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 .
The amendments were received on 3/17/2026. Claims 1-6, 8-15, and 17-20 are pending where claims 1-6, 8-15, and 17-20 were previously presented and claims 7 and 16 were cancelled.
Continued Examination Under 37 CFR 1.114
A request for continued examination under 37 CFR 1.114, including the fee set forth in 37 CFR 1.17(e), was filed in this application after final rejection. Since this application is eligible for continued examination under 37 CFR 1.114, and the fee set forth in 37 CFR 1.17(e) has been timely paid, the finality of the previous Office action has been withdrawn pursuant to 37 CFR 1.114. Applicant's submission filed on 3/17/2026 has been entered.
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 1-6, 8-15, and 17-20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to s without significantly more.
With respect to claim 1:
Step 2A, Prong One:
The claim recites the following limitations which are drawn towards an abstract idea:
A method comprising:
extracting,
generating,
transforming, by the application, the raw data for the digital content into executable data based on the generated user-entity interaction mapping, the transformation comprising applying a contextually relevant messaging format to the digital content, the executable data enabling a type of interaction with the digital content by a receiving application of a user (see paragraphs [0073] and [0078]; the transforming relates to the evaluating/aggregating of information to determine insights about the data/messages which relates to mental process steps associated with evaluating/analyzing data including determining or applying a different format to the data based on how the user decides is the best way to convey the information).
As seen from above, the identified limitations recite concepts associated with an abstract idea and thus the respective claim recites a judicial exception (see 2106.04(a)) and thus requires further analysis as discussed below.
Step 2A, Prong Two:
The following limitations have been identified as being additional elements as discussed below.
receiving, by an application, over a network digital content, the digital content being associated with raw data (recites insignificant extrasolution activity of receiving information over a network, see MPEP 2106.05(g));
“by an application” (recites usage of a computer program to perform the judicial exception which amounts to merely using the computer as a tool to perform the judicial exception, see MPEP 2106.05(f));
“by the application executing a first artificial intelligence (AI) model including a natural language processing (NLP) model” (recites usage of a computer program utilizing a machine-learning model to perform the judicial exception which amounts to merely using the computer as a tool to perform the judicial exception, see MPEP 2106.05(f));
“by the application executing a second AI model including a graph neural network” and “identified by the second AI model” (recites usage of a computer program utilizing a machine-learning model to perform the judicial exception which amounts to merely using the computer as a tool to perform the judicial exception, see MPEP 2106.05(f));
the user-entity interaction mapping indicating a context for which the digital content is to be communicated to an account of a user (recites field of use limitations describing meaning of attributes of data that is being considered/evaluated, see MPEP 2106.05(h));
and causing, by the application, over a network, execution of the type of action for the digital content (recites insignificant extrasolution activity of sorting information, see MPEP 2106.05(g)),
the executed type of interaction causing the digital content to be dynamically rendered by the receiving application based on the context and the applied message format (recites insignificant extrasolution activity of outputting/transmitting information over a network, see MPEP 2106.05(g)).
As seen from the above discussion, the identified limitations did not integrate the judicial exception into a practical application (see MPEP 2106.04(d)). This judicial exception is not integrated into a practical application because the additional elements recite usage of computer-related programs to use a computer as a tool to implement the abstract idea as well as insignificant extrasolution activity associated with sorting/organizing data as well as receiving and transmitting information.
Step 2B:
Below is the analysis of the claims:
receiving, by an application, over a network digital content, the digital content being associated with raw data (recites well-understood, routine, and conventional activity of receiving information over a network, see MPEP 2106.05(g));
“by an application” (recites usage of a computer program to perform the judicial exception which amounts to merely using the computer as a tool to perform the judicial exception, see MPEP 2106.05(f));
“by the application executing a first artificial intelligence (AI) model including a natural language processing (NLP) model” (recites usage of a computer program utilizing a machine-learning model to perform the judicial exception which amounts to merely using the computer as a tool to perform the judicial exception, see MPEP 2106.05(f));
“by the application executing a second AI model including a graph neural network” and “identified by the second AI model” (recites usage of a computer program utilizing a machine-learning model to perform the judicial exception which amounts to merely using the computer as a tool to perform the judicial exception, see MPEP 2106.05(f));
the user-entity interaction mapping indicating a context for which the digital content is to be communicated to an account of a user (recites field of use limitations describing meaning of attributes of data that is being considered/evaluated, see MPEP 2106.05(h));
and causing, by the application, over a network, execution of the type of action for the digital content (recites well-understood, routine, and conventional activity of sorting information, see MPEP 2106.05(d)),
the executed type of interaction causing the digital content to be dynamically rendered by the receiving application based on the context and the applied message format (recites well-understood, routine, and conventional activity of outputting/transmitting information over a network, see MPEP 2106.05(d)).
