DETAILED ACTION
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 .
This action is in response to Amendment filed 11/18/2025.
Claims 2-3 and 9-10 have been amended, and claim 1 was previously canceled. Currently, claims 2-15 are pending.
Priority
This application is a continuation of U.S. Patent Application No. 17/741,895 filed 05/11/2022, which is a continuation of U.S. Patent Application No. 16/203,574 filed 11/28/2018, which is a continuation in part of U.S. Patent Application No. 14/600,739 filed 01/20/2015, which claims priority from U.S. Provisional Application No. 61/928,780 filed 01/17/2014; and U.S. Patent Application No. 16/203,574 claims priority from U.S. Provisional Application No. 62/591,532 filed 11/28/2017. The provisional application 61/928,780 does not provide sufficient support for the claimed invention of this application as currently amended (e.g., it does not disclose at least limitation “a hierarchical structure” and/or “wherein the one or more data inputs are stored in a hierarchical structure comprising an ordered sequence”). All the parent applications including application 14/600,739 provide sufficient support for the claimed invention of this application. Therefore, the earliest effective filing date of the claimed invention of this application is 01/20/2015.
Response to Amendment
Amendment to paragraph [0001] of the Specification filed 11/18/2025 has been accepted and entered. Therefore, the objection to paragraph [0001] of the Specification has been withdrawn.
Amendments to independent claims 2 and 9 including removing the term “a value-congruency model” are effective to overcome the objection to Specification for not providing proper antecedent basis for the claimed subjection matter. As a result, the previous objection to the Specification for not providing proper antecedent basis for the claimed subjection matter has been withdrawn.
Amendments to claims are not effective to overcome the double patenting rejection. Therefore, the double patenting rejection with respect to U.S. Patent No. 10,311,095 is maintained.
Response to Arguments
Applicant's arguments filed 11/18/2025 have been fully considered but they are not persuasive.
Regarding Applicant’s arguments (see Remarks, pages 8-9) with respect to Claim Rejections under 35 U.S.C. § 101 that the parent application was not rejected under § 101 during prosecution and a double patenting rejection suggesting the present application “are not patentably distinct” from those of the parent application, the 101 rejection is improper and misplaced, Examiner respectfully disagrees.
It should be noted that even the present application is claimed as a continuation of application 17/741,895, it recites a different invention. Also, this present invention is rejected under double patenting rejection with respect to Patent No. 10,311,095 (of parent application 14/600,739) and its claimed invention is broader and does not clearly recited the practical application of the invention as the earlier patent. As such, the claimed invention of this present application is directed to abstract idea without significantly more.
In addition, the step of transmitting a request though a network and step of receiving one or more input data from a user though the network between two systems as broadly recited are mere data gathering and/or data transmitting recited at high level of generality, as such being insignificant extra solution activity (see MPEP 2106.05(g)) or well-understood, routine, conventional activity (see MPEP 2106(d)(II)). Thus, these elements are not mental steps but directed to insignificant extra-solution activity for implementing or applying other mental steps or abstract idea recited in claims. Also the combination of steps does not integrate the abstract idea into any practical application or any specific technology solution or improvement.
Regarding Applicant’s arguments (see Remarks, pages 11-12) with respect to prior art rejection in view of amended limitations, Examiner will address amended limitations in view of new ground(s) of rejection in view of Hawthorne et al. and Barbieri et al. (U.S. Publication No. 2013/0124310, Publication date 05/16/2013)
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 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 2-15 are rejected on the ground of nonstatutory double patenting as being unpatentable over claims 6 and 14 of U.S. Patent No. 10,311,095. Although the claims at issue are not identical, they are not patentably distinct from each other because claims 6 and 14 of the earlier application teach and suggest all limitations of claims 2-15 of this application.
