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 .
Double Patenting
The nonstatutory double patenting rejection is based on a judicially created doctrine grounded in public policy (a policy reflected in the statute) so as to prevent the unjustified or improper timewise extension of the “right to exclude” granted by a patent and to prevent possible harassment by multiple assignees. A nonstatutory double patenting rejection is appropriate where the conflicting claims are not identical, but at least one examined application claim is not patentably distinct from the reference claim(s) because the examined application claim is either anticipated by, or would have been obvious over, the reference claim(s). See, e.g., In re Berg, 140 F.3d 1428, 46 USPQ2d 1226 (Fed. Cir. 1998); In re Goodman, 11 F.3d 1046, 29 USPQ2d 2010 (Fed. Cir. 1993); In re Longi, 759 F.2d 887, 225 USPQ 645 (Fed. Cir. 1985); In re Van Ornum, 686 F.2d 937, 214 USPQ 761 (CCPA 1982); In re Vogel, 422 F.2d 438, 164 USPQ 619 (CCPA 1970); In re Thorington, 418 F.2d 528, 163 USPQ 644 (CCPA 1969).
A timely filed terminal disclaimer in compliance with 37 CFR 1.321(c) or 1.321(d) may be used to overcome an actual or provisional rejection based on nonstatutory double patenting provided the reference application or patent either is shown to be commonly owned with the examined application, or claims an invention made as a result of activities undertaken within the scope of a joint research agreement. See MPEP § 717.02 for applications subject to examination under the first inventor to file provisions of the AIA as explained in MPEP § 2159. See MPEP §§ 706.02(l)(1) - 706.02(l)(3) for applications not subject to examination under the first inventor to file provisions of the AIA . A terminal disclaimer must be signed in compliance with 37 CFR 1.321(b).
The filing of a terminal disclaimer by itself is not a complete reply to a nonstatutory double patenting (NSDP) rejection. A complete reply requires that the terminal disclaimer be accompanied by a reply requesting reconsideration of the prior Office action. Even where the NSDP rejection is provisional the reply must be complete. See MPEP § 804, subsection I.B.1. For a reply to a non-final Office action, see 37 CFR 1.111(a). For a reply to final Office action, see 37 CFR 1.113(c). A request for reconsideration while not provided for in 37 CFR 1.113(c) may be filed after final for consideration. See MPEP §§ 706.07(e) and 714.13.
The USPTO Internet website contains terminal disclaimer forms which may be used. Please visit www.uspto.gov/patent/patents-forms. The filing date of the application in which the form is filed determines what form (e.g., PTO/SB/25, PTO/SB/26, PTO/AIA /25, or PTO/AIA /26) should be used. A web-based eTerminal Disclaimer may be filled out completely online using web-screens. An eTerminal Disclaimer that meets all requirements is auto-processed and approved immediately upon submission. For more information about eTerminal Disclaimers, refer to www.uspto.gov/patents/process/file/efs/guidance/eTD-info-I.jsp.
Claims 1-20 are rejected on the ground of nonstatutory anticipatory-type double patenting over Claims 1-20 of U.S. Patent No. 12255749 since the claims, if allowed, would improperly extend the “right to exclude” already granted in the patent.
The subject matter claimed in the instant application is fully disclosed in the patent and is covered by the patent since the patent and the application are claiming common subject matter, as follows:
Regarding Claim 1:
Instant Application 19081179
U.S. Patent No. 12255749
1. A method for facilitating a collaborative meeting in near real-time, the method comprising: monitoring activities of participants of the collaborative meeting in near real-time;
1. A method for facilitating a collaborative meeting, the method comprising:
monitoring activities of participants of the collaborative meeting;
extracting insights from meeting contents shared by the participants in near real-time, wherein the insights are extracted using a generative machine learning model;
extracting insights from meeting contents shared by the participants, wherein the insights are extracted using a generative machine learning model;
generating a structured summary log based on the insights associated with the collaborative meeting, wherein the structured summary log is generated using the generative machine learning model;
generating a structured summary log based on the selected data from the insights associated with the collaborative meeting, wherein the structured summary log is generated using the generative machine learning model;
presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting; and generating one or more customized meeting summaries for one or more participants after the collaborative meeting,
presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting; and generating one or more customized meeting summaries for one or more participants after the collaborative meeting,
wherein the one or more customized meeting summaries are generated using the generative machine learning model.
wherein the one or more customized meeting summaries are generated using the generative machine learning model.
Regarding Claim 10:
Instant Application 19081179
U.S. Patent No. 12255749
10. A computing device for facilitating a collaborative meeting, the computing device comprising: a processor; and a memory having a plurality of instructions stored thereon that, when executed by the processor, causes the computing device to: monitor activities of participants of the collaborative meeting;
10. A computing device for facilitating a collaborative meeting, the computing device comprising: a processor; and a memory having a plurality of instructions stored thereon that, when executed by the processor, causes the computing device to: monitor activities of participants of the collaborative meeting;
extract insights from meeting contents shared by the participants, wherein the insights are extracted using a generative machine learning model;
extract insights from meeting contents shared by the participants, wherein the insights are extracted using a generative machine learning model;
select data from the insights that is deemed important based on engagement and interests of the participants;
select data from the insights that is deemed important based on engagement and interests of the participants;
generate a structured summary log based on the selected data from the insights associated with the collaborative meeting, wherein the structured summary log is generated using the generative machine learning model; present the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting;
generate a structured summary log based on the selected data from the insights associated with the collaborative meeting, wherein the structured summary log is generated using the generative machine learning model; present the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting;
and generate one or more customized meeting summaries one or more of the participants after the collaborative meeting, wherein the one or more customized meeting summaries are generated using the generative machine learning model.
and generate one or more customized meeting summaries one or more of the participants after the collaborative meeting, wherein the one or more customized meeting summaries are generated using the generative machine learning model.
