DETAILED ACTION
This final rejection is responsive to communication filed March 16, 2026. Claims 1, 2, 6, 10-17 and 20 are currently amended. Claims 4-5, 7-9, 18 and 19 are canceled. Claims 1-3, 6, 10-17, and 20 are pending in this application.
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 .
Claim Rejections - 35 USC § 112(b)
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.
Claim 14 is 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. Claim 14 does not include any language after the preamble, and therefore it is unclear what Applicant is trying to claim.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(d):
(d) REFERENCE IN DEPENDENT FORMS.—Subject to subsection (e), a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
The following is a quotation of pre-AIA 35 U.S.C. 112, fourth paragraph:
Subject to the following paragraph [i.e., the fifth paragraph of pre-AIA 35 U.S.C. 112], a claim in dependent form shall contain a reference to a claim previously set forth and then specify a further limitation of the subject matter claimed. A claim in dependent form shall be construed to incorporate by reference all the limitations of the claim to which it refers.
Claim 14 is rejected under 35 U.S.C. 112(d) or pre-AIA 35 U.S.C. 112, 4th paragraph, as being of improper dependent form for failing to further limit the subject matter of the claim upon which it depends, or for failing to include all the limitations of the claim upon which it depends. Claim 14 does not include any language after the preamble, and therefore it fails to further limit claim 1. Applicant may cancel the claim(s), amend the claim(s) to place the claim(s) in proper dependent form, rewrite the claim(s) in independent form, or present a sufficient showing that the dependent claim(s) complies with the statutory requirements.
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 1-3, 6, 10-17, and 20 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more.
Claims 1, 15, and 20 recite the following limitations directed to an abstract idea because the broadest reasonable interpretation of these steps is that the steps fall within the mental process groupings of abstract ideas because they cover concepts performed in the human mind, including observation, evaluation, judgment, and opinion. See MPEP 2106.04(a)(2), subsection III:
assign the plurality of messages to one or more conversations based on at least one of: a time of posting, a user identifier, or message content– (mental process – a user can mentally assign messages to conversations by making observation and evaluation based on time, user identifier, or content);
generate one or more conversation documents corresponding to the one or more conversations wherein the one or more conversation documents each comprises one or more identifiers of messages belonging to a corresponding conversation, content associated with the messages belonging to the corresponding conversation, and metadata identifying a corresponding communication channel of the plurality of communication channels associated with each message of the corresponding conversation - (mental process – user can manually generate conversation documents with the aid of pen and paper based on mentally analyzing conversations from multiple communication channels);
identify a referenced document associated with a first conversation of the one or more conversations - (mental process – user can mentally identify a references document by making an evaluation); and
generate a summary of the referenced document - (mental process – user can mentally (and with the aid of pen and paper) summarize a document).
This judicial exception is not integrated into a practical application because the following additional elements are not indicative of integration into practical application:
a hardware storage device configured to store a search index for groups of communications - (mere instructions to apply the exception using a generic computer component);
one or more processors in communication with the storage device – (mere instructions to apply the exception using a generic computer component);
acquire/receive a plurality of messages from a plurality of different communication channels (Mere data gathering or Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g));
generating conversation documents each comprises a machine-readable data structure (mere instructions to apply the exception using a generic computer component);
using a generative artificial intelligence model to generate a summary (mere instructions to apply the exception using a generic computer component);
store the summary of the referenced document in a first conversation document of the one or more conversation documents storing the first conversation (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g));
store the one or more conversation documents as searchable content within the search index, wherein the search index comprises a database storing searchable documents retrieved from a plurality of data sources associated with an entity (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g));
receive a search query associated with at least one of the one or more conversations (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)); and
display, via a graphical user interface, a ranked list of documents relevant to the search query, the ranked list comprising at least one of the one or more conversation documents (Adding insignificant extra-solution activity to the judicial exception - see MPEP 2106.05(g)).
Even when viewed in combination, these additional elements do not integrate the recited judicial exception into a practical application, and the claims are directed to the judicial exception.