In particular, the mapping of the rejection is as follows:
Instant Application
Patent No. 10,311,095
2. A method, comprising:
Claim 6 including limitation of claim 1, claim 5 and claim 6: A method, comprising:
transmitting over a network, by one or more processors coupled to memory in an application programming interface server, a request to a graphical user interface that is displayed on a client device;
initiating, by one or more computing devices (i.e., server) , a user experience assessment with a user computer (i.e., client device) via a communications network, wherein the user experience assessment comprises one or more predetermined content consuming experience; (wherein the initiated user experience assessment is interpreted as a request)
receiving, via input to the graphical user interface on the client device and through the network to the application programming interface server, one or more data inputs comprising a behavior or emotion of a user in reaction to previously viewed or purchased content;
receiving, by the one or more computing devices, positive appraisal sensation data (i.e., data inputs) from the user computer, wherein the positive appraisal data comprises user responses associated with the one or more predetermined content consuming experience;
analyzing, via one or more models, the received one or more data inputs as positive appraisal data wherein the one or more models identify classification of positive appraisal categories;
using, by the one or more computing devices, one or more analysis algorithms (i.e., models) in order to analyze the positive appraisal sensation data;
determining, by the one or more computing devices, one or more positive appraisal categories corresponding to the positive appraisal sensation data, wherein the one or more positive appraisal categories are determined based on the analysis;
storing, using a data model, the positive appraisal data, in a database by organizing the one or more data inputs in one or more data objects, wherein the one or more data inputs are stored in a hierarchical structure comprising an ordered sequence; and
ranking, by the one or more computing devices, each of the one or more positive appraisal categories (i.e., data objects) based on a predetermined frequency for each of the one or more positive appraisal categories, wherein the one or more positive appraisal categories are arranged in a sequential order based on the ranking; (the relationship between positive appraisal data sensation data (i.e., data inputs) and positive appraisal categories represents a hierarchical structure as recited)
generating, by the one or more processors, a context specific recommendation profile; and
generating, by the one or more computing devices, a recommendation profile (i.e., database), wherein the recommendation profile comprises the one or more positive appraisal categories each associated with the ranking (i.e., ordered sequence);
performing, by the one or more processors, comparisons between the context specific recommendation profile and previously stored content to determine congruency of the positive appraisal data by identifying a positive appraisal category included in a recommendation profile provided to the user that matches a category of previously stored content, wherein the previously stored content comprises content that is previously coded with one or more categories.
determining, by the one or more computing devices, value-congruency between the recommendation profile and coded content based on at least a predetermined number of matches between the recommendation profile and the coded content or at least a predetermined fraction or threshold indicative of a required level of similarity between the recommendation profile and the coded content, wherein the coded content is based at least upon information retrieved from scanned text;
wherein the coded content is associated with one or more predetermined content categories (see Claim 5) AND
wherein determining the value-congruency comprise identifying one or more positive appraisal categories that correspond to the one or more predetermined content categories (see Claim 6)
generating, by the one or more computing devices, content recommendation information based on the determined value-congruency; and
transmitting, by the one or more computing devices, an electronic message to the user via the communications network, wherein the electronic message comprises the content recommendation information.
Similarly,
Claims 3-8 rejected by Claim 6
Claims 9-15 rejected by Claim 14
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 2-15 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Regarding independent claim 2, the claim recites “generating, by the one or more processors, a context specific recommendation profile” in lines 14-15. However, it is unclear on how the context specific recommendation profile is generated and/or how it related to previous steps. The claim also recited using a data model to store data inputs in a hierarchical structure, but it is unclear how these data inputs are used for any purpose/benefit in the recited invention. The claim recites limitation “a context specific recommendation profile” in line 15 and limitation “a recommendation profile” in line 18, which raise question of whether they are the same and/or how they are related. Finally, the recited “performing, by the one or more processors, comparison between the context specific recommendation profile and previously stored content to determine congruency of the positive appraisal data by identifying a positive appraisal category included in a recommendation profile provided to a user that match a category of previously stored content” appears to be unclear (e.g., how “the context specific recommendation profile” and “the recommendation profile provided to the user” are related (?), what is “congruency of the positive appraisal data” (?)). In short, the claimed invention is unclear on how it processes data and how processed data are used for any practical application or enhancement in the system.
Regarding independent claim 9, the claim recites “generate a context specific recommendation profile” in line 15. However, it is unclear on how the context specific recommendation profile is generated and/or how it related to previous steps. The claim also recited using a data model to store data inputs in a hierarchical structure, but it is unclear how these data inputs are used for any purpose/benefit in the recited invention. The claim recites limitation “a context specific recommendation profile” in line 15 and limitation “a recommendation profile” in line 18, which raise question of whether they are the same and/or how they are related. Finally, the claimed invention recites “perform comparison between the context specific recommendation profile and previously stored content to determine congruency by identifying a positive category included in a recommendation profile provided to a user that matches a category of previously stored content” appears to be unclear (e.g., how “the context specific recommendation profile” and “the recommendation profile provided to the user” are related (?), and why it is needed to determine “congruency” (?)). In short, the claimed invention is unclear on how it processes data and how processed data are used for any practical application or enhancement in the system.
Other dependent claims are rejected as incorporating and failing to resolve the deficiencies of the rejected independent claims 2 and 9 upon which they depend correspondingly.
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 2-15 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea of analyzing data without significantly more.
