographic characteristic and the candidate value would help in provide a more accurate counterparty that the user would be interested in and visit and that would which would therefore make the method/system more profitable.
As to Claim 35, Yahia, Roberts, and Suvajac teach the computer-implemented method of claim 34.
Yahia, Roberts, and Suvajac do not teach wherein: the at least one query parameter value comprises a value of a geographic characteristic; each of the first elements of aggregated review data comprises a candidate value of a geographic characteristic; and the determining comprises determining, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on a comparison between the value of the geographic characteristic and the candidate value.
However Lessin teaches wherein: the at least one query parameter value comprises a value of a geographic characteristic; each of the first elements of aggregated review data comprises a candidate value of a geographic characteristic; and the determining comprises determining, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on a comparison between the value of the geographic characteristic and the candidate value; (0022: A search results listing 110 for a search query 102 may include other objects maintained by the social networking system 100. For example, a search results listing 110 includes content posts by social networking system users, pages, groups, and other entities connected to viewing users in the social networking system 100, pages, groups, users, events, applications, topics, interests, entities, claims, and any other suitable objects maintained by the social networking system 100. For example, a user provides a search query 102 for "people nearby that are hungry." In this example, the query analysis module 114 interprets "nearby" as a location query and limits search results to users within a threshold geographic distance to the location associated with the searching user 124. A geographic location module 120 may retrieve the current geographic location of connected users 126 to the searching user 124 based on status updates, check in events, and/or other content items or communications with the social networking system 100 providing a geographic location to the social networking system 100. Other search queries may include specific geographic locations, such as "best restaurants in Palo Alto," or "fun things to do in Paris." Search results based on search queries 102 including a specific location include objects associated with the specific location, such as check-in events associated with the location specified by the search query 102, third-party website reviews associated with the specified location and stored by the social networking system 100, user-generated lists of activities associated with the specified location, or any other suitable object associated with the specified location).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia, Roberts, and Suvajac to include determining, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on a comparison between the value of the geographic characteristic and the candidate value of Lessin. Motivation to do so comes from the knowledge well known in the art that determining, for at least one of the first elements of aggregated review data, that the corresponding candidate counterparty is consistent with the query parameter value based on a comparison between the value of the geographic characteristic and the candidate value would help in provide a more accurate counterparty that the user would be interested in and visit and that would which would therefore make the method/system more profitable.
C. Claim 30 is rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Yahia et al., (U.S. Patent Application Publication No. 20130138644) in view of Roberts, (U.S. Patent Application Publication No. 20160335683) in view of Suvajac et al., (U.S. Patent Application Publication No. 20200104911) in view of Singh et al., (U.S. Patent Application Publication No. 20170041437).
As to Claim 30, Yahia, Roberts, and Suvajac teach the apparatus of claim 29.
Yahia, Roberts, and Suvajac do not teach wherein the at least one processor is further configured to execute the instructions to:receive, via the communications interface, a message associated with the additional data exchange, the message comprising the elements of message data disposed within corresponding message fields, and the message fields being structured in accordance with a standardized data- exchange protocol; obtain, from the memory, mapping data associated with the message fields of the received message; and perform operations that obtain the elements of message data from message fields based on the mapping data, and that store the elements of message data within the memory.
