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
The Amendment filed 12/19/2025 has been entered. Claims 4, 10, and 17 have been cancelled. New claims 21-23 have been added. Claims 1-3, 5-9, 11-16, and 18-23 remain pending in this application.
Response to Arguments
Applicant’s arguments filed 12/19/2025 have been fully considered but are not persuasive.
With respect to the 35 U.S.C. 102 rejection, on pages 9-12, of claims 1, 3-4, 6-7, 9-10, 12, 13-14, 16-17, and 19-20, under Zhou et al. (US Patent Application Publication No. 2023/0103076), hereinafter referred to as Zhou, and to the 35 U.S.C. 103 rejection, on page 13, of claims 2, 8, and 15, under Zhou, in view of Kim et al. (US Patent Application Publication No. 2025/0007870), hereinafter referred to as Kim, and claims 5, 11, and 18 under Zhou, in view of Ekmekci et al. (US Patent Application Publication No. 2020/0184151), hereinafter referred to as Ekmekci, the Applicant asserts that Zhou fails to disclose the amended limitations “causing, prior to the user profile posting the text to the first virtual space, a portion of the question-answer pair to be displayed” and “receiving, prior to the user profile posting the text to the first virtual space and in response to displaying the portion of the question-answer pair and from the user profile, user input data representing an intent to view the question-answer pair.”
In response to the argument that Zhou fails to disclose the limitations noted above, Zhou para [0081] states "In one embodiment, the first suggested action 306 to set a document pin may be automatically generated upon detection that at least a threshold number of other users have accessed (e.g., read or viewed) the document “Pushmaster Duties” and/or at least a threshold number of other users (e.g., at least ten other users) have starred the document “Pushmaster Duties” when performing searches.” This states that the suggested actions shown in Zhou Fig. 3A could be any documents that might have met the conditions of a certain threshold number of views and/or users starring or favoriting them. This, by extension, could also apply to frequently-asked question (FAQ) documents, or to common queries themselves. This would thereby meet the conditions of the limitation of displaying a portion of a question-answer pair prior to a user posting a text to a virtual space. Zhou Fig. 3B, which illustrates the same device as in Fig. 3A, reference character 345 shows a pointer, which the user is able to utilize in order to interact with the interface and thereby can click on the suggested documents noted in Fig. 3A. This therefore discloses the conditions of the limitation of receiving user data representing an intent to view the question-answer pair prior to the user posting a text to a virtual space. Hence, the Applicant’s arguments are not persuasive.
Claim Rejections - 35 USC § 102
The following is a quotation of the appropriate paragraphs of 35 U.S.C. 102 that form the basis for the rejections under this section made in this Office action:
A person shall be entitled to a patent unless –
(a)(1) the claimed invention was patented, described in a printed publication, or in public use, on sale, or otherwise available to the public before the effective filing date of the claimed invention.
(a)(2) the claimed invention was described in a patent issued under section 151, or in an application for patent published or deemed published under section 122(b), in which the patent or application, as the case may be, names another inventor and was effectively filed before the effective filing date of the claimed invention.
Claim(s) 1, 3, 6-7, 9, 12, 13-14, 16, and 19-23 is/are rejected under 35 U.S.C. 102(a)(2) as being anticipated by Zhou et al. (US Patent Application Publication No. 2023/0103076), hereinafter referred to as Zhou.