The claims recite an abstract idea of analyzing data based on broadly recited steps of analyzing and determining, which are broadly recited steps/concepts that can be performed in the human mind and/or with the aid of pencil and paper and directed to mental processes grouping of abstract ideas. This judicial exception is not integrated into a practical application because other additional elements including genetic computer components and common computer functionality (e.g., accessing, storing, displaying, etc.) and/or insignificant extra-solution activity (e.g., mere data gathering and transmitting) for implementing the abstract idea are not sufficient to integrate the abstract idea into a practical application. The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because additional elements include only generic/common computer components (e.g., memory, processor, program instructions, etc.) and generic/common computer functions (e.g., accessing, storing, displaying, etc.) and/or insignificant extra-solution activity (e.g., mere data gathering and transmitting), which are not sufficient to amount to significantly more than the recited abstract idea.
Abstract idea analysis as follows:
Step 1:
According to the first part of the analysis, in the instant claims, claims 2-8 recite a method, which is directed to a process (i.e., a statutory category of invention). Claims 9-15 reciting a system including an application programming interface server (i.e., can be software) are directed to software per se, which is not directed to any statutory categories of invention (e.g., process, machine, manufacture, or composition of matter).
Step 2a Prong 1 (claims 2 and 9):
The following limitations recited in claims 2 and 9 are abstract ideas that fall under mental processes:
analyzing, via one or more models, the received one or more data inputs as positive appraisal data, wherein the one or more models identify classification of positive appraisal categories (the step of analyzing as broadly recited can be mentally performed in the human mind and/or with the aid of pencil and paper, through observation, evaluation, judgment and opinion (e.g., observing and classifying data based on models of categories),
generating, by the one or more processor, a context specific recommendation profile (this step of generating as broadly recited can be mentally performed in the human mind or with the aid of pencil and paper, wherein “the one or more processor” are directed to generic computer or computer components for implementing or applying the mental step or abstract idea),
performing, by the one or more processor, comparisons between the context specific recommendation profile and previously stored content to determine congruency of the positive appraisal data by identifying a positive appraisal category included in a recommendation profile provided to a user that matches a category of previously stored content, wherein the previously stored content comprises content that is previously coded with one or more categories (the step of performing comparisons to determine congruency as broadly recited can be mentally performed in the human mind or with the aid of pencil and paper, such as comparing data/category between user information and content information to determine congruency of positive appraisal data, wherein “the one or more processor” are directed to generic computer or computer components for implementing or applying the mental step or abstract idea).
All the limitations above are mental steps that can be performed in the human mind or with the aid of pencil and paper.
Step 2a Prong 2 (Claims 2 and 9):
The following limitations in claims 2 and 9 are additional elements:
transmitting over a network, by one or more processors coupled to memory in an application programming interface server, a request to a graphical user interface that is displayed on a client device (this step of transmitting over a network as broadly recited is directed to generic function of a computer network; other elements such as “a network”, “one or more processors”, “memory”, and “client device” are directed to generic computer components or generic computer for implementing or applying the abstract idea; and elements such as “application programing interface server” and “a graphical user interface” are directed to mere instructions to implement the insignificant extra-solution activity),
“receiving, via input to the graphical user interface on the client device and through the network to the application programming interface server, one or more data inputs comprising a behavior or emotion of a user in reaction to previously viewed or purchased content; (this step of receiving is directed to data gathering recited at high level of generality or insignificant extra-solution activity; and other elements such as “application programing interface server” and “a graphical user interface” are directed to mere instructions to implement insignificant extra-solution activity), and
“storing, using a data model, the positive appraisal data, in a database by organizing the one or more data inputs in one or more data objects, wherein the one or more data input are stored in a hierarchical structure comprising an ordered sequence” (the step of storing as broadly recited is directed to generic computer function).
These are a generic computer and/or generic computer components used to perform generic computer functions or insignificant extra-solution activity, such that they amount to no more than components used to execute mere instructions to apply the abstract idea. Accordingly, these additional elements do not integrate the abstract idea(s) into a practical application because they do not impose any meaningful limits on practicing the abstract idea(s).
Step 2b (Claims 2 and 9):
The following limitations in claims 2 and 9 are additional elements:
transmitting over a network, by one or more processors coupled to memory in an application programming interface server, a request to a graphical user interface that is displayed on a client device (this step of transmitting over a network as broadly recited is directed to generic function of a computer network; other elements such as “a network”, “one or more processors”, “memory”, and “client device” are directed to generic computer components or generic computer for implementing or applying the abstract idea; and elements such as “application programing interface server” and “a graphical user interface” are directed to mere instructions to implement the insignificant extra-solution activity or well-understood, routine, conventional activity),
“receiving, via input to the graphical user interface on the client device and through the network to the application programming interface server, one or more data inputs comprising a behavior or emotion of a user in reaction to previously viewed or purchased content; (this step of receiving is directed to data gathering recited at high level of generality or insignificant extra-solution activity; and other elements such as “application programing interface server” and “a graphical user interface” are directed to mere instructions to implement insignificant extra-solution activity or well-understood, routine, conventional activity), and
“storing, using a data model, the positive appraisal data, in a database by organizing the one or more data inputs in one or more data objects, wherein the one or more data input are stored in a hierarchy structure comprising an ordered sequence” (the step of storing as broadly recited is directed to generic computer function or well-understood, routine, conventional activity).
