DETAILED ACTION
This action is responsive to the amendments filed 9/16/2026.
Claims 1-20 are pending. Claims 1, 11 and 16 are currently amended.
All prior rejections under 35 U.S.C. §§ 102-103 are withdrawn as necessitated by amendment.
Claim Rejections - 35 USC § 103
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, 2, 6-8, 10-12, 16 and 17 are rejected under 35 U.S.C. 103 as being unpatentable over Gellens, U.S. PGPUB No. 2004/0176072 (“Gellens”), in view of Dotan-Cohen, et al., U.S. PGPUB No. 2018/0048595 (“Dotan-Cohen”).
With regard to Claim 1, Gellens teaches a method comprising:
identifying, by an application, an electronic message addressed to an inbox of a recipient ([0037] describes that email messages addressed to a user are initially delivered to an email server);
analyzing, by the application executing a messaging triaging model, the electronic message ([0038] describes that the server executes a filtering process to perform triage on the received email messages); and
determining, by the application, based on the analysis, whether the electronic message is a candidate for summarization ([0038] describes that certain messages can be determined for immediate delivery, while others receive additional or alternative processing, including messages designated as “preview” messages which can be delivered in summarized form), the determination further comprising:
causing delivery of the electronic message to the inbox according to a delivery protocol defined by a message platform hosting the inbox when the application determines the electronic message is not a candidate for summarization ([0038] describes that a message can be immediately forwarded in its entirety to an email client), and
causing delivery of at least an email summary of the electronic message to the inbox when the application determines the electronic message is a candidate for summarization ([0038] describes that filtering rules can cause an email summary or preview to be sent instead of the entire message).
Gellens does not teach determining a candidate for summarization according to an urgency level associated with the electronic message. Dotan-Cohen teaches at [0081] that emails can be modified using personalization logic, where personalization logic includes rules, conditions, associations, or other criteria. The personalization logic considers email-related information, including urgency, to determine personalization, where personalization can include summarization. Therefore, a determined level of urgency for a message is used in determining if a message is a candidate for summarization.
It would have been obvious to one of ordinary skill in the art at the time this application was filed to modify Gellens to include message urgency as described in Dotan-Cohen. One of skill in the art would have sought the modification, to improve user experience by enabling additional factors to be considered when determining which messages to summarize, thereby allowing for determinations that better match a user’s preferences.
Claim 11 recites a system comprising: a processor (Fig. 2) configured to carry out the method of Claim 1, and is similarly rejected. Claim 16 recites a medium encoded with instructions ([0012]) for carrying out the method of Claim 1, and is likewise rejected.
With regard to Claim 2, Gellens teaches calling, upon identifying of the electronic message, the message triaging model. [0044] describes that the server’s filtering rules are applied when an email message is received by the email server.
Claim 12 recites a system comprising: a processor (Fig. 2) configured to carry out the method of Claim 2, and is similarly rejected. Claim 17 recites a medium encoded with instructions ([0012]) for carrying out the method of Claim 2, and is likewise rejected.
With regard to Claim 6, Gellens teaches performing the delivery of the email summary by sending a message inbox item with the summary as part of an inbox for display within the inbox. [0038] describes that the message summaries are forwarded to the email client, along with the messages determined to be sent in their entirety. [0045] describes that the summaries are received and viewed in the email client in the same manner as ordinary received messages.
With regard to Claim 7, Gellens teaches that the message triaging model performs the analysis of the electronic message based on information selected from: sender identifier (ID), sender domain, content, category of content, type of content, number of recipients, recipient ID, message type, message format, a time, date and a location. [0046]-[0047] describes that user feedback can indicate whether future messages are to be delivered in full or deleted based on feedback, which causes the system to treat messages similar to a message for which feedback was received in the directed manner. Similarity can be determined using aspects such as an email subject, or sender.
With regard to Claim 8, Gellens teaches that the application executing on a device of the recipient. [0038] describes that the operations of the email triaging are carried out using an email client that operates on the recipient device.
With regard to Claim 10, Gellens teaches the application being associated with a mail platform. [0009] describes a server interacting with a client email application. [0003] describes that the background of the invention includes web email platforms, such as Hotmail.
Claims 3-5, 9, 13-15 and 18-20 are rejected under 35 U.S.C. 103 as being unpatentable over Gellens, in view of Dotan-Cohen, and in view of Milich, et al., U.S. PGPUB No. 2025/0383758 (“Milich”).
With regard to Claim 3, Gellens, in view of Milich teaches sampling data from a set of electronic messages; sampling data from a set of inboxes; analyzing the sampled data from the set of electronic messages and the sampled data from the set of inboxes; and performing fine-tuning of the message triaging model based on the analysis of the sampled data.