Regarding claim 1, Zhou discloses a system comprising: one or more processors; and one or more non-transitory computer-readable media storing computer-executable instructions that, when executed, cause the one or more processors to perform operations comprising: receiving, from a user profile inputting text to a first virtual space ("The information displayed or referenced (e.g., via reference to a linked electronic document) within an automated response to a user question may be determined based on access rights to linked documents and the number of electronic interactions between users of the permissions-aware search and knowledge management system," Zhou para [0031] implies the usage of user profiles/accounts), first data indicative of the text being input to a message input pane associated with the first virtual space of a communication platform (Zhou Fig. 7E reference character 742 and 744);
inputting the text into a machine-learning model trained to identify a key word or a key phrase within the text from a list of one or more key words or phrases ("The first question may be identified due to the presence of keywords (e.g., “where”) or symbols (e.g., a question mark). The first question may be identified from a portion of one of the first set of electronic messages as a factual question using a machine learning model that was trained by providing a test set of questions," Zhou para [0141]);
receiving, from the machine-learning model, second data representative of one or more key words or phrases included in the text (Zhou Fig. 7E reference character 746, if 744 may be performed through a machine learning model, then it would be inherent that 746 would be the output of the machine learning model);
determining, based on the one or more key words or phrases, a question-answer pair associated with a second virtual space of the communication platform that is different than the first virtual space and that is associated with the first virtual space (Zhou Fig. 7E reference character 752, shows that it is added to a database, which could be considered associated with a second virtual space);
causing, prior to the user profile posting the text to the first virtual space, ("In one embodiment, the first suggested action 306 to set a document pin may be automatically generated upon detection that at least a threshold number of other users have accessed (e.g., read or viewed) the document “Pushmaster Duties” and/or at least a threshold number of other users (e.g., at least ten other users) have starred the document “Pushmaster Duties” when performing searches," Zhou para [0081], the first suggested action could therefore be a FAQ document with question-answer pairs that a threshold number of users have accessed) a portion of the question-answer pair to be displayed via a user interface associated with the user profile (Zhou Fig. 7G reference character 788, 794, and 798, 798 shows that only the answer is displayed, i.e. a portion of the question-answer pair);
receiving, prior to the user profile posting the text to the first virtual space and ("In one embodiment, the first suggested action 306 to set a document pin may be automatically generated upon detection that at least a threshold number of other users have accessed (e.g., read or viewed) the document “Pushmaster Duties” and/or at least a threshold number of other users (e.g., at least ten other users) have starred the document “Pushmaster Duties” when performing searches," Zhou para [0081], the first suggested action could therefore be a FAQ document with question-answer pairs that a threshold number of users have accessed) in response to displaying the portion of the question-answer pair and from the user profile, user input data representing an intent to view the question-answer pair ("In some cases, a user may explicitly request that the enterprise knowledge assistant provide an automated response to their question, such as question 626 in FIG. 6B," Zhou para [0033] and Zhou Fig. 3B [same device as in Fig. 3A] reference character 345 shows a pointer, which the user utilizes to interact with the interface and thereby can click on the suggested documents noted in Fig. 3A);
and causing, based on the user input data, the second virtual space to be displayed, wherein the second virtual space includes the question-answer pair ("and in response the enterprise knowledge assistant may identify an extracted question and answer pair from the frequently asked questions database, display the answer for the question and answer pair, and display any surrounding context for the answer if the user's question is classified as being semantically equivalent to an extracted question stored within the frequently asked questions database," Zhou para [0033]).
Regarding claim 3, Zhou discloses all of the limitations of claim 1. Zhou further discloses wherein the list of one or more key words or phrases is determined based on one or more frequently asked questions associated with the first virtual space, wherein the one or more frequently asked questions are determined based on at least one of: a question being posted to the first virtual space a first threshold number of times, the question being posted to the first virtual space a second threshold number of times within a threshold period of time, or the question being assigned as a frequently asked question by the user profile associated with the first virtual space (Zhou Fig. 8A reference characters 812 and 814, here the threshold value is <1 because the question-answer pair is added to the database if it does not currently exist within the database).
Regarding claim 6, Zhou discloses all of the limitations of claim 1. Zhou further discloses wherein the text is a question that is associated with the question-answer pair (Zhou Fig. 7E reference character 744 and 752).