These are a generic computer and/or generic computer components used to perform generic computer functions or well-understood, routine, conventional activity, and do not amount to significantly more, see MPEP 2106.05(d)(II).
Regarding claims 3 and 10, claims 3 and 10 depend on claims 2 and 9 respectively. As such, claims 3 and 10 recite the abstract idea as presented in claims 2 and 9.
In addition, claims 3 and 10 include additional elements:
wherein determination of congruency requires one match (this element specifying the determination based on data, which is directed to mental process or mere data).
These are additional elements directed to mental processes (i.e., abstract idea) and/or mere data, which do not integrate the judicial exception into a practical application and do not amount to significantly more, see MPEP 2106.05(d)(II).
Regarding claims 4 and 11, claims 4 and 11 depend on claims 2 and 9 respectively. As such, claims 4 and 11 recite the abstract idea as presented in claims 2 and 9.
In addition, claims 4 and 11 include additional elements:
wherein determination of congruency requires a plurality of matches (this element specifying the determination based on data, which is directed to mental process or mere data).
These are additional elements directed to mental processes (i.e., abstract idea) and/or mere data, which do not integrate the judicial exception into a practical application and do not amount to significantly more, see MPEP 2106.05(d)(II).
Regarding claims 5 and 12, claims 5 and 12 depend on claims 2 and 9 respectively. As such, claims 5 and 12 recite the abstract idea as presented in claims 2 and 9.
In addition, claims 5 and 12 include additional elements:
wherein determination of congruency is text based (this element specifying the determination based on data, which is directed to mental process or mere data).
These are additional elements directed to mental processes (i.e., abstract idea) and/or mere data, which do not integrate the judicial exception into a practical application and do not amount to significantly more, see MPEP 2106.05(d)(II).
Regarding claims 6 and 13, claims 6 and 13 depend on claims 2 and 9 respectively. As such, claims 6 and 13 recite the abstract idea as presented in claims 2 and 9.
In addition, claims 6 and 13 include additional elements:
wherein the one or more data objects/inputs comprise positive appraisal category, positive appraisal experience and positive appraisal sensation (this element specifying the one or more data objects (see claim 6) and one or more data inputs (see claim 13), which are directed to data only).
These are additional elements directed to mere data, which do not integrate the judicial exception into a practical application and do not amount to significantly more, see MPEP 2106.05(d)(II).
Regarding claims 7 and 14, claims 7 and 14 depend on claims 2 and 9 respectively. As such, claims 7 and 14 recite the abstract idea as presented in claims 2 and 9.
In addition, claims 7 and 14 include additional elements:
wherein analyzing comprises ranking the positive appraisal categories (this step of ranking as broadly recited can be mentally performed in the human mind or with the aid of pencil and paper).
These are additional elements directed to mental process (i.e., abstract idea), which do not integrate the judicial exception into a practical application and do not amount to significantly more, see MPEP 2106.05(d)(II).
Regarding claims 8 and 15, claims 8 and 15 depend on claims 7 and 14 respectively. As such, claims 8 and 15 recite the abstract idea as presented in claims 7 and 14.
In addition, claims 8 and 15 include additional elements:
wherein the ranking is based on a number of occurrence of a positive appraisal category (this step of ranking as broadly recited can be mentally performed in the human mind or with the aid of pencil and paper).
These are additional elements directed to mental process (i.e., abstract idea), which do not integrate the judicial exception into a practical application and do not amount to significantly more, see MPEP 2106.05(d)(II).
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 (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 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 2-6 and 9-13 (effective filing date 01/20/2015) are rejected under 35 U.S.C. 103 as being unpatentable over Hawthorne et al. (U.S. Publication No. 2011/0016102, Publication date 01/20/2011), in view of Barbieri et al. (U.S. Publication No. 2013/0124310, Publication date 05/16/2013), and further in view of Hauser (U.S. Publication No. 2010/0250341, Publication date 09/30/2010).