However Singh teaches wherein the at least one processor is further configured to execute the instructions to:receive, via the communications interface, a message associated with the additional data exchange, the message comprising the elements of message data disposed within corresponding message fields, and the message fields being structured in accordance with a standardized data- exchange protocol; obtain, from the memory, mapping data associated with the message fields of the received message; and perform operations that obtain the elements of message data from message fields based on the mapping data, and that store the elements of message data within the memory; (See Fig. 3a and 3b), and (0040: A server (e.g., server 100 in FIG. 1) may determine (e.g., predict) the application function 146-4 as a subsequent application function that a user of the client computer device 140 may use after using the application function 146-1. For example, the server may determine that a user may message a contact about a restaurant when the user is reading a review of the restaurant in the application view 46-1. The server may select a value for the drop-down 260 to be a contact with whom the user of the client computing device 140 communicates most frequently. The server may select a value for the drop-down 260 to be the last contact with whom the user of the client computing device 140 communicated. The server may select a default message as a value for the text field 262. The server may select a value for the text field 262 based on the contextual data received from the client computing device 140. For example, the contextual data may indicate historical messages that the user may have sent to the contact indicated by the drop-down 260. The user may change the value of the drop-down 260 and the text field 262. For example, the user can send the message to Veronica instead of Betty.), and (0051-0054).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia, Roberts, and Suvajac to include perform operations that obtain the elements of message data from message fields based on the mapping data, and that store the elements of message data within the memory of Singh. Motivation to do so comes from the knowledge well known in the art that perform operations that obtain the elements of message data from message fields based on the mapping data, and that store the elements of message data within the memory would help in provide a more accurate counterparty that the user would be interested in and visit and that would which would therefore make the method/system more accurate.
D. Claim 31 is rejected under pre-AIA 35 U.S.C. 103(a) as being unpatentable over Yahia et al., (U.S. Patent Application Publication No. 20130138644) in view of Roberts, (U.S. Patent Application Publication No. 20160335683) in view of Suvajac et al., (U.S. Patent Application Publication No. 20200104911) in view of Singh et al., (U.S. Patent Application Publication No. 20170041437) in view of Miller et al., (U.S. Patent Application Publication No. 20200005258).
As to Claim 31, Yahia, Roberts, and Suvajac teach the apparatus of claim 29.
Yahia further teaches generate notification data comprising the identifier of the first counterparty and digital content , and to transmit the notification data to the device via the communications interface prior to the execution of the additional data exchange; (Examiner interpret this limitations to be the display of the review into an application on a users device for the user to read the review of the restaurant found in 0044: generating the relevant context and transmits the relevant context as a result set of one or more attribute-value… display via the user interface 101 as an annotation for a given review… 0044: present the given item of content for display in conjunction with subjective and objective attributes of the item of content on a client device 110 and 112 via the network 109.).
Yahia, Roberts, and Suvajac do not teach the additional data exchange involves the first counterparty and a second counterparty the device being operable by the second counterparty;the device is configured to execute an application program, the executed additional application program causing the device to initiate the additional data exchange; and
the at least one processor is further configured to execute the instructions to:determine a value of a parameter of the additional data exchange based on an application.
However Singh teaches wherein the at least one processor is further configured to execute the instructions to:receive, via the communications interface, a message associated with the additional data exchange, the message comprising the elements of message data disposed within corresponding message fields, and the message fields being structured in accordance with a standardized data- exchange protocol; obtain, from the memory, mapping data associated with the message fields of the received message; and perform operations that obtain the elements of message data from message fields based on the mapping data, and that store the elements of message data within the memory; wherein:the additional data exchange involves the first counterparty (0040: restaurant) and a second counterparty (0040: client computing device 140), the device being operable by the second counterparty; (0040: users device and also See Fig. 3a and 3b: Mobile device),the device is configured to execute an application program, the executed additional application program causing the device to initiate the additional data exchange; and (0041: represents an application function 146-4), and (Fig. 3a and 3b),the at least one processor is further configured to execute the instructions to:determine a value of a parameter of the additional data exchange based on an application; and (0112: machine instructions for a programmable processor, and can be implemented in a high-level procedural and/or object-oriented programming language, and/or in assembly/machine language… for 0040: a restaurant when the user is reading a review of the restaurant in the application view 46-1).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia, Roberts, and Suvajac to include determine a value of a parameter of the additional data exchange based on an application of Singh. Motivation to do so comes from the knowledge well known in the art that determine a value of a parameter of the additional data exchange based on an application would help in provide a more accurate counterparty that the user would be interested in and visit and that would therefore make the method/system more accurate.
