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 .
Response to Amendment
This Office Action has been issued in response to Applicant’s Communication of amended application S/N 18/927,089 filed on September 11, 2025. Claims 1 to 8, and 10 to 18 are currently pending with the application.
Claim Objections
Claims 1, 10, and 11 are objected to because of the following informalities:
Claims 1, 10, and 11 recite the limitation “training, using the collected conversation data by one or more processors, an artificial intelligence (AI) conversation model configured to generate natural language responses to input queries by labeling the pieces of text knowledge and the images as additional information for the user utterance”. For purposes of clarity, it should read “training, using the collected conversation data by one or more processors, an artificial intelligence (AI) conversation model configured to generate natural language responses to input queries, by labeling the pieces of text knowledge and the images as additional information for the user utterance”.
Appropriate corrections are required.
Claim Rejections - 35 USC § 112
The following is a quotation of 35 U.S.C. 112(b):
(b) CONCLUSION.—The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the inventor or a joint inventor regards as the invention.
The following is a quotation of 35 U.S.C. 112 (pre-AIA ), second paragraph:
The specification shall conclude with one or more claims particularly pointing out and distinctly claiming the subject matter which the applicant regards as his invention.
Claims 6 and 16 are rejected under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), second paragraph, as being indefinite for failing to particularly point out and distinctly claim the subject matter which the inventor or a joint inventor (or for applications subject to pre-AIA 35 U.S.C. 112, the applicant), regards as the invention.
Claim 6 recites the limitation “the characteristics feature information” in line 5. There is insufficient antecedent basis for this limitation in the claim. Same rationale applies to claim 16, since it recites similar limitations.
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 to 8, and 10 to 18 are rejected under 35 U.S.C. 101 because the claimed invention is directed to an abstract idea without significantly more. Claims 1, 10, and 11 searching text and images, and collecting information.
The limitation of searching text, which specifically recites “searching pieces of text knowledge related to a user utterance”, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting “by one or more processors”, nothing in the claim element precludes the steps from practically being performed in a human mind. For example, but for the “by one or more processors” language, “searching”, in the context of this claim encompasses the user mentally, with the aid of pen and paper, reading and identifying text that is related to a question. The limitation of searching images, which specifically recites “searching images related to the user utterance”, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting “by one or more processors”, nothing in the claim element precludes the steps from practically being performed in a human mind. For example, but for the “by one or more processors” language, “searching”, in the context of this claim encompasses the user mentally, with the aid of pen and paper, looking at a sheet of paper and identifying images that are related to the question.
Finally, the collecting information, which specifically recites “collecting the user utterance, the pieces of text knowledge, the images, and an answer to the user utterance as conversation data”, is a process that, under its broadest reasonable interpretation, covers performance of the limitation in the mind, but for the recitation of generic computer components. That is, other than reciting “by one or more processors”, nothing in the claim element precludes the steps from practically being performed in a human mind. For example, but for the “by one or more processors” language, “collecting”, in the context of this claim encompasses the user mentally, with the aid of pen and paper, keeping track of the question, the previously identified text and images, and writing down an answer to the query. If a claim limitation, under its broadest reasonable interpretation, covers mental processes but for the recitation of generic computer components, then it falls within the “Mental Processes” grouping of abstract ideas. Accordingly, the claims recite an abstract idea.
This judicial exception is not integrated into a practical application. In particular, the claims recite the additional elements – “training, using the collected conversation data, an artificial intelligence (Al) conversation model configured to generate natural language responses to input queries by labeling the pieces of text knowledge and the images as additional information for the user utterance”, “receiving input of an answer to the user utterance referring to the searched text knowledge and images” (claim 11), one or more processors, and a storage unit. The limitation “receiving input of an answer to the user utterance referring to the searched text knowledge and images” amounts to data-gathering steps which is considered to be insignificant extra-solution activity (See MPEP 2106.05(g)). The limitation “training, using the collected conversation data, an artificial intelligence (Al) conversation model configured to generate natural language responses to input queries by labeling the pieces of text knowledge and the images as additional information for the user utterance” is recited at a high-level of generality, with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, and is equivalent to merely saying “applying it”. The one or more processors and storage unit in these steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Accordingly, these additional elements do not integrate the abstract idea into a practical application because they do not impose any meaningful limits on practicing the abstract idea. The claims are directed to an abstract idea.
