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
This non-final Office action is in response to applicant’s communication received on January 27, 2025, wherein claims 21-40 are currently pending.
Double Patenting
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 USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The 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/process/file/efs/guidance/eTD-info-I.jsp.
Claims 21-40 of current application 19/033,423 (hereinafter ‘423) are rejected on the ground of nonstatutory double patenting as being as being unpatentable over claims 1, 2, and 8 of U.S. Patent No. 12,265,972 (hereinafter ‘972) in view of Palakovich et al., (US 2016/0099892). Although the claims at issue are not identical, they are not patentably distinct from each other because the independent claims of the current application ‘423 are mostly encompassed in the claims presented in Pat. ‘972. Most claimed concepts in the current application ‘423 are disclosed by Pat. ‘972 – see Table 1 below. Additionally, one of ordinary skill in the art would have recognized the slight differences between the claim language/limitations of the corresponding claims as being directed towards intention, non-functional and non-structural field-of-use language, slight variations in terminology, or obvious variants of claim elements, and therefore these claims are not patentably distinct from one another despite these slight differences. The Applicant may have reworded some of the limitations of the independent and dependent claims but the concepts claimed in the current application are all also presented in the claims of patent ‘972.
Regarding Applicant’s claims 21, 27, 32, and 39 (in ‘423), claims for Pat ‘972 does not explicit state unsatisfactory interaction with a virtual agent. Analogous art Palakovich discloses unsatisfactory interaction with a virtual agent (¶¶ 0041 [recognize when a virtual assistant is unable to satisfy…issues], 0064 [virtual agent…unable to satisfy…user’s needs…escalation (to another agent)]).
Therefore, it would be obvious to one of ordinary skill in the art to include in ‘972 unsatisfactory interaction with a virtual agent as taught by analogous art Palakovich in order to provide customers/users with optimal service experience and resolve all issues since doing so could be performed readily by any person of ordinary skill in the art, with neither undue experimentation, nor risk of unexpected results (TSM/KSR-G); and also since one of ordinary skill in the art at the time of the invention would have recognized that applying the known technique and concepts of Palakovich would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such concepts and features into similar systems (TSM/KSR-D). (See (1) 2007 Examination Guidelines for Determining Obviousness Under 35 U.S.C. 103 in View of the Supreme Court Decision in KSR International Co. v. Teleflex Inc. - Federal Register, Vol. 72, No. 195, October 10, 2007, pages 57526-57535; (2) 2010 Examination Guidelines Updated Developments in the Obviousness Inquiry After KSR v. Teleflex. -Federal Register, Vol. 75, No. 169, September 01, 2010, pages 53643-53660; and (3) materials posted at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidelines-training-materials-view-ksr).
Regarding Applicant’s claims 23 and 29 (in ‘423), claims of Pat ‘972 does not explicit state data pre-processed locally at an edge device (note that edge device is a user device – Applicant’s specification para. 0059). Analogous art Palakovich discloses data collected and pre-processed locally at an edge device (¶¶ 0002 [executed on user devices], 0025 [browser executing on a client device and is presented with a user interface input element…module…launched by the client device…upon receipt of the chat initialization message, determines a chat queue for the new chat]; see also 0049-0052).
Therefore, it would be obvious to one of ordinary skill in the art to include in ‘972 data pre-processed locally at an edge device as taught by analogous art Palakovich in order to further make is convenient for the user to get optimal service experience since doing so could be performed readily by any person of ordinary skill in the art, with neither undue experimentation, nor risk of unexpected results (TSM/KSR-G); and also since one of ordinary skill in the art at the time of the invention would have recognized that applying the known technique and concepts of Palakovich would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such concepts and features into similar systems (TSM/KSR-D). (See (1) 2007 Examination Guidelines for Determining Obviousness Under 35 U.S.C. 103 in View of the Supreme Court Decision in KSR International Co. v. Teleflex Inc. - Federal Register, Vol. 72, No. 195, October 10, 2007, pages 57526-57535; (2) 2010 Examination Guidelines Updated Developments in the Obviousness Inquiry After KSR v. Teleflex. -Federal Register, Vol. 75, No. 169, September 01, 2010, pages 53643-53660; and (3) materials posted at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidelines-training-materials-view-ksr).
Table 1 (exemplary):
19/033,423 (current application)
Pat. No. 12,265,972
Claims 21, 27, 39
Claims 1, 2, 14, 15 (obvious in view of Palakovich – see above)
Claims 22, 28
Claims 1 and 2
Claims 23, 29
Claims 1 and 2 (obvious in view of Palakovich – see above)
Claim 24, 25, 30, 31
Claims 1 and 4
Claim 32
Claim 1 (obviousness in view Palakovich – see above)
Claims 26, 33, 40
Claim 1
Claim 34
Claim 12
Claim 35
Claim 3
Claim 36
Claims 4, 12, and 13
Claims 37
Claims 12 and 13
Claim 38
Claims 1 and 4
Claim Rejections - 35 USC § 101
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 non-statutory subject matter.