As to claim 2, Hawthorne et al. teaches:
“A method” (see Hawthorne et al., Abstract and Fig. 1), comprising:
“transmitting over a network, by one or more processors coupled to memory in an application programming interface server, a request to a graphical user interface that is displayed on a client device” (see Hawthorne et al., Fig. 1, [0024] and [0052] for initiating, by the assessment engine (e.g., a server), one or more questions (i.e., transmitting a request) to the user (i.e., associated with a client/user device) via the user interaction engine (e.g., a server); for example, presenting/displaying a visual presentation of emotions (i.e., a graphical user interface), wherein an application programming interface server as broadly recited can be broadly interpreted as a server or any computer system in general);
“receiving, via input to the graphical user interface on the client device and through the network to the application programming interface server, one or more data inputs comprising a behavior or emotion of a user in reaction to previously viewed or purchased content” (see Hawthorne et al., [0052] for receiving selections/inputs from the user regarding user’s current emotional state; also see [0053] for receiving user report of his/her emotion or feeling regarding a certain image or different kinds of psychoactive content recommended to a user; also see [0055]);
“analyzing, via one or more models, the received one or more data inputs as positive appraisal data wherein the one or more models identify classification of positive appraisal categories” (see Hawthorne et al., [0053] for performing an emotional state and an emotional-state-specific content-feeling association assessment (i.e., analysis) of the user whenever psychoactive content is to be retrieved or presented to the user, wherein the assessment (i.e., the analysis) is based on inputs/responses (e.g., exciting feeling (i.e., positive appraisal data)) from the user; also see Fig. 10 and [0052] for a three-dimensional emotion circumplex for receiving user inputs, wherein the three-dimensional emotion circumplex as disclosed can be interpreted as a model for identifying classification of positive appraisal categories (e.g., optimism, joy, love, etc.) as recited; also see [0035] for categorizing facial expressions and/or depictions of behavior via a custom screen (i.e., a model) built using emotive icons (i.e., data objects));
“storing, using a data model, the positive appraisal data, in a database by organizing the one or more data inputs in one or more data objects” (see Hawthorne et al., [0055] for storing for each user a set of content-feeling associations and the associated emotional states and the time of assessment in the user library (i.e., database), wherein the data structure for storing a content-feeling association and/or association between a set of content-feeling associations with associated emotional states can be interpreted as a data model as recited, and each content-feeling association or emotional state can be interpreted as data objects as recited);
“generating, by the one or more processors, a context specific recommendation profile” (see Hawthorne et al., [0055] wherein a user library storing data (e.g., the content-feeling association) that can be used to recommend or retrieve content as disclosed (see [0054]) can be interpreted as a recommendation profile as recited);
“performing, by the one or more processors, comparisons between the context specific recommendation profile and previously stored content to determine congruency of the positive appraisal data by identifying a positive appraisal category included in a recommendation profile provided to a user that matches a category of previously stored content, wherein the previously stored content comprises content that is previously coded with one or more categories” (see Hawthorne et al., [0056] and [0061] for using user’s emotional state and content-feeling associations to determine the congruency/relevance between types/categories of content items and types/categories of feelings/reactions from a specific user, wherein a set of any information associated with a user (e.g., history of user’s feelings/reactions, the user’s emotional state, etc.) can be interpreted as a recommendation profile as recited, wherein the processing of using user data to identify contents as disclosed must be include a comparison between user data and content data).
In addition, Hawthorn et al. teaches storing data (e.g., user inputs) in database (see [0055]).
However, Hawthorn et al. does not explicitly teach a feature for storing data in a hierarchical structure as recited as following:
“wherein the one or more data inputs are stored in a hierarchical structure comprising an ordered sequence”.
On the other hand, Barbieri et al. explicitly teaches a feature for storing data in a hierarchical structure (see Barbieri et al., [0025] for storing the determined hierarchy of categories).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Barbieri et al.'s teaching to Hawthorne et al.’s system by implementing a feature for storing/managing data in a hierarchical structure. Ordinarily skilled artisan would have been motivated to do so to provide Hawthorne et al.’s system with an effective way to store/manage data. In addition, both of the references (Hawthorne et al. and Barbieri et al.) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, a system for generating user profiles and using user profiles to recommend content for users. This close relation between both of the references highly suggests an expectation of success.
In case that Hawthorne et al. does not explicitly teaches a feature of determining a congruency/match of the positive appraisal data between a user profile and a content items as equivalently recited as following:
“performing, by the one or more processors, comparisons between the context specific recommendation profile and previously stored content to determine congruency of the positive appraisal data by identifying a positive appraisal category included in a recommendation profile provided to a user that matches a category of previously stored content, wherein the previously stored content comprises content that is previously coded with one or more categories”.