The claim does not include additional elements that are sufficient to amount to significantly more than the judicial exception. The insignificant extra-solution activity identified above, which include the data gathering steps, is recognized by the courts as well-understood, routine, and conventional activity when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (See MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)). The claims are not patent eligible.
Claim 2 is dependent on claim 1 and includes all the limitations of claim 1. Therefore, claim 2 recites the same abstract idea of claim 1. The claim recites the additional limitations of “searching text documents related to the user utterance; selecting some of the searched text documents; selecting some of the pieces of text knowledge within the selected text document; and finally selecting text knowledge to reference for the answer to the user utterance among the selected pieces of text knowledge, wherein the collecting comprises collecting, as the conversation data, the user utterance, a query used for searching documents, the text knowledge finally selected to reference for the answer to the user utterance, and the answer to the user utterance”, which is further elaborating on the abstract idea, and therefore it does not amount to significantly more. Same rationale applies to claims 4, 5, and 8.
Claim 3 is dependent on claim 2 and includes all the limitations of claim 1. Therefore, claim 3 recites the same abstract idea of claim 1. The claim recites the additional limitations of “the user utterance is inputted by a developer who performs a role of a user having a conversation with the AI conversation model, and wherein the answer to the user utterance is inputted by a developer who performs a role of the AI conversation model”, which amounts to data-gathering steps and which is considered to be insignificant extra-solution activity, (See MPEP 2106.05(g)), and recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (See MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network)). Therefore, does not amount to significantly more than the abstract idea.
Claim 6 is dependent on claim 4 and includes all the limitations of claim 1. Therefore, claim 6 recites the same abstract idea of claim 1. The claim recites the additional limitation of “displaying characteristics information which is pre-labeled for the image; selecting characteristic information to reference for the answer to the user utterance from the characteristics feature information; and adding the selected characteristic information on the image to the conversation data as knowledge on the image”, where the adding the information as presently presented is further elaborating on the abstract idea, and where the selecting amounts to data storing steps, and the displaying amounts to data-presentation steps, which are considered to be insignificant extra-solution activity, (See MPEP 2106.05(g)), and recognized by the courts as well-understood, routine, and conventional activities when they are claimed in a merely generic manner (e.g., at a high level of generality) or as insignificant extra-solution activity (See MPEP 2106.05(d)(II)(i) Receiving or transmitting data over a network, e.g., using the Internet to gather data, buySAFE, Inc. v. Google, Inc., 765 F.3d 1350, 1355, 112 USPQ2d 1093, 1096 (Fed. Cir. 2014) (computer receives and sends information over a network); (v) Presenting offers and gathering statistics, OIP Techs., 788 F.3d at 1362-63, 115 USPQ2d at 1092-93)). Therefore, the limitations do not amount to significantly more than the abstract idea. Same rationale applies to claim 7.
Additionally, the claims do not include a requirement of anything other than conventional, generic computer technology for executing the abstract idea, and therefore, do not amount to significantly more than the abstract idea.
Claims 1 to 8 and 10 to 18 are therefore not drawn to eligible subject matter as they are directed to an abstract idea without significantly more.
Claim Rejections - 35 USC § 103
In the event the determination of the status of the application as subject to AIA 35 U.S.C. 102 and 103 (or as subject to pre-AIA 35 U.S.C. 102 and 103) is incorrect, any correction of the statutory basis (i.e., changing from AIA to pre-AIA ) for the rejection will not be considered a new ground of rejection if the prior art relied upon, and the rationale supporting the rejection, would be the same under either status.
The following is a quotation of 35 U.S.C. 103 which forms the basis for all obviousness rejections set forth in this Office action:
A patent for a claimed invention may not be obtained, notwithstanding that the claimed invention is not identically disclosed as set forth in section 102, if the differences between the claimed invention and the prior art are such that the claimed invention as a whole would have been obvious before the effective filing date of the claimed invention to a person having ordinary skill in the art to which the claimed invention pertains. Patentability shall not be negated by the manner in which the invention was made.