Regarding Step 1 (MPEP 2106.03) of the subject matter eligibility test per MPEP 2106.03, claims 21-26 are directed to a system (i.e. machine), claims 27-38 are directed to a method (i.e., process), and claim 39-40 are directed to non-transitory computer readable media (i.e. product or article of manufacture). Accordingly, all claims are directed to one of the four statutory categories of invention.
(Under Step 2) The claimed invention is directed to an abstract idea without significantly more.
(Under Step 2A, Prong 1 (MPEP 2106.04)) The independent claims (21, 27, 39) are directed to is directed towards customer service and customer experience and recite accessing/obtaining information/data (where the information is abstract in nature – e.g. request data (service request, time, locations, etc.,), user input (and according to specification – also insight information, feedback information, etc.,)), query information, requests, intent, type of service, etc.,), analyzing and manipulating information to get more information to use (e.g. comparing information, identifying, arranging/rearranging information, etc.,), , and providing/displaying the resulting information for further analysis and decision-making (proposals, recommendation, personalization, etc.,). The limitations of the independent claims (21, 27, 39), under the broadest reasonable interpretation, covers methods of organizing human activity (fundamental economic principles or practices (customer service and customer experience); commercial interactions (business relations – business-customer interactions); and managing behavior and interactions (agent-user/customer interaction and behavior and following rules or instructions)). If a claims limitation, under its broadest reasonable interpretation, covers the performance of the limitation as fundamental economic principles or practices (including hedging, insurance, mitigating risk); commercial or legal interactions (including agreements in the form of contracts; legal obligations; advertising, marketing or sales activities or behaviors; business relations); managing personal behavior or relationships or interactions between people (including scheduling, social activities, teaching, and following rules or instructions), then it falls within the “organizing human activities” grouping of abstract ideas. (MPEP 2106.04).
Accordingly, since Applicant's claims fall under organizing human activities grouping the claims recite an abstract idea.
(Under Step 2A, prong 2 (MPEP 2106.04(d))) This judicial exception is not integrated into a practical application because but for the recitation of old/well-known generic/general-purpose computing/technology components/elements/terms (system, machine learning (only stated and no details provided), memory, processor, virtual, generic list of possible learning algorithms (only stating “using at least one of a deep neural network, a convolutional neural network (CNN), or recurrent neural network (RNN)” without showing any technical details on how they are applied/used), digitally communicate, Application Programming Interface (APIs), (in independent claim 21); devices, virtual, digitally communicate, (in independent claim 27); non-transitory computer-readable media, processors, virtual, digitally communicate (in independent claim 39)), in the context of the independent claims (21, 27, 39), the claims encompass the above stated abstract idea (organizing human activity (managing inventory and construction sites in view of abstract information (fundamental economic activity and managing behavior/interactions by following rules or instructions)) and mathematical concepts (using mathematical techniques and using the results of the techniques)).
As shown above, the independent claims recite generic/general-purpose computing/technology components/elements/terms/limitations (system, machine learning (only stated and no details provided), memory, processor, virtual, generic list of possible learning algorithms (only stating “using at least one of a deep neural network, a convolutional neural network (CNN), or recurrent neural network (RNN)” without showing any technical details on how they are applied/used), digitally communicate, Application Programming Interface (APIs), (in independent claim 21); devices, virtual, digitally communicate, (in independent claim 27); non-transitory computer-readable media, processors, virtual, digitally communicate (in independent claim 39)) which are recited at a high level of generality performing generic/general purpose computer/computing functions. (MPEP 2106.04). The generic/general-purpose computing/technology components/elements/terms/limitations are no more than mere instructions to apply the judicial exception (the above abstract idea) in an apply-it fashion using generic/general-purpose computing/technology components/elements/terms/limitations (see list/listing above). The CAFC has stated that it is not enough, however, to merely improve abstract processes by invoking a computer merely as a tool. Customedia Techs., LLC v. Dish Network Corp., 951 F.3d 1359, 1364 (Fed. Cir. 2020). The focus of the claims is simply to use computers and a familiar network as a tool to perform abstract processes (discussed above) involving simple information exchange. Carrying out abstract processes involving information exchange is an abstract idea. See, e.g., BSG, 899 F.3d at 1286; SAP America, 898 F.3d at 1167-68; Affinity Labs of Tex., LLC v. DIRECTV, LLC, 838 F.3d 1253, 1261-62 (Fed. Cir. 2016). And use of standard computers and networks to carry out those functions—more speedily, more efficiently, more reliably—does not make the claims any less directed to that abstract idea. See Alice Corp., 573 U.S. at 222-25; Customedia, 951 F.3d at 1364; Trading Techs. Int'l, Inc. v. IBG LLC, 921 F.3d 1084, 1092-93 (Fed. Cir. 2019); SAP America, 898 F.3d at 1167; Intellectual Ventures I LLC v. Symantec Corp., 838 F.3d 1307, 1314 (Fed. Cir. 2016); Electric Power Grp., LLC v. Alstom S.A., 830 F.3d 1350, 1353, 1355 (Fed. Cir. 2016); Intellectual Ventures I LLC v. Capital One Bank (USA), 792 F.3d 1363, 1367, 1370 (Fed. Cir. 2015); buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355 (Fed. Cir. 2014). Accordingly, the additional elements (see list/listing above) do not integrate the abstract idea in to a practical application because it does not impose any meaningful limits on practicing the abstract idea – i.e. they are just post-solution/extra-solution activities.