The claims do not include additional elements that are sufficient to amount to significantly more than the judicial exception because the following additional limitations are not indicative of an inventive concept (i.e. “significantly more”):
a hardware storage device configured to store a search index for groups of communications - (mere instructions to apply the exception using a generic computer component);
one or more processors in communication with the storage device – (mere instructions to apply the exception using a generic computer component);
acquire/receive a plurality of messages from a plurality of different communication channels (MPEP 2106.05(d)(II) indicates that merely “receiving or transmitting data over a network” is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim));
generating conversation documents each comprises a machine-readable data structure (mere instructions to apply the exception using a generic computer component);
using a generative artificial intelligence model to generate a summary (mere instructions to apply the exception using a generic computer component);
store/incorporate the summary of the referenced document in a first conversation document of the one or more conversation documents storing the first conversation (MPEP 2106.05(d)(II) indicates that merely “storing and retrieving information in memory” is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim));
store/incorporate the one or more conversation documents as searchable content within the search index, wherein the search index comprises a database storing searchable documents retrieved from a plurality of data sources associated with an entity (MPEP 2106.05(d)(II) indicates that merely “storing and retrieving information in memory” is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim));
receive a search query associated with at least one of the one or more conversations (MPEP 2106.05(d)(II) indicates that merely “receiving or transmitting data over a network” is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim)); and
display, via a graphical user interface, a ranked list of documents relevant to the search query, the ranked list comprising at least one of the one or more conversation documents (MPEP 2106.05(d)(II) indicates that merely “receiving or transmitting data over a network” or “presenting offers and gathering statistics” is well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claim)).
Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
Claim 2 recites the following limitations directed to a mental process “detect a conversation boundary between a first group of messages corresponding to the first conversation and a second group of messages corresponding to a second conversation.” This judicial exception is not integrated into a practical application because the additional elements of one or more processors represents mere instructions to apply the exception using a generic computer component and thus are not indicative of integration into practical application. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of one or more processors represents mere instructions to apply the exception using a generic computer component and thus is not indicative of an inventive concept.
Claim 3 recites the following limitations directed to a mental process “detect the conversation boundary between the first group of messages and the second group of messages.” This judicial exception is not integrated into a practical application because the additional elements of one or more processors and using a machine learning model to detect the conversation boundary represents adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and thus are not indicative of integration into practical application. The examiner notes that the additional element of a machine learning model is a high level application of a previously trained model to detect conversation boundaries. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of one or more processors and using a machine learning model to detect the conversation boundary represents adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and thus are not indicative of an inventive concept.
Claim 6 recites the following limitations directed to mental processes “identify a first subject matter classification for the first group of messages and a second subject matter classification for a particular message; and detect that the particular message should be assigned to the second group of messages different from the first group of messages based on the first subject matter classification for the first group of messages and the second subject matter classification for the particular message.” This judicial exception is not integrated into a practical application because the additional elements of one or more processors represents mere instructions to apply the exception using a generic computer component and thus are not indicative of integration into practical application. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of one or more processors represents mere instructions to apply the exception using a generic computer component and thus is not indicative of an inventive concept.
Claims 10-12 recite limitations that further describe the acquired/received messages and/or source of the messages. As such, these limitations do not integrate the judicial exception into a practical application and are not sufficient to amount to significantly more than the judicial exception. MPEP 2106.05(d)(II) indicates that merely “receiving or transmitting data over a network” is a well‐understood, routine, conventional function when it is claimed in a merely generic manner (as it is in the present claims).
Claim 13 recites the following limitation directed to a mental process “detect that the first group of messages has exceeded a maximum number of messages per grouping and detect that the second message should be assigned to the second group of messages different from the first group of messages based on detection that the first group of messages has exceeded the maximum number of messages per grouping”. This judicial exception is not integrated into a practical application because the additional elements of one or more processors represents mere instructions to apply the exception using a generic computer component and thus are not indicative of integration into practical application. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of one or more processors represents mere instructions to apply the exception using a generic computer component and thus is not indicative of an inventive concept.
Claim 14 does not recite any additional limitations. The judicial exception is not integrated into a practical application because the additional elements of one or more processors represents mere instructions to apply the exception using a generic computer component and thus are not indicative of integration into practical application. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional elements of one or more processors represents mere instructions to apply the exception using a generic computer component and thus is not indicative of an inventive concept.
Claim 16 recites the following limitation: wherein assigning the plurality of messages to the one or more conversations comprises applying a machine learning model to classify messages into one of the one or more conversations. This judicial exception is not integrated into a practical application because the additional element of using a machine learning model to classify messages represents adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and thus is not indicative of integration into practical application. The examiner notes that the additional element of a machine learning model is a high level application of a trained model to assign a second message to the second group of messages. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because the additional element of using a machine learning model to assign the plurality of messages to conversations represents adding the words “apply it” (or an equivalent) with the judicial exception, or mere instructions to implement an abstract idea on a computer, or merely uses a computer as a tool to perform an abstract idea and thus are not indicative of an inventive concept.