Claims 1 to 4, 7, 8, 10 to 14, 17, and 18 are rejected under 35 U.S.C. 103 as being unpatentable over Clark et al. (U.S. Publication No. 2016/0110357) hereinafter Clark, and further in view of HALL et al. (U.S. Publication No. 2020/0302019) hereinafter Hall.
As to claim 1:
Clark discloses:
A processor-implemented conversation data collection method comprising:
searching, by one or more processors, pieces of text knowledge related to a user utterance [Paragraph 0027 teaches input query may be a question including various selection criteria; Paragraph 0038 teaches performing a search of a set of corpora to retrieve information to answer the question, where the corpora include document repositories; Paragraph 0061 teaches receiving a natural language question and performing a textual search by consulting various knowledge resources; Paragraph 0064 teaches performing a textual search for the user’s question];
searching, by one or more processors, images related to the user utterance [Paragraph 0062 teaches performing an image-type search based on the user question; Paragraph 0064 teaches performing an image-type search on a second corpus based on the input query, to find images related to the question]; and
collecting, by one or more processors, the user utterance, the pieces of text knowledge, the images, and an answer to the user utterance as conversation data [Paragraph 0030 teaches keeping track of user activity across sessions of interaction with the Q&A system, and retaining a succession of user questions, and answers produced in response to the questions; Paragraph 0041 teaches users may be engaged in dialog with the Q&A system, where the user may provide feedback on generated answers, which may be used for future question answering sessions, therefore, conversation data].
Clark does not appear to expressly disclose training, using the collected conversation data by one or more processors, an artificial intelligence (Al) conversation model configured to generate natural language responses to input queries by labeling the pieces of text knowledge and the images as additional information for the user utterance.
Hall discloses:
training, using the collected conversation data by one or more processors, an artificial intelligence (Al) conversation model configured to generate natural language responses to input queries by labeling the pieces of text knowledge and the images as additional information for the user utterance [Paragraph 0027 teaches collecting and processing a variety of communications, including queries from a user interacting with a dialog bot, to extract features from the request, including user query, background information, entity information, multi-turn utterances between user and a dialog bot, etc.; Paragraph 0100 teaches dialog bot training and deployment, including processing multimodal data, as audio and visually oriented data, metadata, images, patterns, etc.; Paragraph 0101 teaches machine learning classifiers perform image and textual processing, including multimodal information as textual, audio, video, image, visual, etc.; Paragraph 0102 teaches building and training convolutional neural networks to output an accurate classification of data (hence, labeling the text and images information) to create intuitive artificial conversational entities or dialog bots].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the teachings of the cited references and modify the invention as taught by Clark, by training, using the collected conversation data by one or more processors, an artificial intelligence (Al) conversation model configured to generate natural language responses to input queries by labeling the pieces of text knowledge and the images as additional information for the user utterance, as taught by Hall [Paragraph 0027, 0100-0102], because the applications are directed to improvements in processing search queries; training an AI conversation model with the collected data including text, images, and other data from multiple sources enables the improvement of human-machine interaction and overall user experience, while allowing self-learning, which may help reduce costs associated with required ongoing maintenance (See Hall Para [0019]).
As to claim 2:
Clark discloses:
searching text documents related to the user utterance [Paragraph 0027 teaches input query may be a question including various selection criteria; Paragraph 0038 teaches performing a search of a set of corpora to retrieve information to answer the question, where the corpora include document repositories; Paragraph 0061 teaches receiving a natural language question and performing a textual search by consulting various knowledge resources; Paragraph 0064 teaches performing a textual search for the user’s question]; selecting some of the searched text documents [Paragraph 0056 teaches extracting data from a set of source items, which are relevant source items during the search of the set of corpora]; selecting some of the pieces of text knowledge within the selected text document [Paragraph 0056 teaches processing the first and second data, generating a second set of candidate answers]; and finally selecting text knowledge to reference for the answer to the user utterance among the selected pieces of text knowledge [Paragraph 0056 teaches a final version of the second set of candidate answers may be selected based on having the highest confidence scores of all the potential candidate answers], wherein the collecting comprises collecting, as the conversation data, the user utterance, a query used for searching documents, the text knowledge finally selected to reference for the answer to the user utterance, and the answer to the user utterance [Paragraph 0030 teaches keeping track of user activity across sessions of interaction with the Q&A system, and retaining a succession of user questions, and answers produced in response to the questions; Paragraph 0041 teaches users may be engaged in dialog with the Q&A system, where the user may provide feedback on generated answers, which may be used for future question answering sessions].