(Under Step 2B (MPEP 2106.05)) The independent claims (21, 27, 39) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims do not recite an improvement to another technology or technical field, an improvement to the functioning of the computer itself, or meaningful limitations beyond generally linking the use of an abstract idea to a particular technological environment. The independent claims recite using additional elements that are known generic/general-purpose computing/technology components/elements/terms/limitations (system, machine learning (only stated and no details provided), memory, processor, virtual, generic list of possible learning algorithms (only stating “using at least one of a deep neural network, a convolutional neural network (CNN), or recurrent neural network (RNN)” without showing any technical details on how they are applied/used), digitally communicate, Application Programming Interface (APIs), (in independent claim 21); devices, virtual, digitally communicate, (in independent claim 27); non-transitory computer-readable media, processors, virtual, digitally communicate (in independent claim 39)). For the role of a computer in a computer implemented invention to be deemed meaningful in the context of this analysis, it must involve more than performance of "well-understood, routine, [and] conventional activities previously known to the industry." Alice Corp. v. CLS Bank Int'l, 110 USPQ2d 1976 (U.S. 2014), at 2359 (quoting Mayo, 132 S. Ct. at 1294 (internal quotation marks and brackets omitted)). These activities as claimed by the Applicant are all well-known and routine tasks in the field of art – as can been seen in the specification of Applicant’s application (for example, see Applicant’s specification at, for example, figure 4 and Pages 24-25 [where Applicant recites general-purpose/generic computers/processors/etc., and generic/general-purpose computing components/devices/etc., in Applicant’s specification]) and/or the specification of the below cited art (used in the rejection below and on the PTO-892) and/or also as noted in the court cases in §2106.05 in the MPEP. Further, "the mere recitation of a generic computer cannot transform a patent ineligible abstract idea into a patent-eligible invention." Alice at 2358. None of the hardware offers a meaningful limitation beyond generally linking the system to a particular technological environment, that is, implementation via computers. Adding generic computer components to perform generic functions that are well‐understood, routine and conventional, such as gathering data, performing calculations, and outputting a result would not transform the claims into eligible subject matter. Abstract ideas are excluded from patent eligibility based on a concern that monopolization of the basic tools of scientific and technological work might impede innovation more than it would promote it. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims require no more than a generic computer to perform generic computer functions. The additional elements (system, machine learning (only stated and no details provided), memory, processor, virtual, generic list of possible learning algorithms (only stating “using at least one of a deep neural network, a convolutional neural network (CNN), or recurrent neural network (RNN)” without showing any technical details on how they are applied/used), digitally communicate, Application Programming Interface (APIs), (in independent claim 21); devices, virtual, digitally communicate, (in independent claim 27); non-transitory computer-readable media, processors, virtual, digitally communicate (in independent claim 39)) or combination of elements in the claims other than the abstract idea per se amounts to no more than: (i) mere instructions to implement the idea on a computer, and/or (ii) recitation of generic computer structure that serves to perform generic computer functions that are well-understood, routine, and conventional activities previously known to the pertinent industry. Applicant is directed to the following citations and references: Digitech Image., LLC v. Electronics for Imaging, Inc. (758 F.3d 1344 (2014) discussing U.S. Patent No. 6,128,415); and (2) Federal register/Vol. 79, No 241 issued on December 16, 2014, page 74629, column 2, Gottschalk v. Benson. Viewed as a whole, the independent claims do not purport to improve the functioning of the computer itself, or to improve any other technology or technical field. Use of an unspecified, generic computer does not transform an abstract idea into a patent-eligible invention. Thus, the independent claims do not amount to significantly more than the abstract idea itself. See Alice Corp. v. CLS Bank Int'l, 110 USPQ2d 1976 (U.S. 2014).
The dependent claims (22-26, 28-38, 40) further define the independent claims and merely narrow the described abstract idea, but not adding significantly more than the abstract idea. The dependent claims either individually or in combination are merely an extension of the abstract idea itself. The above rejection discussed for the independent claims fully applies to the dependent claims.