As seen from above, the respective claim elements taken individually do not amount to significantly more than the judicial exception. When taken as a whole (in combination), the claim also does not amount to significantly more than the abstract idea because the additional elements recite usage of computer-related programs to use a computer as a tool to implement the abstract idea as well as sorting/organizing data with high-level recitation of receiving and transmitting information too with no meaningful limitation beyond that of the abstract idea as discussed above.
With regard to claim 2, this claim recites the transformation involving a set of layers of the raw data, each layer corresponding to a portion of the digital content, such that the type of interaction is configured for each layer (recites field of use limitations describing attributes/dimensions of the data, see MPEP 2106.05(h)).
With regard to claim 3, this claim recites the parameters corresponding to a set of information selected from a group consisting of: topic, a communication pattern, transmitted data across a configurable time window, and engagement data (recites field of use limitations describing attributes/dimensions of the data, see MPEP 2106.05(h)).
With regard to claim 4, this claim recites the configurable time window being a set of rolling days for which the raw data can be retrieved from a database (recites field of use limitations describing attributes/dimensions of the data, see MPEP 2106.05(h)).
With regard to claim 5, this claim recites determining that a parameter of the digital content corresponds to a type of content (recites mental process step of making a determination/decision based on prior analysis/evaluation);
filtering the digital content (recites insignificant extrasolution activity of sorting information which amounts to well-understood, routine, and conventional activity of sorting information, see MPEP 2106.05(d));
and applying a tag corresponding to the type of content to the digital content (recites mental process steps of evaluating and making a decision such as a label for the content).
With regard to claim 6, this claim recites the user-entity interaction mapping being based on information selected from a group consisting of: message characteristics, content characteristics, user behaviors, and user characteristics (recites field of use limitations describing meaning of attributes of data that is being considered/evaluated, see MPEP 2106.05(h)).
With regard to claim 8, this claim recites communicating information related to a communication of the digital content to the account of the user (recites insignificant extrasolution activity of sending/transmitting information which amounts to well-understood, routine, and conventional activity of sending/transmitting information over a network, see MPEP 2106.05(d));
and training the second AI model based on the communicated information (recites merely using a computer to perform the abstract idea by training computer processes to perform desired actions, see MPEP 2106.05(f)).
With regard to claim 9, this claim recites associating the digital content with an electronic message (recites mental process steps of evaluating/determination to make mental associations that link different content together, e.g. associating Tom Cruise with Top Gun or Mission Impossible).
With regard to claims 10-15, 17, and 18, these claims are substantially similar to claims 1-6, 8, and 9 and are rejected for similar reasons as discussed above.
With regard to claims 19 and 20, these claims are substantially similar to claims 1 and 5 and are rejected for similar reasons as discussed above.
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.
This application currently names joint inventors. In considering patentability of the claims the examiner presumes that the subject matter of the various claims was commonly owned as of the effective filing date of the claimed invention(s) absent any evidence to the contrary. Applicant is advised of the obligation under 37 CFR 1.56 to point out the inventor and effective filing dates of each claim that was not commonly owned as of the effective filing date of the later invention in order for the examiner to consider the applicability of 35 U.S.C. 102(b)(2)(C) for any potential 35 U.S.C. 102(a)(2) prior art against the later invention.
Claims 1-3, 6, 8-12, 15, 17-19 are rejected under 35 U.S.C. 103 as being unpatentable over Vukich et al [US 11,082,387] in view of Bodigutla et al [US 2024/0378425 A1].
With regard to claim 1, Vukich teaches a method comprising: receiving, by an application over a network, digital content, the digital content being associated with raw data (see Figure 4 and col 18, lines 5-7 & 30-36; a message is received/identified and data of the digital intent is identified);
extracting, by the application executing a first artificial intelligence (AI) model including a natural language processing (NLP) model, from the digital content, features obtained via tokenization and semantic parsing and determining parameters associated with the digital content based on the extracted features (see col 13, lines 1-24; col 15, lines 28-30; the system can utilize a natural language recognition/processing model for extracting features including identifying words/tokenization and semantic analysis);
generating,
the user-entity interaction mapping indicating a context for which the digital content is to be communicated to an account of the user (see Vukich, col 13, line 60 through col 14, line 13; col 7, lines 13-51; see col 16, lines 21-32 & 60-66; the system can utilize some context information to determine a priority and ordering of the messages and how they are communicated/presented to the user).
transforming, by the application, the raw data for the digital content into executable data based on the generated user-entity interaction mapping, the transformation comprising applying a contextually relevant messaging format to the digital content, the executable data enabling a type of interaction with the digital content by a receiving application of a user (see col 15, line 54 through col 16, line 32; the system can transform the information associated with the content into actionable intelligence for further processing by the system);
and causing, by the application, over the network, execution of the type of interaction, the executed type of interaction causing the digital content to be dynamically rendered by the receiving application based on the context and the applied messaging format (see col 16, lines 10-48; see col 16, lines 21-32; the system can execute the type of action to provide distinction of the various messages/digital content from each other including an applied messaging format).