On the other hand, Hauser explicitly teaches a feature of determining a congruency/match of the positive appraisal data between a user profile and a content items (see Hauser, [0021] for matching each user’s interests with topics, concepts and entities related to each content item, wherein each interest can be interpreted as positive appraisal data as recited).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Hauser's teaching to Hawthorne et al.’s system (as modified by Barbieri et al.) by implementing a feature for identifying a congruency/match between user interest(s) and topics/concepts/categories associated with content items. Ordinarily skilled artisan would have been motivated to do so to provide Hawthorne et al.’s system with an effective way to recommend content items based on user interest (i.e., positive appraisal data). In addition, both of the references (Hawthorne et al. and Hauser) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, a system for generating user profiles based on user interests and using user profiles to recommend content for users. This close relation between both of the references highly suggests an expectation of success.
As to claim 3, this claim is rejected based on the same arguments as above to reject claim 2 and is similarly rejected including the following:
Hawthorne et al. as modified by Barbieri et al. and Hauser teaches:
“wherein determination of congruency requires a one match” (see Hawthorne et al., [0057] for determining one or more contents (i.e., one or more matches) from content library that most likely meet the current emotional and psychological needs of the user, wherein the determination of content meeting/matching the current emotional and psychological needs of the user is interpreted as the determination of congruency as broadly recited).
As to claim 4, this claim is rejected based on the same arguments as above to reject claim 2 and is similarly rejected including the following:
Hawthorne et al. as modified by Barbieri et al. and Hauser teaches:
“wherein determination of congruency requires a plurality of matches” (see Hawthorne et al., [0057] for determining one or more contents (i.e., one or more matches) from content library that most likely meet the current emotional and psychological needs of the user, wherein the determination of content meeting/matching the current emotional and psychological needs of the user is interpreted as the determination of congruency as broadly recited).
As to claim 5, this claim is rejected based on the same arguments as above to reject claim 2 and is similarly rejected including the following:
Hawthorne et al. as modified by Barbieri et al. and Hauser teaches:
“wherein determination of congruency is text based” (see Hawthorne et al., [0057] for determining one or more contents (i.e., one or more matches) from content library that most likely meet the current emotional and psychological needs of the user, wherein the determination of content meeting/matching the current emotional and psychological needs of the user is interpreted as the determination of congruency as broadly recited; also see [0018] wherein content items can include text, therefore, the determining of content meeting/matching the current emotional and psychological needs of the user is text based).
As to claim 6, this claim is rejected based on the same arguments as above to reject claim 2 and is similarly rejected including the following:
Hawthorne et al. as modified by Barbieri et al. and Hauser teaches:
“wherein the one or more data objects comprise positive appraisal category, positive appraisal experience and positive appraisal sensation” (see Hawthorne et al., Fig. 10 and [0052] wherein area associated with a label in the three-dimensional emotion circumplex can be interpreted as a data object and each label can represent positive appraisal category (e.g., optimism, love, etc.), positive appraisal experience (e.g., serenity, interest, etc.), and/or positive appraisal sensation (e.g., joy, ecstasy, etc.); also see [0050]-[0051]).
As to claim 9, Hawthorne et al. teaches:
“A system” (see Hawthorne et al., Fig. 1 and Abstract), comprising:
“an application programming interface server configured to transmit, over a network, a request to a graphical user interface that is displayed on a client device” (see Hawthorne et al., Fig. 1, [0024] and [0052] for initiating, by the assessment engine (e.g., a server), one or more questions (i.e., transmitting a request) to the user (i.e., associated with a client/user device) via the user interaction engine (e.g., a server); for example, presenting/displaying a visual presentation of emotions (i.e., a graphical user interface), wherein an application programming interface server as broadly recited can be broadly interpreted as a server or any computer system in general) and further configured to
“receive, via input to the graphical user interface on the client device and through the network, one or more data inputs comprising a behavior or emotion of a user in reaction to previously viewed or purchased content” (see Hawthorne et al., [0052] for receiving selections/inputs from the user regarding user’s current emotional state; also see [0053] for receiving user report of his/her emotion or feeling regarding a certain image or different kinds of psychoactive content recommended to a user; also see [0055]);
“the application programming interface server further configured to analyze, via one or more models, the received one or more data inputs as positive appraisal data wherein the one or more models identify classification of positive appraisal categories” (see Hawthorne et al., [0053] for performing an emotional state and an emotional-state-specific content-feeling association assessment (i.e., analysis) of the user whenever psychoactive content is to be retrieved or presented to the user, wherein the assessment (i.e., the analysis) is based on inputs/responses (e.g., exciting feeling (i.e., positive appraisal data)) from the user; also see Fig. 10 and [0052] for a three-dimensional emotion circumplex for receiving user inputs, wherein the three-dimensional emotion circumplex as disclosed can be interpreted as a model for identifying classification of positive appraisal categories (e.g., optimism, joy, love, etc.) as recited; also see [0035] for categorizing facial expressions and/or depictions of behavior via a custom screen (i.e., a model) built using emotive icons (i.e., data objects));