Yahia, Roberts, and Suvajac do not teach a trained machine learning or artificial intelligence process to textual content associated with at least one of the elements of message data.
However Miller teaches a trained machine learning or artificial intelligence process to textual content associated with at least one of the elements of message data; and (0018: As described herein, the content provisioning system may also perform operations that classify the groups of the recognized textual content in accordance with corresponding classifications parameters, e.g., based on an application of one or more machine learning algorithms to each of the groups of textual content. The classification parameters may, in some instances, be associated with the data exchange and additionally or alternatively, with the document identified by the received image data. The machine learning algorithms may include, but are not limited to, a one-dimensional, convolutional neural network model, and the one or more machine learning algorithms may be trained against, and adaptively improved using, elements of previously classified image data identifying documents associated with the data exchange (e.g., as maintained locally by the content provisioning system), and (0019: Subsequent to classifying the textual content, the content provisioning system may further process each element of the classified textual content to identify, and extract, a value characterizing the corresponding one of the classification parameters, e.g., based on an application of one or more additional machine learning algorithms to each of the elements of textual content. By way of the example, the additional machine learning algorithms may include, but are not limited to, an adaptive natural language processing algorithm that, among other things, predicts starting an ending indices of a candidate parameter value within each element of textual content, extracts the candidate parameter value in accordance with the predicted indices, and computes a confidence score for the candidate parameter value that reflects a probability that the candidate parameter value accurately represents the corresponding classification parameter. As described herein, the one or more additional machine learning algorithms may be trained against, and adaptively improved using, the locally maintained elements of previously classified image data identifying documents associated with the data exchange).
It would have been obvious to one of ordinary skill in the art at the time of the invention to modify Yahia, Roberts, and Suvajac to include a trained machine learning or artificial intelligence process to textual content associated with at least one of the elements of message data of Miller. Motivation to do so comes from the knowledge well known in the art that a trained machine learning or artificial intelligence process to textual content associated with at least one of the elements of message data would help in provide a more accurate data that would help in the determination of values and that would therefore make the method/system more accurate.
NPL Reference
5. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. The NPL “Venmo’ed: Sharing Your Payment Data With the World” describes “The app Venmo has quickly become one of the most popular mobile, peer-to-peer payment platforms among Millennials in the United States. The app allows users to pay each other and share the payment message, recipient and time with other users of the app. In the past Venmo has had its share of security and privacy issues and has even been the target of regulatory action [12]. Despite this, Venmo has continued to have features and designs that publicly reveal large amounts of user data. In addition to the privacy implications of revealing user data, previous papers have shown that this information can be used in social engineering attacks to defraud users [10]. I hypothesized that Venmo’s payment sharing feature, which defaults to sharing all transactions publicly with any user of the app, causes users to leak sensitive personal data about themselves, and that the problem is widespread.”.
Pertinent Art
6. The prior art made of record and not relied upon is considered pertinent to applicant's disclosure. Reference#US11163846B1 teaches similar invention which describes the system is programmed to receive a user query, generally associated with a buyer account and related to a procurement activity, such as ordering, approval, purchase, inventory, expense reporting, audit, or market analysis. The system is programmed to next identify a query context based on the collected data or other external data. The query context can include buyer data derived from the identity of the buyer account, or other data derived from the user query. For example, the query may refer to a broad product category or a specific product make and model. The query context can then include the corresponding supplier data. The query may also include general product descriptions, such as “on sale” or “four-star reviews”, and the query context may include data retrieved from internal accounts or external sources in real time. The system is programmed to ultimately include a list of key-value pairs in the query context, where the key correspond to possible input parameters of the recommendation models and the values are included in the user query or derived from the database or external sources.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to TAREK ELCHANTI whose telephone number is (571) 272-9638. The examiner can normally be reached on Flex Mon - Thur 7-7:00 and Fri 7-4:00.
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/TAREK ELCHANTI/Primary Examiner, Art Unit 3621B