Claim 17 recites the following limitations directed to mental processes “determining a first subject matter classification associated with contents of the first message; determining a second subject matter classification associated with contents of the second message; and detecting that the second message should be assigned a conversation of the one or more conversations based on the first subject matter classification and the second subject matter classification.” This judicial exception is not integrated into a practical application because there are no additional elements. The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception because there are no additional elements.
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.
Claim 1, 14, 15 and 20 are rejected under 35 U.S.C. 103 as being unpatentable over Menon et al. (US 2020/0311151 A1) (‘Menon’) in view of Liu et al. (US 2021/0152506 A1) (‘Liu’), and further in view of Alakuijala et al. (US 20140280614 A1) (‘Alakuijala’).
With respect to claim 1, Menon teaches a system, comprising:
a hardware storage device configured to store a search index for groups of communications (paragraphs 23-24); and
one or more processors (paragraph 61) in communication with the storage device configured to:
acquire a plurality of messages from a plurality of different communication channels (paragraphs 17 and 18);
assign the plurality of messages to one or more conversations based on at least one of: a time of posting, a user identifier, or message content (defines a conversation as a series (e.g., series 112-114) of messages exchanged between or among two or more participants…defines each conversation based on a conversation title, group name, time period spanning messages in the conversation) (paragraph 18);
generate one or more conversation document corresponding to the one or more conversations, wherein the one or more conversation documents each comprises a machine-readable data structure comprising one or more identifiers of messages belonging to a corresponding conversation, content associated with the messages belonging to the corresponding conversation, and metadata associated with each message of the corresponding conversation (paragraphs 18-20and 57);
store a summary (i.e. message content) in a first conversation document of the one or more conversation documents storing the first conversation (paragraphs 19 and 21);
store the one or more conversation documents as searchable content within the search index, wherein the search index comprises a database storing searchable documents retrieved from a plurality of data sources associated with an entity (paragraphs 13, 22, and 24);
receive a search query associated with at least one of the one or more conversations (paragraphs 22 and 28-29); and
display, via a graphical user interface, a list of documents relevant to the search query, the list comprising at least one of the one or more conversation documents (paragraph 29).
Menon does not explicitly teach wherein conversation documents are configured to include metadata identifying a corresponding communication channel of the plurality of communication channels associated with each message of the corresponding conversation.
Liu teaches wherein conversation documents are configured to include metadata identifying a corresponding communication channel (i.e. source) of the plurality of communication channels associated with each message of the corresponding conversation (paragraphs 36-38).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified Menon to include conversation documents from multiple communication channels as taught by Liu to enable all related messages, regardless of platform, to be viewed/stored together (Liu, abstract and paragraph 38). Menon teaches that a conversation of messages can include an email thread, a series of chats exchanged within a group or channel, and/or a string of responses and/or comments to a post, article, and/or other content, and thus it would have been obvious to incorporating messages from those different places into a single view/document. Therefore, the modification would entail combining known prior art elements (i.e. messages from different communication channels) to achieve predictable results (i.e. a conversation with messages from different communication channels.)
Further regarding claim 1, Menon in view of Liu does not explicitly teach identify a referenced document associated with a first conversation of the one or more conversations; generate, using a generative artificial intelligence model, a summary of the referenced document; store the summary of the referenced document in a first conversation document of one or more conversation documents storing the first conversation; or ranking a list of documents.
Alakuijala teaches identify a referenced document associated with a first conversation of the one or more conversations; generate, using a generative artificial intelligence model (paragraph 18), a summary of the referenced document; and store the summary of the referenced document in a first conversation document of one or more conversation documents storing the first conversation (paragraphs 41-42); and
ranking a list of documents (paragraph 23).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified Menon to identify and summarize a reference document associated with a conversation as taught by Alakuijala to enable information of interest to a receiver/sender of the message to be extracted and summarized from a document mentioned in a conversation and presented within the conversation, thereby saving the sender/receiver of the message time from not having to open and read the external document (Alakuijala, abstract). Further, including the summarized content would improve searching of Menon by allowing all aspects of a conversation to be recorded and searched.