Vukich teaches usage of multiple models but does not appear to explicitly teach:
generating, by the application executing a second AI model including a graph neural network, based on connections between the determined parameters and user data that are identified by the second AI model, a user-entity interaction mapping;
Bodigutla teaches generating, by the application executing a second AI model including a graph neural network, based on connections between the determined parameters and user data that are identified by the second AI model, a user-entity interaction mapping (see paragraph [0068] to illustrate a first model; paragraph [0155] for the data system having machine learning model inputs and outputs; see paragraphs [0169]-[0174] to illustrate a graphing mechanism for generating the user-entity interaction graph/mapping; see paragraph [0195] to illustrate the teaching of a graph neural model).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the message analysis and prioritization system of Vukich by utilizing a machine learning algorithm to generate/update mappings between users and entities as taught by Bodigutla in order to be able to not only monitor data as it is observed/detected but also utilize automated means/tools to process the data and update relationships between users and entities in real-time thereby allowing the system to maintain accurate up-to-date as soon as possible while also providing means to determine or infer new relationships earlier thus allowing the system to utilize those inferences to better serve the user in other downstream processes.
With regard to claim 2, Vukich in view of Bodigutla teach the transformation involving a set of layers of the raw data, each layer corresponding to a portion of the digital content, such that the type of interaction is configured for each layer (see Vukich, col 15, lines 1-53; col 13, line 48 through col 14, line 16; the system can involve multiple layers of data that represent various dimensions of the content/message).
With regard to claim 3, Vukich in view of Bodigutla teach the parameters corresponding to a set of information selected from a group consisting of: topic, a communication pattern, transmitted data across a configurable time window, and engagement data (see Vukich, col 14, lines 38-67; various information can be gleamed from the parameters associated with the digital content).
With regard to claim 6, Vukich in view of Bodigutla teach the user-entity interaction mapping being based on information selected from a group consisting of: message characteristics, content characteristics, user behaviors, and user characteristics (see Vukich, col 14, lines 38-67; the mapping can be based on message characteristics/content characteristics as well as user behavior).
With regard to claim 8, Vukich in view of Bodigutla teach communicating information related to a communication of the digital content to the account of the user; and training the second AI model based on the communicated information (see Vukich, col 9, lines 3-8; and col 10, lines 31-61; see Bodigutla, paragraph [0180]; the system can monitor communications/interactions related to the digital content and be able to train the respective AI model(s) accordingly).
With regard to claim 9, Vukich in view of Bodigutla teach associating the digital content with an electronic message, such that the identification of the digital content comprises identifying the electronic message (see Vukich, col 13, lines 25-47; the system can associate or identify particular information with the message including the digital content or message boy type information).
With regards to claims 10-12, 15, 17, and 18, these claims are substantially similar to claims 1-3, 6, 8, and 9 respectively and are rejected for similar reasons as discussed above.
With regard to claim 19, this claim is substantially similar to claim 1 and is rejected for similar reasons as discussed above.
Claims 4, 5, 13, 14, and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Vukich et al [US 11,082,387] in view of Bodigutla et al [US 2024/0378425 A1] in further view of Azarbakht et al [US 2022/0215345 A1].
With regard to claim 4, Vukich in view of Bodigutla teach all the claim limitations of claims 1 and 3 as discussed above.
Vukich in view of Bodigutla do not appear to explicitly teach the configurable time window being a set of rolling days for which the raw data can be retrieved from a database.
Azarbakht teaches the configurable time window being a set of rolling days for which the raw data can be retrieved from a database (see paragraphs [0112] and [0113] and [0093]; the system can have a set of rolling days for which to evaluate data).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the data analysis/evaluation process of Vukich in view of Bodigutla by including means to evaluate a rolling window of days as taught by Azarbakht in order to reduce the amount of data that has to be considered when making determinations or associating relationships based on user interactions of messages thereby allowing the system to be able to minimize the loss of the model’s output while ensuring that the most recent interactions are weighted or have a greater influence on how the system/model will evaluate new messages thus allowing interactions from a long time ago to not unduly skew the model from being accurate with respect to recent user interactions/behavior.