Regarding claim 7, Zhou discloses one or more non-transitory computer-readable media storing instructions executable by one or more processors, wherein the instructions, when executed, cause the one or more processors to perform operations comprising: receiving, from a user profile inputting text to a first virtual space ("The information displayed or referenced (e.g., via reference to a linked electronic document) within an automated response to a user question may be determined based on access rights to linked documents and the number of electronic interactions between users of the permissions-aware search and knowledge management system," Zhou para [0031] implies the usage of user profiles/accounts), first data indicative of the text being input to a message input pane associated with a first virtual space associated with a communication platform (Zhou Fig. 7E reference character 742 and 744);
inputting the text into a machine-learning model trained to identify a key word or a phrase within the text from a list of one or more key words or phrases ("The first question may be identified due to the presence of keywords (e.g., “where”) or symbols (e.g., a question mark). The first question may be identified from a portion of one of the first set of electronic messages as a factual question using a machine learning model that was trained by providing a test set of questions," Zhou para [0141]);
receiving, from the machine-learning model, second data representative of one or more key words or phrases included in the text (Zhou Fig. 7E reference character 746, if 744 may be performed through a machine learning model, then it would be inherent that 746 would be the output of the machine learning model);
determining, prior to the user profile posting the text to the first virtual space and ("In one embodiment, the first suggested action 306 to set a document pin may be automatically generated upon detection that at least a threshold number of other users have accessed (e.g., read or viewed) the document “Pushmaster Duties” and/or at least a threshold number of other users (e.g., at least ten other users) have starred the document “Pushmaster Duties” when performing searches," Zhou para [0081], the first suggested action could therefore be a FAQ document with question-answer pairs that a threshold number of users have accessed) based at least in part on the one or more key words or phrases, a question-answer pair associated with a second virtual space associated with the communication platform that is different than the first virtual space and that is associated with the first virtual space (Zhou Fig. 7E reference character 752, shows that it is added to a database, which could be considered associated with a second virtual space);
receiving, prior to the user profile posting the text to the first virtual space and ("In one embodiment, the first suggested action 306 to set a document pin may be automatically generated upon detection that at least a threshold number of other users have accessed (e.g., read or viewed) the document “Pushmaster Duties” and/or at least a threshold number of other users (e.g., at least ten other users) have starred the document “Pushmaster Duties” when performing searches," Zhou para [0081], the first suggested action could therefore be a FAQ document with question-answer pairs that a threshold number of users have accessed) based at least in part on the question-answer pair and from the user profile, user input data representing an intent to view the question-answer pair ("In some cases, a user may explicitly request that the enterprise knowledge assistant provide an automated response to their question, such as question 626 in FIG. 6B," Zhou para [0033] and Zhou Fig. 3B [same device as in Fig. 3A] reference character 345 shows a pointer, which the user utilizes to interact with the interface and thereby can click on the suggested documents noted in Fig. 3A);
and causing, based at least in part on the user input data, the second virtual space to be displayed, wherein the second virtual space includes the question-answer pair ("and in response the enterprise knowledge assistant may identify an extracted question and answer pair from the frequently asked questions database, display the answer for the question and answer pair, and display any surrounding context for the answer if the user's question is classified as being semantically equivalent to an extracted question stored within the frequently asked questions database," Zhou para [0033]).
Regarding claim 9, Zhou discloses all of the limitations of claim 7. Zhou further discloses wherein the list of one or more key words or phrases is determined based at least in part on one or more frequently asked questions associated with the first virtual space, wherein the one or more frequently asked questions are determined based at least in part on at least one of: a question being posted to the first virtual space a first threshold number of times, the question being posted to the first virtual space a second threshold number of times within a threshold period of time, or the question being assigned as a frequently asked question by the user profile associated with the first virtual space (Zhou Fig. 8A reference characters 812 and 814, here the threshold value is <1 because the question-answer pair is added to the database if it does not currently exist within the database).
Regarding claim 12, Zhou discloses all of the limitations of claim 7. Zhou further discloses wherein the text is a question that is associated with the question-answer pair (Zhou Fig. 7E reference character 744 and 752).
Regarding claim 13, Zhou discloses all of the limitations of claim 7. Zhou further discloses wherein receiving the user input data is based at least in part on: causing a portion of the question-answer pair to be displayed via a user interface associated with the user profile (Zhou Fig. 7G reference character 788 and 798 and Zhou Fig. 6A shows an example user interface).
As to claim 14, method claim 14 and computer-readable medium (CRM) claim 7 are related as CRM and method of using same, with each claimed element’s function corresponding to the CRM step. Accordingly, claim 14 is similarly rejected under the same rationale as applied above with respect to the CRM claim.