As to claim 3:
Clark discloses:
wherein the user utterance is inputted by a developer who performs a role of a user having a conversation with the AI conversation model [Paragraph 0041 teaches users may be engaged in dialog with the QA system to evaluate the relevance of received answers to a question submitted by a user], and wherein the answer to the user utterance is inputted by a developer who performs a role of the AI conversation model [Paragraph 0041 teaches user may rank each answer according to its relevance to the question, where the feedback of users on generated answers may be used for future question answering sessions].
As to claim 4:
Clark discloses:
searching the images related to the user utterance [Paragraph 0062 teaches performing
an image-type search based on the user question; Paragraph 0064 teaches performing an image-type
search on a second corpus based on the input query, to find images related to the question]; and selecting images to use for the answer to the user utterance among the searched images [Paragraph 0064 teaches a lion photograph is then transmitted to remote device and presented to the user as the answer to the input query], wherein collecting comprises collecting, as the conversation data, the user utterances, a query used for searching images, the images selected to be used for the answer to the user utterance, and the answer to the user utterance [Paragraph 0030 teaches keeping track of user activity across sessions of interaction with the Q&A system, and retaining a succession of user questions, and answers produced in response to the questions; Paragraph 0041 teaches users may be engaged in dialog with the Q&A system, where the user may provide feedback on generated answers, which may be used for future question answering sessions, therefore, conversation data].
As to claim 7:
Clark discloses:
listing, as mentions, objects constituting an image and noun phrases constituting a text which are displayed on a chatting window which displays the user utterance and the answer to the user utterance [Paragraph 0024 teaches graphical user interface, i.e., menu screens, etc., that enables users to solicit queries and to display answers/results obtained in relation to the user queries]; grouping mentions indicating a same entity among the listed mentions, and configuring the grouped mentions to an entity [Paragraph 0036 teaches syntactic relationship identifier may identify syntactic relationships in phrases and words]; and adding the entity to the conversation data as knowledge on the image [Paragraph 0035 teaches semantic relationship identifier may identify semantic relationships of recognized entities in words and phrases].
As to claim 8:
Clark discloses:
configuring relations between the grouped mentions; and adding the configured relations between the grouped mentions to the conversation data as knowledge on the image [Paragraph 0035 teaches semantic relationship identifier may determine functional dependencies between entities and other semantic relationships].
Same rationale applies to claims 10 to 14, 17, and 18, since they recite similar limitations, and are therefore, similarly rejected.
Claims 5, 6, 15, and 16 are rejected under 35 U.S.C. 103 as being unpatentable over Clark et al. (U.S. Publication No. 2016/0110357) hereinafter Clark, in view of HALL et al. (U.S. Publication No. 2020/0302019) hereinafter Hall, and further in view of Kale et al. (U.S. Publication No. 2022/0100791) hereinafter Kale.
As to claim 5:
Clark discloses all the limitations as set forth in the rejections of claim 4 above, but does not appear to expressly disclose extracting characteristic information on the image from the answer to the user utterance; and adding the extracted characteristic information to the conversation data as knowledge on the image.
Kale discloses:
extracting characteristic information on the image from the answer to the user utterance; and adding the extracted characteristic information to the conversation data as knowledge on the image [Paragraph 0023 teaches determining and associating multi-term contextual tags with images using a correspondence between user search queries, tags of the images, and user selections of the images in response to the user search queries].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the teachings of the cited references and modify the invention as taught by Clark, by extracting characteristic information on the image from the answer to the user utterance; and adding the extracted characteristic information to the conversation data as knowledge on the image, as taught by Kale [Paragraph 0023], because both applications are directed to improvements in processing search queries; by extracting characteristic information on the image from the answer to the user utterance; and adding the extracted characteristic information to the conversation data as knowledge on the image, efficiency and accuracy of search and retrieval of desired images that accurately portray a search query is increased (See Kale Para [0006]).