With respect to claim 14, Menon in view of Liu and Alakuijala teaches wherein the one or more processors are further configured to (Menon, paragraph 61).
With respect to claim 15, Menon teaches a method for operating a search system, comprising:
receiving a plurality of messages from a plurality of different communication channels (paragraphs 17 and 18);
assigning the plurality of messages to one or more conversations based on at least one of: a time of posting, a user identifier, or message content (defines a conversation as a series (e.g., series 112-114) of messages exchanged between or among two or more participants…defines each conversation based on a conversation title, group name, time period spanning messages in the conversation) (paragraph 18);
generating one or more conversation document corresponding to the one or more conversations, wherein the one or more conversation documents each comprises a machine-readable data structure comprising one or more identifiers of messages belonging to a corresponding conversation, content associated with the messages belonging to the corresponding conversation, and metadata associated with each message of the corresponding conversation (paragraphs 18-20and 57);
storing a summary (i.e. message content) in a first conversation document of the one or more conversation documents storing the first conversation (paragraphs 19 and 21);
storing the one or more conversation documents as searchable content within the search index, wherein the search index comprises a database storing searchable documents retrieved from a plurality of data sources associated with an entity (paragraphs 13, 22, and 24);
receiving a search query associated with at least one of the one or more conversations (paragraphs 22 and 28-29); and
displaying, via a graphical user interface, a list of documents relevant to the search query, the list comprising at least one of the one or more conversation documents (paragraph 29).
Menon does not explicitly teach wherein conversation documents are configured to include metadata identifying a corresponding communication channel of the plurality of communication channels associated with each message of the corresponding conversation.
Liu teaches wherein conversation documents are configured to include metadata identifying a corresponding communication channel (i.e. source) of the plurality of communication channels associated with each message of the corresponding conversation (paragraphs 36-38).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified Menon to include conversation documents from multiple communication channels as taught by Liu to enable all related messages, regardless of platform, to be viewed/stored together (Liu, abstract and paragraph 38). Menon teaches that a conversation of messages can include an email thread, a series of chats exchanged within a group or channel, and/or a string of responses and/or comments to a post, article, and/or other content, and thus it would have been obvious to incorporating messages from those different places into a single view/document. Therefore, the modification would entail combining known prior art elements (i.e. messages from different communication channels) to achieve predictable results (i.e. a conversation with messages from different communication channels.)
Further regarding claim 15, Menon in view of Liu does not explicitly teach identifying a referenced document associated with a first conversation of the one or more conversations; generating, using a generative artificial intelligence model, a summary of the referenced document; storing the summary of the referenced document in a first conversation document of one or more conversation documents storing the first conversation; or ranking a list of documents.
Alakuijala teaches identifying a referenced document associated with a first conversation of the one or more conversations; generating, using a generative artificial intelligence model (paragraph 18), a summary of the referenced document; and storing the summary of the referenced document in a first conversation document of one or more conversation documents storing the first conversation (paragraphs 41-42); and
ranking a list of documents (paragraph 23).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified Menon to identify and summarize a reference document associated with a conversation as taught by Alakuijala to enable information of interest to a receiver/sender of the message to be extracted and summarized from a document mentioned in a conversation and presented within the conversation, thereby saving the sender/receiver of the message time from not having to open and read the external document (Alakuijala, abstract). Further, including the summarized content would improve searching of Menon by allowing all aspects of a conversation to be recorded and searched.
With respect to claim 20, Menon teaches one or more non-transitory storage devices containing processor readable code for configuring one or more processors to perform a method for operating a search system, wherein the processor readable code configures the one or more processors to:
acquire a plurality of messages from a plurality of different communication channels (paragraphs 17 and 18);
assign the plurality of messages to one or more conversations based on at least one of: a time of posting, a user identifier, or message content (defines a conversation as a series (e.g., series 112-114) of messages exchanged between or among two or more participants…defines each conversation based on a conversation title, group name, time period spanning messages in the conversation) (paragraph 18);
generate one or more conversation documents corresponding to the one or more conversations (paragraphs 18-19 and 57);
incorporate a summary (i.e. message content) in a first conversation document of the one or more conversation documents storing the first conversation (paragraphs 19 and 21);
incorporate the one or more conversation documents as searchable content within the search index, wherein the search index comprises a database storing searchable documents retrieved from a plurality of data sources associated with an entity (paragraphs 13, 22, and 24);
receiving a search query associated with at least one of the one or more conversations (paragraphs 22 and 28-29); and
displaying, via a graphical user interface, a list of documents relevant to the search query, the list comprising at least one of the one or more conversation documents (paragraph 29).