The dependent claims (22-26, 28-38, 40) further state using obtained data/information (where the information is abstract in nature – e.g. request data (service request, time, locations, etc.,), user input (and according to specification – also insight information, feedback information, etc.,)), query information, requests, intent, type of service, etc.,), analyzing and manipulating information to get more information to use (e.g. comparing information, identifying, arranging/rearranging information, etc.,), , and providing/displaying the resulting information for further analysis and decision-making (proposals, recommendation, personalization, etc.,). These dependent claims also cover methods of organizing human activity (organizing human activity (fundamental economic principles or practices (customer service and customer experience); commercial interactions (business relations – business-customer interactions); and managing behavior and interactions (agent-user/customer interaction and behavior and following rules or instructions))).
This judicial exception is not integrated into a practical application because the claims and specification recite additional elements as generic/general-purpose computing/technology components/elements/terms/limitations (system, processor, edge device, virtual, (in claim 21’s dependent claims 22-26); edge devices (user devices), virtual, digitally communicate, Application Programming Interface (APIs) (in claim 27’s dependent claims 28-38); non-transitory computer-readable media, virtual (in claim 39’s dependent claim 40)) performing generic computer/computing/technology functions. (MPEP 2106.04). The dependent claims merely use the same general technological environment and instructions as the independent claims above to implement the abstract idea. The generic/general-purpose computing/technology components/elements/terms/limitations are no more than mere instructions to apply the judicial exception (the above abstract idea – organizing human activity (fundamental economic principles or practices (customer service and customer experience); commercial interactions (business relations – business-customer interactions); and managing behavior and interactions (agent-user/customer interaction and behavior and following rules or instructions))) in an apply-it fashion using generic/general-purpose computing/technology components/elements/terms/limitations (system, processor, edge device, virtual, (in claim 21’s dependent claims 22-26); edge devices (user devices), virtual, digitally communicate, Application Programming Interface (APIs) (in claim 27’s dependent claims 28-38); non-transitory computer-readable media, virtual (in claim 39’s dependent claim 40)). Hence, the additional elements (system, processor, edge device, virtual, (in claim 21’s dependent claims 22-26); edge devices (user devices), virtual, digitally communicate, Application Programming Interface (APIs) (in claim 27’s dependent claims 28-38); non-transitory computer-readable media, virtual (in claim 39’s dependent claim 40)) do not integrate the abstract idea in to a practical application because they does not impose any meaningful limits on practicing the abstract idea – i.e. they are just post-solution/extra-solution activities.
Also, the dependent claims either individually or in combination are merely an extension of the abstract idea itself and the dependent claims (similar to the independent claims) do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the claims require no more than a generic computer to perform generic computer functions. The additional elements (system, processor, edge device, virtual, (in claim 21’s dependent claims 22-26); edge devices (user devices), virtual, digitally communicate, Application Programming Interface (APIs) (in claim 27’s dependent claims 28-38); non-transitory computer-readable media, virtual (in claim 39’s dependent claim 40)) or combination of elements in the dependent claims other than the abstract idea per se amounts to no more than: (i) mere instructions to implement the idea on a computer, and/or (ii) recitation of generic computer structure that serves to perform generic computer functions that are well-understood, routine, and conventional activities previously known to the pertinent industry. Applicant is directed to the following citations and references: Digitech Image., LLC v. Electronics for Imaging, Inc. (758 F.3d 1344 (2014) discussing U.S. Patent No. 6,128,415); and (2) Federal register/Vol. 79, No 241 issued on December 16, 2014, page 74629, column 2, Gottschalk v. Benson. Viewed as a whole, dependent claims do not purport to improve the functioning of the computer itself, or to improve any other technology or technical field. Use of an unspecified, generic computer does not transform an abstract idea into a patent-eligible invention. Thus, dependent claims also do not amount to significantly more than the abstract idea itself. See Alice Corp. v. CLS Bank Int'l, 110 USPQ2d 1976 (U.S. 2014).
Claim Rejections - 35 USC § 102
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 (i.e., changing from AIA to pre-AIA ) 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 the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claims 27-37, 39-40 are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Palakovich et al., (US 2016/0099892).
As per claim 27, Palakovich discloses a method, comprising:
determining, by one or more devices, to process a request using a virtual agent that is configured to digitally communicate with one or more third-party service suppliers (¶¶ 0008-0011 [chat…virtual agent…chat server…chatting…user and a virtual agent…receiving, at the chat server, a first message for a chat from a client device of an end user (request); with 0031 [chat server…virtual agent…messages received…user…merchant…using the chat service], 0039 [virtual agent conversational…chat dialog], 0054 [transmits a request; with 0093]]);
processing, by the one or more devices and based on determining to process the request using the virtual agent, request data, related to the request, to determine a type of service (¶¶ 0011 [updating a chat log based upon the first message, and sending the first message to the virtual agent (processing request); with 0025-0027 [receipt of the chat initialization message…selecting…based on topic…virtual agent module…messages received…API…updates]);
routing, by the one or more devices and based on the virtual agent corresponding to the type of service, the request to the virtual agent (¶¶ 0011 [chat…including…virtual agent…sending first/initial message/request (see above 0025-0027 discussion regarding type of service) to the virtual agent], 0047 [routing communication…between user…virtual agents]); and
redirecting, by the one or more devices and based on the virtual agent determining that an intent has changed or that a dialog with the virtual agent is unsatisfactory, to a different agent that is different from the virtual agent (¶¶ 0027 [indicator of an escalation of a chat from a virtual agent to a live agent (live agent is different agent from virtual agent); with 0035 [escalation when virtual agent is slow…chant event… the virtual agent has not responded in a particular period of time or cannot provide an answer (dialog is unsatisfactory)]]; also 0043 [ through use of the virtual agent proxy module, one or more different virtual agents may seamlessly be used in a same chat system…chats may even seamlessly be shifted from one type of virtual agent to another type of virtual agent]).