Gellens teaches at [0046] that a user can provide feedback regarding a message for which a summary was provided to is to apply to future messages. A user can provide a data sample from the messages in the user’s inbox, indicating that messages including a particular sender or subject should be delivered in full in the future, thereby fine-tuning the filtering rules with regard to that particular message information. Milich teaches at [0072]-[0073] that a machine learning LLM can be fine-tuned by providing data samples, where [0198] describes an AI system being used to triage email messages and summarize text.
It would have been obvious to one of ordinary skill in the art at the time this application was filed to modify Gellens and Dotan-Cohen to implement email triage functions using AI as described in Milich. One of skill in the art would have sought the modification, to improve system functioning by leveraging AI to provide superior triage and summarization over the rules-based filtering approach described in Gellens.
Claim 13 recites a system comprising: a processor (Fig. 2) configured to carry out the method of Claim 3, and is similarly rejected. Claim 18 recites a medium encoded with instructions ([0012]) for carrying out the method of Claim 3, and is likewise rejected.
With regard to Claim 4, Gellens, in view of Milich teaches extracting message information from the electronic message; and performing model-fine tuning of the message triaging model based on the electronic message and information related to the triaging determination. Gellens at [0046] describes that a user can fine-tune the rule-based filtering model by providing feedback in the form of subject or sender information extracted from a message when a user indicates that messages similar to a selected message should be handled a certain way. Milich teaches at [0072]-[0073] that a machine learning LLM can be fine-tuned by providing data samples, where [0198] describes an AI system being used to triage email messages and summarize text.
It would have been obvious to one of ordinary skill in the art at the time this application was filed to modify Gellens and Dotan-Cohen to implement email triage functions using AI as described in Milich. One of skill in the art would have sought the modification, to improve system functioning by leveraging AI to provide superior triage and summarization over the rules-based filtering approach described in Gellens.
Claim 14 recites a system comprising: a processor (Fig. 2) configured to carry out the method of Claim 4, and is similarly rejected. Claim 19 recites a medium encoded with instructions ([0012]) for carrying out the method of Claim 4, and is likewise rejected.
With regard to Claim 5, Milich teaches calling and executing a summarization LLM model, such that the electronic message is input to the summarization LLM model; and generating the email summary. [0163] describes that a visual appearance of an inbox includes summaries, which are generated for emails using an LLM.
It would have been obvious to one of ordinary skill in the art at the time this application was filed to modify Gellens and Dotan-Cohen to implement email triage functions using AI as described in Milich. One of skill in the art would have sought the modification, to improve system functioning by leveraging AI to provide superior triage and summarization over the rules-based filtering approach described in Gellens.
With regard to Claim 9, Milich teaches the application executing on a cloud. [0090] describes the use of a cloud-based model. [0064] describes cloud-based server units, and [0246] describes that the implementing computer system can be one or more cloud components on one or more networks.
It would have been obvious to one of ordinary skill in the art at the time this application was filed to modify Gellens and Dotan-Cohen to implement email triage functions using AI as described in Milich. One of skill in the art would have sought the modification, to improve system functioning by leveraging AI to provide superior triage and summarization over the rules-based filtering approach described in Gellens.
With regard to Claim 15, Gellens, in view of Milich teaches the processor further configured to: call and execute a summarization LLM model, such that the electronic message is input to the summarization LLM model; generate the email summary; and perform the delivery of the email summary by sending a message inbox item with the summary as part of an inbox for display within the inbox. Gellens teaches at [0038] that the message summaries are forwarded to the email client, along with the messages determined to be sent in their entirety. [0045] describes that the summaries are received and viewed in the email client in the same manner as ordinary received messages. Milich teaches at [0163] that a visual appearance of an inbox includes summaries, which are generated for emails using an LLM.
It would have been obvious to one of ordinary skill in the art at the time this application was filed to modify Gellens and Dotan-Cohen to implement email triage functions using AI as described in Milich. One of skill in the art would have sought the modification, to improve system functioning by leveraging AI to provide superior triage and summarization over the rules-based filtering approach described in Gellens.
Claim 20 recites a medium encoded with instructions ([0012]) implementing the system of Claim 15, and is similarly rejected.
Response to Arguments
Applicant’s arguments have been considered but are moot, as the newly cited Dotan-Cohen reference teaches or suggests the elements of the amended claims regarding considering an urgency level when determining whether to generate summary information.
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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/KEITH D BLOOMQUIST/Primary Examiner, Art Unit 2171
10/5/2026