As to claim 6:
Clark discloses all the limitations as set forth in the rejections of claim 4 above, but does not appear to expressly disclose displaying characteristics information which is pre-labeled for the image; selecting characteristic information to reference for the answer to the user utterance from the characteristics feature information; and adding the selected characteristic information on the image to the conversation data as knowledge on the image.
Kale discloses:
displaying characteristics information which is pre-labeled for the image [Paragraph 0057 teaches providing the result digital images, that include multi-term contextual tags that match the search query; Paragraph 0059 teaches providing digital images that include tags related to one or more terms in the search query]; selecting characteristic information to reference for the answer to the user utterance from the characteristics feature information [Paragraph 0062 teaches determine which images from the selected images to associate with a multi-term contextual tag determined from the search query]; and adding the selected characteristic information on the image to the conversation data as knowledge on the image [Paragraph 0063 teaches determine multi-term contextual tag scores to be associated with the images].
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention, to combine the teachings of the cited references and modify the invention as taught by Clark, by displaying characteristics information which is pre-labeled for the image; selecting characteristic information to reference for the answer to the user utterance from the characteristics feature information; and adding the selected characteristic information on the image to the conversation data as knowledge on the image, as taught by Kale [Paragraph 0023, 0059, 0062, 0063], because both applications are directed to improvements in processing search queries; by extracting characteristic information on the image from the answer to the user utterance and adding the extracted characteristic information, efficiency and accuracy of search and retrieval of desired images that accurately portray a search query is increased (See Kale Para [0006]).
Same rationale applies to claims 15 and 16, since they recite similar limitations, and are therefore, similarly rejected.
Response to Arguments
The following is in response to arguments filed on September 11, 2025. Arguments have been carefully and respectfully considered.
Claim Rejections - 35 USC § 101
Applicant’s arguments have been carefully and respectfully considered, but are not persuasive.
In regards to claim 1, Applicant argues that “that the above-noted claimed features of independent claim 1 are not, and/or would/could not be, practically performed in the human mind and/or correspond to mental process or manual activities”.
In response to the preceding argument, Examiner respectfully disagrees, and respectfully points out that, as further described in the rejections above, the training limitation and the one or more processors are additional elements, not part of the abstract idea. However, the limitation “training, using the collected conversation data, an artificial intelligence (Al) conversation model configured to generate natural language responses to input queries by labeling the pieces of text knowledge and the images as additional information for the user utterance” is recited at a high-level of generality, with no restriction on how the result is accomplished and no description of the mechanism for accomplishing the result, and is equivalent to merely saying “applying it”, and the one or more processors and storage unit in these steps are recited at a high-level of generality (i.e., as a generic processor performing a generic computer function) such that it amounts no more than mere instructions to apply the exception using a generic computer component. Therefore, the claim is directed to an abstract idea.
In regards to claim 1, Applicant argues that “the claimed features are integrated into a practical application”.
In response to the preceding argument, Examiner respectfully submits that it is not clear, from the Applicant’s arguments, how the claimed features are integrated into a practical application. Even considering the claims as a whole, the claims as presently presented are directed to an abstract idea under the Mental Processes of abstract ideas, without significantly more. 101 Rejections are hereby sustained.
Claim Rejections - 35 USC § 103
Applicant’s arguments have been fully and respectfully considered, but are moot in view of new grounds of rejections, as necessitated by the amendments.
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 RAQUEL PEREZ-ARROYO whose telephone number is (571)272-8969. The examiner can normally be reached Monday - Friday, 8:00am - 5:30pm, Alt Friday, EST.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, Sherief Badawi can be reached at 571-272-9782. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RAQUEL PEREZ-ARROYO/Primary Examiner, Art Unit 2169
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