As per claim 39, claim 39 discloses substantially similar limitations as claim 27 above; and therefore claim 39 is rejected under the same rationale and reasoning as presented above for claim 27.
As per claim 28, Palakovich discloses the method of claim 27, further comprising: receiving, from an edge device, the request data collected at the edge device ((note that edge device is a user device – Applicant’s specification para. 0059) ¶¶ 0008-0011 [chat…virtual agent…chat server…chatting…user and a virtual agent…receiving, at the chat server, a first message for a chat from a client device of an end user (request); with 0025 [input element…user interface module…launched by the client device], 0039 [virtual agent conversational…chat dialog], 0048, 0054-0059 [transmits a request…user/client device…chat initiation…chat initiation response message is transmitted back to the client device to indicate a beginning of the chat…application may cause a chat user interface module to be presented to the end user, which allows for the chat to proceed]])).
As per claim 29, Palakovich discloses the method of claim 27, wherein the request data includes data collected and pre-processed locally at an edge device (figs. 1-2 [shows data collected in deice and processed locally (data is processed to begin chat sessions and during session (if any changes or another agent is needed) – pre-processed)]; ¶¶ 0011 [updating a chat log based upon the first message, and sending the first message to the virtual agent (processing request); with 0025-0027 [receipt of the chat initialization message…selecting…based on topic…virtual agent module…messages received…API…updates], 0054-0055).
As per claim 30, Palakovich discloses the method of claim 27, further comprising: providing, using the virtual agent, a service recommendation based on the intent (¶¶ 0006 [guided assistance], 0055-0056 [chat initiation message may include information that identifies the end user, identifies the webpage or module causing the chat initiation message to be transmitted (e.g., a URL or identifier of a webpage), identifies a category/product/etc.’ with 0033 [discussing determining intent] and 0076 [discussing intent of user question]]).
As per claim 31, Palakovich discloses the method of claim 27, wherein redirecting to the different agent comprises: redirecting to the different agent based on the virtual agent determining that the intent has changed (see citations above for claims 27 and 30 and see with ¶¶ 0011 [first message (intent)…receiving…second message (changed intent)…updating chat log…determine…chat is…escalated…(move chat to different agent); also see with 0029-0031 [discussing changes of intent and initiates escalation or de-escalation which redirects/reassigns agents)]]).
As per claim 32, Palakovich discloses the method of claim 27, wherein redirecting to the different agent comprises: redirecting to the different agent based on the virtual agent determining that the dialog with the virtual agent is unsatisfactory (see citations above for claim 27 and 31 and see with ¶¶ 0027 [indicator of an escalation of a chat from a virtual agent to a live agent (live agent is different agent from virtual agent); with 0035 [escalation when virtual agent is slow…chant event… the virtual agent has not responded in a particular period of time or cannot provide an answer (dialog is unsatisfactory)]]; also 0043 [ through use of the virtual agent proxy module, one or more different virtual agents may seamlessly be used in a same chat system…chats may even seamlessly be shifted from one type of virtual agent to another type of virtual agent]).
As per claim 33, Palakovich discloses the method of claim 27, wherein the different agent is a different virtual agent (¶¶ 0043 [through use of the virtual agent proxy module, one or more different virtual agents may seamlessly be used in a same chat system…chats may even seamlessly be shifted from one type of virtual agent to another type of virtual agent]).
As per claim 40, claim 40 discloses substantially similar limitations as claim 33 above; and therefore claim 40 is rejected under the same rationale and reasoning as presented above for claim 33.
As per claim 34, Palakovich discloses the method of claim 27, wherein the virtual agent is configured to digitally communicate with the one or more third-party service suppliers using one or more Application Programming Interface (APIs) (see citations for claim 27 above and see with ¶¶ 0025-0027 [merchant…receipt of the chat initialization message…virtual agent module…virtual agent API]).