With regard to claim 5, Vukich in view of Bodigutla teach all the claim limitations of claim 1 as discussed above.
Vukich in view of Bodigutla teach determining that a parameter of the digital content corresponds to a type of content (see Vukich, col 15, lines 63-65; the topic/subject of the message can be determined);
filtering the digital content (see Vukich, col 10, lines 5-10; the system can perform various functions including filtering based on parameters of the message/content).
Azarbakht teaches applying a tag corresponding to the type of content to the digital content (see paragraphs [0117], [0063]-[0065], and [0086]; the system can apply labels to the content/messages based on the type of content).
It would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to modify the data analysis/evaluation process of Vukich in view of Bodigutla by including means to apply a tag/label to the content/message as taught by Azarbakht in order to leverage the tasks already being performed by keeping track of particular determinations such as content type via a label/tag thus allowing other downstream products/services to be able to more efficiently interact and other processing on the content/message by being able to take into consideration the respective label/tag without having to spend processing time and resources with their own separate evaluation.
With regard to claims 13 and 14, these claims are substantially similar to claims 4 and 5 and are rejected for similar reasons as discussed above.
With regard to claim 20, this claim is substantially similar to claim 5 and is rejected for similar reasons as discussed above.
Response to Arguments
Applicant's arguments (see the last paragraph on page 7 through the second whole paragraph on page 11) have been fully considered but they are not persuasive. The applicant argues (a) that the claims do not recite a mental process but rather recite a specific computer-implemented pipeline to perform the claim limitations (see last paragraph on page 8); (b) the respective limitations cannot be performed in the human mind since they require machine execution of particular AI models, transformation of raw data into executable data for a receiving application, and dynamic rendering by that application over a network (see first whole paragraph on page 9); (c) even if claim 1 implicates an abstract idea, the amended claim integrates into a practical application via specific computer-implemented content communication and rendering pipeline since it controls how digital content is presented by a receiving application in the user’s account rather than merely classifying and organizing information (see second to last paragraph on page 9); (d) the specification expressly identifies the underlying technical problems of prior systems and teaches the disclosed framework to transform raw data in a manner to allow the interaction mapping to dictate how, when and/or where the user receives message/content in their account thus the claim reflects the technical improvement (see last paragraph on page 9); and (e) the amended claims recite significantly more than the alleged abstract idea since the recited elements individually and as an ordered combination are not well-understood, routine, and conventional in the field (see second to last paragraph on page 10 through the second paragraph on page 11). The Examiner respectfully disagrees.
With regard to argument (a) about not reciting a mental process but rather a specific computer-implemented pipeline to perform the claim limitations (see last paragraph on page 8), the Examiner notes that Step 2A, Prong One evaluation is to identify if a limitation exists that recites or is directed to an abstract idea. As illustrated in the 35 USC 101 rejections, the various limitations recite concepts at a high-level of generality that involve analysis/evaluating data for parameters to determine relationships/mappings for users. The respective additional elements are evaluated in Step 2A, Prong Two and are addressed below. Accordingly, applicant’s arguments are not persuasive.
With regard to argument (b) the respective limitations cannot be performed in the human mind since they require machine execution of particular AI models, transformation of raw data into executable data for a receiving application, and dynamic rendering by that application over a network (see first whole paragraph on page 9); the Examiner notes that the various limitations are recited at a high-level of generality where transformation of raw data into executable data can relate to altering or determining to alter the data in a manner that “most likely will be engaged with by the receiving user”, i.e. mental process evaluation and decision steps of how to present information such as targeted advertising/marketing (i.e. actionable targeting intelligence); as noted in applicant’s specification at paragraphs 73 and 78. Also, the Examiner notes that, according to MPEP 2106.04(a)(2)(III)(C), that claims can be directed to a mental process even if they are claimed as being performed on a computer. The mere usage of a computer, as noted above, does not render the claim patent eligible. In the instant case, high-level recitation of AI models do little except indicate that the abstract idea is being performed on a computer as noted in the 35 USC 101 rejections above. Therefore, applicant’s arguments are not persuasive.