“the application programming interface server further configured to store, using a data model, the positive appraisal data, in a database by organizing the one or more data inputs in one or more data objects” (see Hawthorne et al., [0055] for storing for each user a set of content-feeling associations and the associated emotional states and the time of assessment in the user library (i.e., database), wherein the data structure for storing a content-feeling association and/or association between a set of content-feeling associations with associated emotional states can be interpreted as a data model as recited, and each content-feeling association or emotional state can be interpreted as data objects as recited); and
“the application programming interface server further configured to generate a context specific recommendation profile” (see Hawthorne et al., [0055] wherein a user library storing data (e.g., the content-feeling association) that can be used to recommend or retrieve content as disclosed (see [0054]) can be interpreted as a recommendation profile as recited) and
“perform comparisons between the context specific recommendation profile and previously stored content to determine congruency by identifying a positive appraisal category included in a recommendation profile provided to a user that matches a category of previously stored content” (see Hawthorne et al., [0056] and [0061] for using user’s emotional state and content-feeling associations to determine the congruency/relevance between types/categories of content items and types/categories of feelings/reactions from a specific user, wherein a set of any information associated with a user (e.g., history of user’s feelings/reactions, the user’s emotional state, etc.) can be interpreted as a recommendation profile as recited, wherein the processing of using user data to identify contents as disclosed must be include a comparison between user data and content data).
In addition, Hawthorn et al. teaches storing data (e.g., user inputs) in database (see [0055]).
However, Hawthorn et al. does not explicitly teach a feature for storing data in a hierarchical structure as recited as following:
“wherein the one or more data inputs are stored in a hierarchical structure comprising an ordered sequence”.
On the other hand, Barbieri et al. explicitly teaches a feature for storing data in a hierarchical structure (see Barbieri et al., [0025] for storing the determined hierarchy of categories).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Barbieri et al.'s teaching to Hawthorne et al.’s system by implementing a feature for storing/managing data in a hierarchical structure. Ordinarily skilled artisan would have been motivated to do so to provide Hawthorne et al.’s system with an effective way to store/manage data. In addition, both of the references (Hawthorne et al. and Barbieri et al.) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, a system for generating user profiles and using user profiles to recommend content for users. This close relation between both of the references highly suggests an expectation of success.
In case that Hawthorne et al. does not explicitly teaches a feature of determining a congruency/match between a positive appraisal category in a user profile and a category in a content items as equivalently recited as following:
“perform comparisons between the context specific recommendation profile and previously stored content to determine congruency by identifying a positive appraisal category included in a recommendation profile provided to a user that matches a category of previously stored content”.
On the other hand, Hauser explicitly teaches a feature of determining a congruency/match between a positive appraisal category in a user profile and a category in a content items (see Hauser, [0021] for matching each user’s interests with topics, concepts and entities related to each content item, wherein each interest can be interpreted as positive appraisal category as recited).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Hauser's teaching to Hawthorne et al.’s system (as modified by Barbieri et al.) by implementing a feature for identifying a congruency/match between user interest(s) and topics/concepts/categories associated with content items. Ordinarily skilled artisan would have been motivated to do so to provide Hawthorne et al.’s system with an effective way to recommend content items based on user interest (i.e., positive appraisal data). In addition, both of the references (Hawthorne et al. and Hauser) teach features that are directed to analogous art and they are directed to the same field of endeavor, such as, a system for generating user profiles based on user interests and using user profiles to recommend content for users. This close relation between both of the references highly suggests an expectation of success.
As to claim 10, this claim is rejected based on the same arguments as above to reject claim 9 and is similarly rejected including the following:
Hawthorne et al. as modified by Barbieri et al. and Hauser teaches:
“wherein determination of congruency requires a one match” (see Hawthorne et al., [0057] for determining one or more contents (i.e., one or more matches) from content library that most likely meet the current emotional and psychological needs of the user, wherein the determination of content meeting/matching the current emotional and psychological needs of the user is interpreted as the determination of congruency as broadly recited).