As per claim 35, Palakovich discloses the method of claim 27, wherein processing the request data comprises: processing the request data to extract request data points that include information identifying the type of service (see citations above for claims 27-29 and see ¶¶ 0025-0027 [receipt of the chat initialization message…selecting…based on topic…virtual agent module…messages received…API…updates], 0056 [mapping chats to chat queues based upon…[information and] data element explicitly provided by the end user when initiating the chat (e.g., a value selected/provided by the end user indicating a topic for the chat)], 0055-0056 [chat…include information…identifies…category…chat queue…virtual agent queues…associated with…product, category, etc., (type)]).
As per claim 36, Palakovich discloses the method of claim 35, further comprising: generating queries based on the request data points; and communicating the queries to the one or more third-party service suppliers (¶¶ 0004-0006 [questions (queries) and answers…virtual agent…guide…find information…answer questions (queries)], 0005 [user/customer/etc., questions/queries where the agent belongs to a service provider/merchant as shown in 0002 and 0025 [where user/customer/etc., initiates chat with queries on topics/subjects/categories regarding merchant product/services/etc.,)]], 0034-0035 [number of user questions; merchant site and merchant to answer questions/queries (via chat – virtual assistant); see with 0045-0048]; also see 0058, 0060).
As per claim 37, Palakovich discloses the method of claim 27, further comprising: communicating, based on processing the request data, queries to the one or more third- party service suppliers; and receiving, based on communicating the queries, information from the one or more third- party service suppliers (¶¶ 0004-0006 [questions (queries) and answers…virtual agent…guide…find information…answer questions (queries)], 0005 [user/customer/etc., questions/queries where the agent belongs to a service provider/merchant as shown in 0002 and 0025 [where user/customer/etc., initiates chat with queries on topics/subjects/categories regarding merchant product/services/etc.,)]], 0034-0035 [number of user questions; merchant site and merchant to answer questions/queries (via chat – virtual assistant); see with 0045-0048]).
Claim Rejections - 35 USC § 103
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 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 21-26, 38 are rejected under 35 U.S.C. 103 as being unpatentable over Palakovich et al., (US 2016/0099892) in view of Nomula et al., (US 2017/0148073).
As per claim 21, Palakovich discloses a system for reducing processing resources utilized, the system comprising: memory; and one or more processors configured to cause the system to:
determine to process a request using a virtual agent that is and that is configured to digitally communicate with third-party service suppliers using one or more Application Programming Interface (APIs) (¶¶ 0008-0011 [chat…virtual agent…chat server…chatting…user and a virtual agent…receiving, at the chat server, a first message for a chat from a client device of an end user (request); with 0031 [chat server…virtual agent…messages received…user…merchant…using the chat service], 0039 [virtual agent conversational…chat dialog], 0054 [transmits a request; with 0093]], 0025-0027 [receipt of the chat initialization message…virtual agent module…virtual agent API]);
process, based on determining to process the request using the virtual agent, request data, related to the request, using an auto extractor to extract a type of service (¶¶ 0011 [updating a chat log based upon the first message, and sending the first message to the virtual agent (processing request); with 0025-0027 [receipt of the chat initialization message…selecting…based on topic…virtual agent module…messages received…API…updates]);
route, based on the virtual agent corresponding to the type of service, the request to the virtual agent (¶¶ 0011 [chat…including…virtual agent…sending first/initial message/request (see above 0025-0027 discussion) to the virtual agent]); and
redirect, based on the virtual agent determining that an intent has changed or that a dialog with the virtual agent is unsatisfactory, to a different agent that is different from the virtual agent (¶¶ 0027 [indicator of an escalation of a chat from a virtual agent to a live agent (live agent is different agent from virtual agent); with 0035 [escalation when virtual agent is slow…chant event… the virtual agent has not responded in a particular period of time or cannot provide an answer (dialog is unsatisfactory)]]; also 0043 [ through use of the virtual agent proxy module, one or more different virtual agents may seamlessly be used in a same chat system…chats may even seamlessly be shifted from one type of virtual agent to another type of virtual agent]).
However, Palakovich does not explicitly state applying machine learning; and associated with a training using at least one of a deep neural network, a convolutional neural network (CNN), or recurrent neural network (RNN).
Analogous art Nomula discloses:
applying machine learning (¶¶ 0032 [using…machine learning], 0038 [using one or more techniques such as predictive, machine learning or deep learning techniques]); and
associated with a training using at least one of a deep neural network, a convolutional neural network (CNN), or recurrent neural network (RNN) (¶¶ 0038, 0048 [model trained…using a Recurrent Neural Network], 0055-0056 [virtual agent…training…Recurrent Neural Network]).