As to claim 16, method claim 16 and CRM claim 9 are related as CRM and method of using same, with each claimed element’s function corresponding to the CRM step. Accordingly, claim 16 is similarly rejected under the same rationale as applied above with respect to the CRM claim.
As to claim 19, method claim 19 and CRM claim 12 are related as CRM and method of using same, with each claimed element’s function corresponding to the CRM step. Accordingly, claim 19 is similarly rejected under the same rationale as applied above with respect to the CRM claim.
As to claim 20, method claim 20 and CRM claim 13 are related as CRM and method of using same, with each claimed element’s function corresponding to the CRM step. Accordingly, claim 20 is similarly rejected under the same rationale as applied above with respect to the CRM claim.
Regarding claim 21, Zhou discloses all of the limitations of claim 20. Zhou further discloses wherein the portion of the question-answer pair is displayed on an overlay interface (Zhou Fig. 6D reference characters 656-662 show an overlay display).
Regarding claim 22, Zhou discloses all of the limitations of claim 1. Zhou further discloses wherein the portion of the question-answer pair is displayed on an overlay interface (Zhou Fig. 6D reference characters 656-662 show an overlay display).
Regarding claim 23, Zhou discloses all of the limitations of claim 13. Zhou further discloses wherein the portion of the question-answer pair is displayed on an overlay interface (Zhou Fig. 6D reference characters 656-662 show an overlay display).
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(s) 2, 8, and 15 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou, in view of Kim et al. (US Patent Application Publication No. 2025/0007870), hereinafter referred to as Kim.
Regarding claim 2, Zhou discloses all of the limitations of claim 1. Zhou further discloses wherein the machine-learning model is a first machine-learning model, wherein the list of one or more key words or phrases is generated based on: identifying, from the second virtual space, one or more frequently asked questions ("Machine learning techniques may be used to determine whether the first question is semantically equivalent to another question stored within the database," Zhou para [0144]);
inputting the one or more frequently asked questions into a machine-learning model that is different than the first machine-learning model ("The first question may be identified due to the presence of keywords (e.g., “where”) or symbols (e.g., a question mark). The first question may be identified from a portion of one of the first set of electronic messages as a factual question using a machine learning model that was trained by providing a test set of questions," Zhou para [0141]);
and receiving, from the machine-learning model, the list of one or more key words or phrases (Zhou Fig. 7E reference character 746, if 744 may be performed through a machine learning model, then it would be inherent that 746 would be the output of the machine learning model).
However, Zhou fails to disclose the use of a second machine-learning model. Kim teaches that it is known to have a system configured to have multiple trained models.
Kim teaches a second machine-learning model ("The following examples use multiple models of output engines in order to provide content to the user. Specifically, the system 3200 includes a generative output engine 3212 and also a content model 3214. Each of these models of output engines may be adapted for different purposes and may be trained using different training sets to help adapt each engine or model to perform in accordance with the system," Kim para [0376]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Zhou’s method of using a machine learning model to answer and display a question-answer pair by including Kim’s method of utilizing a system configured to have multiple trained models. This modification of Zhou, in view of Kim, such that the system of Zhou incorporated multiple trained models (i.e. a first and a second model), each used to identify key words and phrases from an inputted question, is taught and suggested by the prior art, and it would have been obvious to one of ordinary skill in the art.
Regarding claim 8, Zhou teaches all of the limitations of claim 7. Zhou further discloses wherein the machine-learning model is a first machine-learning model, wherein the list of one or more key words or phrases is generated based at least in part on: identifying, from the second virtual space, one or more frequently asked questions ("Machine learning techniques may be used to determine whether the first question is semantically equivalent to another question stored within the database," Zhou para [0144]);
inputting the one or more frequently asked questions into a machine-learning model that is different than the first machine-learning model ("The first question may be identified due to the presence of keywords (e.g., “where”) or symbols (e.g., a question mark). The first question may be identified from a portion of one of the first set of electronic messages as a factual question using a machine learning model that was trained by providing a test set of questions," Zhou para [0141]);
and receiving, from the machine-learning model, the list of one or more key words or phrases (Zhou Fig. 7E reference character 746, if 744 may be performed through a machine learning model, then it would be inherent that 746 would be the output of the machine learning model).