Menon does not explicitly teach wherein conversation documents are configured to include messages originating from multiple communication channels.
Liu teaches wherein conversation documents are configured to include messages originating from multiple communication channels (paragraphs 36 and 38).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified Menon to include conversation documents from multiple communication channels as taught by Liu to enable all related messages, regardless of platform, to be viewed/stored together (Liu, abstract and paragraph 38). Menon teaches that a conversation of messages can include an email thread, a series of chats exchanged within a group or channel, and/or a string of responses and/or comments to a post, article, and/or other content, and thus it would have been obvious to incorporating messages from those different places into a single view/document. Therefore, the modification would entail combining known prior art elements (i.e. messages from different communication channels) to achieve predictable results (i.e. a conversation with messages from different communication channels.)
Further regarding claim 20, Menon in view of Liu does not explicitly teach identify a referenced document associated with a first conversation of the one or more conversations; generate, using a generative artificial intelligence model, a summary of the referenced document; incorporate the summary of the referenced document in a first conversation document of one or more conversation documents storing the first conversation; or ranking a list of documents.
Alakuijala teaches identify a referenced document associated with a first conversation of the one or more conversations; generate, using a generative artificial intelligence model (paragraph 18), a summary of the referenced document; and incorporate the summary of the referenced document in a first conversation document of one or more conversation documents storing the first conversation (paragraphs 41-42); and
ranking a list of documents (paragraph 23).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified Menon to identify and summarize a reference document associated with a conversation as taught by Alakuijala to enable information of interest to a receiver/sender of the message to be extracted and summarized from a document mentioned in a conversation and presented within the conversation, thereby saving the sender/receiver of the message time from not having to open and read the external document (Alakuijala, abstract). Further, including the summarized content would improve searching of Menon by allowing all aspects of a conversation to be recorded and searched.
Claims 2, 3, 10, 12 and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Menon in view of Liu and Alakuijala, as applied to claims 1 and 15 above, and further in view of Brunn et al. (US 2020/0042595 A1) (‘Brunn’).
With respect to claim 2, Menon in view of Liu and Alakuijala teaches system of claim 1, wherein the one or more processors are configured to detect that the second message should be assigned to the second group of messages different from the first group of messages (Menon, paragraph 18).
Menon in view of Liu and Alakuijala does not explicitly teach detecting a conversation boundary between a first group of messages corresponding to the first conversation and a second group of messages corresponding to a second conversation.
Brunn teaches detecting a conversation boundary between a first group of messages corresponding to the first conversation and a second group of messages corresponding to a second conversation (paragraphs 23, 38, and 67).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified the assigning of messages to groups in Menon to detect a conversation boundary between and first and second group of messages as taught by Brunn to enable more efficient and precise determination of conversations based on conversation boundaries. A person having ordinary skill in the art would have been motivated to make the modification because it is obvious that Menon determines conversation boundaries when he groups messages into conversations, and thus the combination represents combining known elements to achieve predictable results.
With respect to claim 3, Menon in view of Liu, Alakuijala and Brunn teaches the system of claim 2, wherein: the one or more processors are configured to detect the conversation boundary between the first group of messages and the second group of messages using a machine learning model (Brunn, paragraphs 35 and 41).
With respect to claim 10, Menon in view of Liu, Alakujala and Brunn teaches the system of claim 2, wherein: the first group of messages comprises a set of contiguous messages within a messaging application (Menon, paragraphs 17-18 and 21).
With respect to claim 12, Menon in view of Liu, Alakujala and Brunn teaches the system of claim 1, wherein: the first group of messages comprises messages from a first application; and the second group of messages comprises messages from a second application (a conversation can include an email thread, a series of chats exchanged within a group or channel, and/or a string of responses and/or comments to a post, article, and/or other content) (Menon, paragraph 18).
With respect to claim 16, Menon in view of Liu and Alakujala teaches assigning the plurality of messages to the one or more conversations (Menon, paragraph 18).
Menon in view of Liu and Alakujala does not explicitly teach wherein assigning the plurality of messages to the one or more conversations comprises applying a machine learning model to classify messages into one of the one or more conversations.