Therefore, it would be obvious to one of ordinary skill in the art to include in the system/method of Palakovich applying machine learning; and associated with a training using at least one of a deep neural network, a convolutional neural network (CNN), or recurrent neural network (RNN) as taught by analogous art Nomula in order to optimally and accurately provide services based on holistic information and optimal predictions and forecasting regarding the products/services (well-known concept) since doing so could be performed readily by any person of ordinary skill in the art, with neither undue experimentation, nor risk of unexpected results (KSR-G/TSM); and also since one of ordinary skill in the art at the time of the invention would have recognized that applying the known technique and concepts of Nomula (where “applying machine learning; and associated with a training using at least one of a deep neural network, a convolutional neural network (CNN), or recurrent neural network (RNN)” are old and well-known concepts and technology applied in software and services industry and in service industry with virtual agents/bots) would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such concepts and features into similar systems (KSR-D). (See (1) 2007 Examination Guidelines for Determining Obviousness Under 35 U.S.C. 103 in View of the Supreme Court Decision in KSR International Co. v. Teleflex Inc. - Federal Register, Vol. 72, No. 195, October 10, 2007, pages 57526-57535; (2) 2010 Examination Guidelines Updated Developments in the Obviousness Inquiry After KSR v. Teleflex. -Federal Register, Vol. 75, No. 169, September 01, 2010, pages 53643-53660; and (3) materials posted at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidelines-training-materials-view-ksr).
As per claim 22, Palakovich discloses the system of claim 21, wherein the one or more processors are further configured to cause the system to: receive, from an edge device, the request data collected at the edge device ((note that edge device is a user device – Applicant’s specification para. 0059) ¶¶ 0008-0011 [chat…virtual agent…chat server…chatting…user and a virtual agent…receiving, at the chat server, a first message for a chat from a client device of an end user (request); with 0025 [input element…user interface module…launched by the client device], 0039 [virtual agent conversational…chat dialog], 0048, 0054-0059 [transmits a request…user/client device…chat initiation…chat initiation response message is transmitted back to the client device to indicate a beginning of the chat…application may cause a chat user interface module to be presented to the end user, which allows for the chat to proceed]])).
As per claim 23, Palakovich discloses the system of claim 21, wherein the request data includes data collected and pre-processed locally at an edge device (figs. 1-2 [shows data collected in deice and processed locally (data is processed to begin chat sessions and during session (if any changes or another agent is needed) – pre-processed)]; ¶¶ 0011 [updating a chat log based upon the first message, and sending the first message to the virtual agent (processing request); with 0025-0027 [receipt of the chat initialization message…selecting…based on topic…virtual agent module…messages received…API…updates], 0054-0055).
As per claim 24, Palakovich discloses the system of claim 21, wherein the one or more processors are further configured to cause the system to: provide, using the virtual agent, a service recommendation based on the intent (¶¶ 0006 [guided assistance], 0055-0056 [chat initiation message may include information that identifies the end user, identifies the webpage or module causing the chat initiation message to be transmitted (e.g., a URL or identifier of a webpage), identifies a category/product/etc.’ with 0033 [discussing determining intent] and 0076 [discussing intent of user question]]).
As per claim 25, Palakovich discloses the system of claim 21, wherein, to redirect to the different agent, the one or more processors are further configured to cause the system to: redirect to the different agent based on the virtual agent determining that the intent has changed (see citations above for claims 27 and 30 and see with ¶¶ 0011 [first message (intent)…receiving…second message (changed intent)…updating chat log…determine…chat is…escalated…(move chat to different agent); also see with 0029-0031 [discussing changes of intent and initiates escalation or de-escalation which redirects/reassigns agents)]]).
As per claim 26, Palakovich discloses the system of claim 21, wherein the different agent is a different virtual agent (¶¶ 0043 [through use of the virtual agent proxy module, one or more different virtual agents may seamlessly be used in a same chat system…chats may even seamlessly be shifted from one type of virtual agent to another type of virtual agent]).
As per claim 38, Palakovich discloses the method of claim 37, and discloses answering queries and helping users (see citations above for claims 27-30). However, Palakovich does not explicitly state generating one or more recommendations or one or more proposals based on the information.
Analogous art Nomula discloses generating one or more recommendations or one or more proposals based on the information (¶¶ 0019 [The virtual agent 100 processes the input from the customer, considers different scenarios and presents suggestions; see with 0066 and 0072 [ for example: virtual agent 100 on the website or software application…the virtual agent 100 may determine that the user may be unhappy…the virtual agent 100 may suggest or carry out one or more actions to reduce the unhappiness of the user…suggestions…based on some parameters…in case the user is unhappy with a displayed item, the virtual agent 100 may suggest different sizes, prices or brands related to that item on the website…the virtual agent 100 may suggest alternatives for one or more factors such as price, shape, size, color, brand or manufacturer, among other suggestions]], 0090 [discusses virtual agent receiving various information and using that information to suggest items/products; with 0108 [takes into consideration the preferences of users and generates suggestions…helps in suggestion and selection of products on a website]]).