With regard to argument (c) about the amended claim integrating into a practical application via specific computer-implemented content communication and rendering pipeline since it controls how digital content is presented by a receiving application in the user’s account rather than merely classifying and organizing information (see second to last paragraph on page 9); the applicant argues that the system controls how digital content is presented however, the claims merely indicate at a high-level of generality that the application that the content is ‘dynamically rendered’ based on the context and applied messaging format which amounts to transmitting information to a display device for displaying information. Although the claim recites based on the context and the applied messaging format, these limitations are recited at a high-level of generality and the broadest reasonable interpretation of rendering data based on context and format includes determining color coding of priority messages (such as urgent messages versus non-urgent) and sorting them (i.e. rendering based on context). The Examiner notes that, per MPEP 2106.05(a), that “[a]n important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome. McRO, 837 F.3d at 1314-15, 120 USPQ2d at 1102-03; DDR Holdings, 773 F.3d at 1259, 113 USPQ2d at 1107.” (emphasis added). As discussed above, the claim limitations recite a concept at a high-level of generality. Accordingly, applicant’s arguments are not persuasive.
With regard to argument (d) about the specification expressly identifies the underlying technical problems of prior systems and teaches the disclosed framework to transform raw data in a manner to allow the interaction mapping to dictate how, when and/or where the user receives message/content in their account thus the claim reflects the technical improvement (see last paragraph on page 9); as noted above, per MPEP 2106.05(a), that “[a]n important consideration in determining whether a claim improves technology is the extent to which the claim covers a particular solution to a problem or a particular way to achieve a desired outcome, as opposed to merely claiming the idea of a solution or outcome. McRO, 837 F.3d at 1314-15, 120 USPQ2d at 1102-03; DDR Holdings, 773 F.3d at 1259, 113 USPQ2d at 1107.” (emphasis added). Although the specification may describe some problem and potential solution, the claims also have to reflect that where, currently, the claims recite some of the concepts at a high-level of generality and thus the respective arguments are not persuasive.
With regard to argument (e) about the amended claims recite significantly more than the alleged abstract idea since the recited elements individually and as an ordered combination are not well-understood, routine, and conventional in the field (see second to last paragraph on page 10 through the second paragraph on page 11), the applicant appears to merely conclude that the entire claim is not well-understood, routine, and conventional in the field. However, as noted above, the Examiner discussed the respective well-understood, routine, and conventional limitations with regards to step 2B and how the evidence is supported/provided by the citation to the one or more court decisions in MPEP 2106.05(d). For applicant’s convenience, an excerpt from MPEP 2106.05(d) is provided:
“The required factual determination must be expressly supported in writing, as discussed in MPEP § 2106.07(a). Appropriate forms of support include one or more of the following: (a) A citation to an express statement in the specification or to a statement made by an applicant during prosecution that demonstrates the well-understood, routine, conventional nature of the additional element(s); (b) A citation to one or more of the court decisions discussed in Subsection II below as noting the well-understood, routine, conventional nature of the additional element(s); (c) A citation to a publication that demonstrates the well-understood, routine, conventional nature of the additional element(s); and (d) A statement that the examiner is taking official notice of the well-understood, routine, conventional nature of the additional element(s). For more information on supporting a conclusion that an additional element (or combination of additional elements) is well-understood, routine, conventional activity, see MPEP § 2106.07(a), subsection III.”
Therefore, applicant’s arguments are not persuasive and the respective 35 USC 101 rejections still stand.
Applicant’s arguments (see the second to last paragraph on page 11 through the last paragraph on page 13) have been fully considered but they are not persuasive. The applicant argues that the claims do not claim the amended claim limitations since Vukich’s prioritization and ordered display teaches or suggests the claimed transformation of digital content into executable data for context- and format-based rendering. The Examiner respectfully disagrees. As discussed in the 35 USC 103 rejections, the applicant’s specification discusses transforming raw message data into structured, actionable intelligence which, under broadest reasonable interpretation, is augmenting or generally linking metadata to the message such as taught by Vukich with the determination of a priority parameter for each message (i.e. actionable intelligence) which can be rendered as some indicator or flag when presented to the user (see Vukich col 9, lines 49 through col 10, line 30) as well as on context associated with the user such as proximity to known events/dates or other time varying data as well as personnel information (see col 17, lines 55-67). Additionally, the Examiner notes that applicant’s specification on the transforming via applying contextually relevant messaging format appears to broadly recited in paragraph 79 of applicant’s specification and discusses the contextually relevant messaging formats as part of the communication mechanism for personalization, similar to Vukich’s teachings of applying contextually relevant messaging format (i.e. color-coded prioritization) when communicating/rendering information. Therefore, as can be seen, the prior art references teach the claim limitations and the respective 35 USC 103 rejections still stand.
Conclusion
Any inquiry concerning this communication or earlier communications from the examiner should be directed to MARC S SOMERS whose telephone number is (571)270-3567. The examiner can normally be reached M-F 11-8 EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Ann Lo can be reached at 5712729767. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/MARC S SOMERS/Primary Examiner, Art Unit 2159 7/22/2026
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