Brunn teaches wherein assigning the plurality of messages to the one or more conversations comprises applying a machine learning model to classify messages into one of the one or more conversation (paragraphs 23, 35, 41 and 67).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified the assigning of messages to groups in Menon to be based on applying a machine learning model to classify messages into one of the one or more conversations as taught by Brunn to enable more efficient and precise determination of conversations based on conversation boundaries and to enable a smart way of determining message boundaries. A person having ordinary skill in the art would have been motivated to make the modification because it is obvious that Menon determines conversation boundaries when he groups messages into conversations, and thus the combination represents combining known elements to achieve predictable results.
Claims 6 and 11 are rejected under 35 U.S.C. 103 as being unpatentable over Menon in view of Liu, Alakuijala and Brunn, as applied to claim 2 above, and further in view of Hassan et al. (US 2022/0385606 A1) (‘Hassan’).
With respect to claim 6, Menon in view of Liu, Alakuijala and Brunn teaches system of claim 2, wherein: the one or more processors are configured to identify a first tag/label/title for the first group of messages and a second tag/label/title for a particular message (Menon, paragraphs 11, 18, 19 and 31); and
the one or more processors are configured to detect that the particular message should be assigned to the second group of messages different from the first group of messages based on the first tag/label/title for the first group of messages and the second tag/label/title for the particular message (Menon, paragraphs 11, 18, 19 and 31).
Although Menon in view of Liu teaches identifying tags, label and title for groups of messages and assigning messages to groups based on tags, label or title, Menon does not explicitly teach the one or more processors are configured to identify a first subject matter classification for the first group of messages and a second subject matter classification for a particular message; and the one or more processors are configured to detect that the particular message should be assigned to the second group of messages different from the first group of messages based on the first subject matter classification for the first group of messages and the second subject matter classification for the particular message.
Hassan teaches identify a first subject matter classification for the first group of messages and a second subject matter classification for the particular message; detect that the particular message should be assigned to the second group of messages different from the first group of messages based on the first subject matter classification for the first group of messages and the second subject matter classification for the particular message (Fig. 2, paragraphs 30, 32, 35 and 69).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified the grouping of messages of Menon to be based on subject matter classification as taught by Hassan to enable an additional way to group messages based on subject matter classification, thereby improving capabilities of Menon’s message group and allowing conversations to be determined based on users. A person having ordinary skill in the art would have been motivated to make the combination because Menon teaches defining conversation/grouping messages based on tags/label/title and thus detecting groups based on subject matter classification would only entails swapping the determination based on tag, label or title to be based on subject matter classification.
With respect to claim 11, Menon in view of Liu, Alakujala, Brunn, and Hassan teaches system of claim 1, wherein: the particular message comprises a root message for the second group of messages (Menon, paragraphs 54 and 58).
Claim 13 is rejected under 35 U.S.C. 103 as being unpatentable over Menon in view of Liu, Alakujala and Brunn, as applied to claim 2 above, and further in view of Dunne et al. (US 2020/0057808 A1) (‘Dunne’).
With respect to claim 13, Menon in view of Liu, Alakujala and Brunn teaches the system of claim 2.
Menon in view of Liu, Alakujala and Brunn does not explicitly teach detect that the first group of messages has exceeded a maximum number of messages per grouping and detect that the second message should be assigned to the second group of messages different from the first group of messages based on detection that the first group of messages has exceeded the maximum number of messages per grouping.
Dunne teaches detect that the first group of messages has exceeded a maximum number of messages per grouping and detect that the second message should be assigned to the second group of messages different from the first group of messages based on detection that the first group of messages has exceeded the maximum number of messages per grouping (paragraphs 4, 57 and 59-60).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified Menon to assign a second message to a second group based on number of messages exceeding a threshold as taught by Dunne to improve grouping of messages by determining a divergent topic based on number of messages, topic and time (Dunne, abstract, paragraph 57). A person having ordinary skill in the art would have been motivated to make the combination because Menon teaches several methods for defining conversation/grouping messages and thus detecting groups based on number of messages represents a combination of known group detection elements to achieve predictable results of messages grouped into conversations.
Claim 17 is rejected under 35 U.S.C. 103 as being unpatentable over Menon in view of Liu and Alakujala, as applied to claim 15 above, and further in view of Hassan et al. (US 2022/0385606 A1) (‘Hassan’).