Therefore, it would be obvious to one of ordinary skill in the art to include in the system/method of Palakovich generating one or more recommendations or one or more proposals based on the information as taught by analogous art Nomula in order for businesses/organization to become more efficient and provide optimal help/services and/or products to user/customers (keep customer happy/etc.,) based on holistic information and optimal analysis regarding the products/services (well-known concept) since doing so could be performed readily by any person of ordinary skill in the art, with neither undue experimentation, nor risk of unexpected results (KSR-G/TSM); and also since one of ordinary skill in the art at the time of the invention would have recognized that applying the known technique and concepts of Nomula (agents of businesses/organizations/entities making recommendations/suggestions to users based on received information and user quires is an old and well-known concepts in product/retail and services industries using agents (including virtual agents/bots)) would have yielded predictable results because the level of ordinary skill in the art demonstrated by the references applied shows the ability to incorporate such concepts and features into similar systems (KSR-D). (See (1) 2007 Examination Guidelines for Determining Obviousness Under 35 U.S.C. 103 in View of the Supreme Court Decision in KSR International Co. v. Teleflex Inc. - Federal Register, Vol. 72, No. 195, October 10, 2007, pages 57526-57535; (2) 2010 Examination Guidelines Updated Developments in the Obviousness Inquiry After KSR v. Teleflex. -Federal Register, Vol. 75, No. 169, September 01, 2010, pages 53643-53660; and (3) materials posted at https://www.uspto.gov/patent/laws-and-regulations/examination-policy/examination-guidelines-training-materials-view-ksr).
Conclusion
The prior art made of record on the PTO-892 and not relied upon is considered pertinent to applicant's disclosure. For example, some of the pertinent art is listed below:
Konig et al., (US 2021/0203784): Related to routing incoming interactions of contact centers. The method may include: receiving initial data identifying a first incoming interaction that includes information disclosing at least an intent of the first incoming interaction; and performing a first subprocess to generate a personalized routing profile tailored to facilitate routing the first incoming interaction in accordance with preferences of a first customer. The first subprocess may include: accessing data from a database, the database including at least a first customer profile storing data relating to the first customer; based on the accessed data and the intent of the first incoming interaction, determining preferred agent characteristics data of the first customer for the first incoming interaction; and generating the personalized routing profile so to include the preferred agent characteristics data of the first customer. Further discusses that different chatbots may be configured, in conjunction with the chat server, to learn and evolve their behavior and responses according to input by the customers. For example, in response to customers reacting negatively to certain words, phrases, or responses, the chatbots may learn to use different words, phrases, or responses. Such learning may be supervised in order to prevent undesired evolution of the personalities or profiles of the chatbots. For example, changes to the personalities or profiles of the chatbots may be first approved or validated by human supervisors, certain keywords or phrases may be identified or flagged, and customer feedback may be analyzed. According to an embodiment, different chatbots may be configured to learn from each other, in addition to learning based on customer feedback or agent feedback. For example, different chatbots may be configured to communicate and exchange data with each other. In exemplary embodiments, the different chatbots may operate as a neural network for deep learning and self-learning capabilities, by exchanging data with one another.
Negi et al., (US 2020/0327444): Discusses customer journey event representation learning and outcome prediction using neural sequence models. A plurality of events are input into a module where each event has a schema comprising characteristics of the events and their modalities (web clicks, calls, emails, chats, etc.). The events of different modalities can be captured using different schemas and therefore embodiments described herein are schema-agnostic. Each event is represented as a vector of some number of numbers by the module with a plurality of vectors being generated in total for each customer visit. The vectors are then used in sequence learning to predict real-time next best actions or outcome probabilities in a customer journey using machine learning algorithms such as recurrent neural networks.
Kannan et al., (US 2013/0282430): Discusses improvement of customer experiences during online commerce. Generates models that predict trends, patterns, and exceptions in data through statistical analysis. In one embodiment, the predictive engine may use a naive Bayes algorithm to predict behavior. For example, a naive Bayes algorithm is used by the predictive engine to predict the most common problems associated with a family in Arizona using mobile devices made by Company A. FIG. 1 is a flow chart that illustrates the steps for predicting behavior according to one embodiment of the invention. In FIG. 1, the steps performed by the predictive engine 130 generate a model that predicts behavior and/or problems. Contributing variables are calculated according to whether the variable is a numerical or a categorical prediction. Contributing variables for numbers are calculated using regression analysis algorithms, e.g. least squares, linear regression, a linear probability model, nonlinear regression, Bayesian linear regression, nonparametric regression, etc. Categorical predictions use different methods, for example a Naive Bayes algorithm or other machine learning and artificial intelligence techniques, such as support vector machines, artificial neural networks, and agent based models. Simplifies the customer's experience by driving the system towards an intuitive customer experience in a dynamic manner, e.g. through real-time analysis it incorporates a modeling engine which provides models to target the right visitors at the right time by offering intervention strategies in the form of personalized recommendations.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to GURKANWALJIT SINGH whose telephone number is (571)270-5392. The examiner can normally be reached on M-F 8:30-5:30.
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/Gurkanwaljit Singh/
Primary Examiner, Art Unit 3683