As to claim 11, this claim is rejected based on the same arguments as above to reject claim 9 and is similarly rejected including the following:
Hawthorne et al. as modified by Barbieri et al. and Hauser teaches:
“wherein determination of congruency requires a plurality of matches” (see Hawthorne et al., [0057] for determining one or more contents (i.e., one or more matches) from content library that most likely meet the current emotional and psychological needs of the user, wherein the determination of content meeting/matching the current emotional and psychological needs of the user is interpreted as the determination of congruency as broadly recited).
As to claim 12, this claim is rejected based on the same arguments as above to reject claim 9 and is similarly rejected including the following:
Hawthorne et al. as modified by Barbieri et al. and Hauser teaches:
“wherein determination of congruency is text based” (see Hawthorne et al., [0057] for determining one or more contents (i.e., one or more matches) from content library that most likely meet the current emotional and psychological needs of the user, wherein the determination of content meeting/matching the current emotional and psychological needs of the user is interpreted as the determination of congruency as broadly recited; also see [0018] wherein content items can include text, therefore, the determining of content meeting/matching the current emotional and psychological needs of the user is text based).
As to claim 13, this claim is rejected based on the same arguments as above to reject claim 9 and is similarly rejected including the following:
Hawthorne et al. as modified by Barbieri et al. and Hauser teaches:
“wherein the one or more data inputs comprise positive appraisal category, positive appraisal experience and positive appraisal sensation” (see Hawthorne et al., Fig. 10 and [0052] wherein area associated with a label in the three-dimensional emotion circumplex can be interpreted as a data object (i.e., data inputs) and each label can represent positive appraisal category (e.g., optimism, love, etc.), positive appraisal experience (e.g., serenity, interest, etc.), and/or positive appraisal sensation (e.g., joy, ecstasy, etc.); also see [0050]-[0051]).
Claims 7-8 and 14-15 (effective filing date 01/17/2014) are rejected under 35 U.S.C. 103 as being unpatentable over Hawthorne et al. (U.S. Publication No. 2011/0016102, Publication date 01/20/2011), in view of Barbieri et al. (U.S. Publication No. 2013/0124310, Publication date 05/16/2013), in view of Hauser (U.S. Publication No. 2010/0250341, Publication date 09/30/2010)and further in view of Subramanian et al. (U.S. Publication No. 2007/0208569, Publication date 09/06/2007).
As to claims 7 and 14, Hawthorne et al. as modified by Barbieri et al. and Hauser teaches all limitations as recited in claims 2 and 9 respectively including emotional states/categories/labels (see Hawthorne et al., Fig. 10 and [0051])
However, Hawthorne et al. as modified by Barbieri et al. and Hauser does not explicitly teach a feature of ranking the emotional states/labels as recited as follows:
“wherein the analyzing comprises ranking the positive appraisal categories”.
On the other hand, Subramanian et al. explicitly teaches a feature of ranking the emotional states/labels (see Subramanian et al., [0094] for scoring/ranking emotional words/categories by usage/occurrence frequency).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to incorporate Hawthorne et al.'s teaching to Subramanian et al.’s by implementing a feature of ranking/scoring an emotional categories/labels based on usage/occurrence frequency. Ordinarily skilled artisan would have been motivated to do so to provide Hawthorne et al.’s system with an effective way to rank the emotional categories/labels. In addition, ranking a word/category based on occurrence frequency is well-known and well-used in the art in many different fields.
As to claims 8 and 15, these claims are rejected based on the same arguments as above to reject claims 7 and 14 respectively and are similarly rejected including the following:
Hawthorne et al. as modified by Barbieri et al., Hauser, and Subramanian et al. teaches:
“wherein the ranking is based on a number of occurrences of a positive appraisal category” (see Hawthorne et al., Fig. 10 and [0051] for arranging emotional categories/labels; also see Subramanian et al., [0094] for scoring/ranking emotional words/categories by usage/occurrence frequency (i.e., number of occurrences)).
Conclusion
Applicant's amendment necessitated the new ground(s) of rejection presented in this Office action. Accordingly, THIS ACTION IS MADE FINAL. See MPEP § 706.07(a). Applicant is reminded of the extension of time policy as set forth in 37 CFR 1.136(a).
A shortened statutory period for reply to this final action is set to expire THREE MONTHS from the mailing date of this action. In the event a first reply is filed within TWO MONTHS of the mailing date of this final action and the advisory action is not mailed until after the end of the THREE-MONTH shortened statutory period, then the shortened statutory period will expire on the date the advisory action is mailed, and any nonprovisional extension fee (37 CFR 1.17(a)) pursuant to 37 CFR 1.136(a) will be calculated from the mailing date of the advisory action. In no event, however, will the statutory period for reply expire later than SIX MONTHS from the mailing date of this final action.
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/Phuong Thao Cao/Primary Examiner, Art Unit 2164