With respect to claim 17, Menon in view of Liu and Alakujala teaches the method of claim 15, further comprising determining a first tag/label/title for the first group of messages and a second tag/label/title for the second message (Menon, paragraphs 11, 18, 19 and 31); and
detecting that the second message should be assigned to a conversation of the one or more conversations based on the first tag/label/title for the first group of messages and the second tag/label/title for the second message (Menon, paragraphs 11, 18, 19 and 31).
Although Menon in view of Liu and Alakujala teaches identifying tags, label and title for groups of messages and assigning messages to groups based on tags, label or title, Menon does not explicitly teach determining a first subject matter classification associated with contents of the first message; determining a second subject matter classification associated with contents of the second message; and detecting that the second message should be assigned to a conversation of the one or more conversations based on the first subject matter classification and the second subject matter classification.
Hassan determining a first subject matter classification associated with contents of the first message; determining a second subject matter classification associated with contents of the second message; and detecting that the second message should be assigned to a conversation of the one or more conversations based on the first subject matter classification and the second subject matter classification (Fig. 2, paragraphs 30, 32, 35 and 69).
It would have been obvious to a person having ordinary skill in the art prior to the effective filing date of the invention to have modified the grouping of messages of Menon to be based on subject matter classification as taught by Hassan to enable an additional way to group messages based on subject matter classification, thereby improving capabilities of Menon’s message group and allowing conversations to be determined based on users. A person having ordinary skill in the art would have been motivated to make the combination because Menon teaches defining conversation/grouping messages based on tags/label/title and thus detecting groups based on subject matter classification would only entails swapping the determination based on tag, label or title to be based on subject matter classification.
Response to Arguments
Applicant's arguments filed March 16, 2026 have been fully considered but they are not persuasive. Applicant argues that the claims recite a specific technical pipeline, in which the ordered combination reflects a specific technical improvement on how search systems organize, index, and present conversation data to users. The examiner disagrees. The steps in said ordered combination recite limitations that are merely applying the abstract idea with a computer or adding insignificant extra-solution activity that is well-understood, routine and conventional. Even when considered in combination, these additional elements represent mere instructions to implement an abstract idea or other exception on a computer and insignificant extra-solution activity, which do not provide an inventive concept.
Applicant further argues that the combination of generative AI summarization with displaying ranking search results via a GUI demonstrates integration into practical application because they are not mental processes/abstract ideas. However, the examiner does not assert that the generating of a summary using AI or displaying ranked search results via a GUI are part of an abstract idea. Using generative AI to summarize data represents applying the abstract idea using a computer and displaying ranked search results is well-understood, routine, and conventional.
Applicant argues that the claims are analogous to USPTO Example 47 because the claims use a generative AI model to generate summaries and deliver ranked search results. Applicant argues that these limitations provide an improvement to quality and relevance of search results. The examiner disagrees. Generating a summary and ranking search results are concepts that can be performed mentally. The use of generative AI does not provide any improvement, but instead merely applies the concepts that can be applied mentally using a computer. If anything, the computer is used as a tool to provide an alleged improvement.
Applicant argues that the specification emphasizes the technical improvement (i.e. improved quality and relevance of search results) at various places. However, applying an abstract idea with a computer does not provide a technical improvement. Similarly, adding limitations directed to insignificant extra-solution activity that are well-understood, routine and conventional does not provide a technical improvement.
Applicant argues that the display of ranked search results via a graphical user interface is not extra-solution activity, but rather practical output of the claimed invention. Applicant argues that the claims transform data through AI-generated enrichment to deliver improved search results. The examiner disagrees. Ranking search results and summarizing documents are steps that can be performed mentally. MPEP 2106.05 (d)(II) recites that “receiving and transmitting data over a network” and “presenting offers” are both well-understood, routine and conventional. Displaying an outcome of data that has been mentally processed is just post-solution activity. Further, using generative AI to perform summary and displaying results with a GUI also represents mere instructions to apply he abstract idea with a computer. There is no data transformation or enrichment to the data. There is no improvement in displaying ranked search results, as claimed.
Applicant’s prior art arguments with respect to claims 1-3, 6, 10-17, and 20 have been considered but are moot because the new ground of rejection does not rely on any reference applied in the prior rejection of record for any teaching or matter specifically challenged in the argument.
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.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to ALICIA M WILLOUGHBY whose telephone number is (571)272-5599. The examiner can normally be reached 9-5:30, EST, M-F.
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/ALICIA M WILLOUGHBY/Primary Examiner, Art Unit 2156
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