However, Zhou fails to disclose the use of a second machine-learning model.
Kim teaches a second machine-learning model ("The following examples use multiple models of output engines in order to provide content to the user. Specifically, the system 3200 includes a generative output engine 3212 and also a content model 3214. Each of these models of output engines may be adapted for different purposes and may be trained using different training sets to help adapt each engine or model to perform in accordance with the system," Kim para [0376]).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Zhou’s method of using a machine learning model to answer and display a question-answer pair by including Kim’s method of utilizing a system configured to have multiple trained models. This modification of Zhou, in view of Kim, such that the system of Zhou incorporated multiple trained models (i.e. a first and a second model), each used to identify key words and phrases from an inputted question, is taught and suggested by the prior art, and it would have been obvious to one of ordinary skill in the art.
As to claim 15, method claim 15 and CRM claim 8 are related as CRM and method of using same, with each claimed element’s function corresponding to the CRM step. Accordingly, claim 15 is similarly rejected under the same rationale as applied above with respect to the CRM claim.
Claim(s) 5, 11, and 18 is/are rejected under 35 U.S.C. 103 as being unpatentable over Zhou, in view of Ekmekci et al. (US Patent Application Publication No. 2020/0184151), hereinafter referred to as Ekmekci.
Regarding claim 5, Zhou discloses all of the limitations of claim 1. Zhou further discloses wherein the list of one or more key words or phrases is a first list of one or more key words or phrases, the operations further comprising: identifying a third virtual space within the communication platform (Zhou Fig. 6A shows multiple channels).
However, Zhou fails to disclose identifying a second list of one or more key words or phrases; and determining that the second list of one or more key words or phrases is different than the first list of one or more key phrases. Ekmekci teaches a method for identifying an event from data.
Ekmekci teaches identifying a second list of one or more key words or phrases (Ekmekci Fig. 5 reference character 506);
and determining that the second list of one or more key words or phrases is different than the first list of one or more key phrases (Ekmekci Fig. 5 reference character 506).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Zhou’s method of using a machine learning model to answer and display a question-answer pair by including Ekmekci’s method of identifying and comparing a second keyword list with a first list. More key word lists, and ensuring that these key words lists are different, allows for more variation and adaptability in what the machine learning model classifies or identifies as a key word or a question. This increases accuracy and efficacy of the model and its use. This inclusion would have been obvious to one of ordinary skill in the art.
Regarding claim 11, Zhou discloses all of the limitations of claim 7. Zhou further discloses wherein the list of one or more key words or phrases is a first list of one or more key words or phrases, the operations further comprising: identifying a third virtual space within the communication platform (Zhou Fig. 6A shows multiple channels).
However, Zhou fails to disclose identifying a second list of one or more key words or phrases; and determining that the second list of one or more key words or phrases is different than the first list of one or more key phrases.
Ekmekci teaches identifying a second list of one or more key words or phrases (Ekmekci Fig. 5 reference character 506);
and determining that the second list of one or more key words or phrases is different than the first list of one or more key phrases (Ekmekci Fig. 5 reference character 506).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to have combined Zhou’s method of using a machine learning model to answer and display a question-answer pair by including Ekmekci’s method of identifying and comparing a second keyword list with a first list. More key word lists, and ensuring that these key words lists are different, allows for more variation and adaptability in what the machine learning model classifies or identifies as a key word or a question. This increases accuracy and efficacy of the model and its use. This inclusion would have been obvious to one of ordinary skill in the art.
As to claim 18, method claim 18 and CRM claim 11 are related as CRM and method of using same, with each claimed element’s function corresponding to the CRM step. Accordingly, claim 18 is similarly rejected under the same rationale as applied above with respect to the CRM claim.
Conclusion
THIS ACTION IS MADE FINAL. 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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/ADAM MICHAEL WEAVER/Examiner, Art Unit 2658
/RICHEMOND DORVIL/Supervisory Patent Examiner, Art Unit 2658
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