Regarding Claim 15:
Instant Application 19081179
U.S. Patent No. 12255749
15. A non-transitory computer-readable medium storing instructions for facilitating a collaborative meeting, the instructions when executed by one or more processors of a computing device, cause the computing device to perform a method comprising: monitoring activities of participants of the collaborative meeting;
15. A non-transitory computer-readable medium storing instructions for facilitating a collaborative meeting, the instructions when executed by one or more processors of a computing device, cause the computing device to perform a method comprising: monitoring activities of participants of the collaborative meeting;
extracting insights from meeting contents shared by the participants; generating a structured summary log based on the insights associated with the collaborative meeting;
extracting insights from meeting contents shared by the participants; generating a structured summary log based on the selected data from the insights associated with the collaborative meeting;
presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting;
presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting;
interacting with participants during the collaborative meeting;
interacting with participants during the collaborative meeting;
and generating a customized meeting summary for each of the participants after the collaborative meeting.
and generating a customized meeting summary for each of the participants after the collaborative meeting.
Regarding Claims 2-9, 11-14, and 16-20, Claims 2-9, 11-14, and 16-20 are rejected on the ground of nonstatutory double patenting as being unpatentable over Claims 2-9, 11-14, and 16-20 of U.S. Patent No. 12255749 using similar reasoning.
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 1-9 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 pre-AIA the applicant regards as the invention.
Regarding Claim 1, the term "near real-time" in Claim 1 is a relative term which renders the claim indefinite. The term "near real-time" is not defined by the claim, the specification does not provide a standard for ascertaining the requisite degree, and one of ordinary skill in the art would not be reasonably apprised of the scope of the invention.
Regarding Claims 2-9, Dependent Claims 2-9 are rejected under 35 U.S.C. 112(b) for inheriting the deficiencies of Claim 1.
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.
Claims 15, 17, and 19-20 are rejected under 35 U.S.C. 102(a) (1) as being anticipated by Daredia et al (“Daredia”, US 20200403817).
Regarding Claim 15, Daredia teaches a non-transitory computer-readable medium storing instructions for facilitating a collaborative meeting, the instructions when executed by one or more processors of a computing device, cause the computing device to perform a method comprising:
monitoring activities of participants of the collaborative meeting (par 52; par 67);
extracting insights from meeting contents shared by the participants (par 52; par 67; The insights are the information extracted from the audio.);
generating a structured summary log based on the insights associated with the collaborative meeting (par 67-69; The insights are the information extracted from the audio. The structured summary log is the summary 310.);
presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting (par 67-69; Fig. 4A, elements {400, 402, 430, 432}, par 98-99; The insights are the information extracted from the audio. The structured summary log is the summary 310. The collaborative canvas is the meeting interface.);
interacting with participants during the collaborative meeting (par 46);
and generating a customized meeting summary for each of the participants after the collaborative meeting (par 103; The customized meeting summary is the text transcript.).
Regarding Claim 17, Daredia teaches the non-transitory computer-readable medium of claim 15.
Daredia further teaches wherein the structured summary log captures the insights that represent the meeting contents that are deemed important to the participants (par 123-129; par 67-69; The insights are the information extracted from the audio. The structured summary log is the summary 310.).
Regarding Claim 19, Daredia teaches the non-transitory computer-readable medium of claim 17.
Daredia further teaches wherein to select data from the insights that is deemed important based on
engagement and interests of the participants includes to monitor a density of dialog,
a number of participants speaking or texting (par 123-129; par 67-69; The insights are the information extracted from the audio. The structured summary log is the summary 310.),
and/or a number of hand-raised or emojis in a chat box when a particular meeting content is shared in the collaborative meeting.
Regarding Claim 20, Daredia teaches the non-transitory computer-readable medium of claim 15.
Daredia further teaches wherein the method further comprises:
receiving, from a participant to the collaborative meeting, a change to content in the collaborative canvas (Fig. 4E, element 438, par 107; The change to content is rejecting the content in the meeting summary.);
accepting the change to the content in the collaborative canvas (Fig. 4E, element 438, par 107; Fig. 4E, element 438, par 107; The change to content is rejecting the content in the meeting summary. Accepting the change is clicking on the “X”.);
and resharing the collaborative canvas with the participants (Fig. 4E, element 438, par 107).
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.
The test for obviousness is not whether the features of a secondary reference may be bodily incorporated into the structure of the primary reference; nor is it that the claimed invention must be expressly suggested in any one or all of the references. Rather, the test is what the combined teachings of the references would have suggested to those of ordinary skill in the art. See In re Keller, 642 F.2d 413, 208 USPQ 871 (CCPA 1981).
Claims 1, 5, and 7-9 are rejected under 35 U.S.C. 103 as being unpatentable over Daredia in view of Tadesse et al (“Tadesse”, US 20220385758).
Regarding Claim 1, Daredia teaches a method for facilitating a collaborative meeting in near real-time, the method comprising:
monitoring activities of participants of the collaborative meeting in near real-time (par 52; par 67);
extracting insights from meeting contents shared by the participants in near real-time (par 52; par 67; The insights are the information extracted from the audio.),
wherein the insights are extracted using a machine learning model (par 67);
generating a structured summary log based on the insights associated with the collaborative meeting (par 67-69; The insights are the information extracted from the audio. The structured summary log is the summary 310.),
wherein the structured summary log is generated using the machine learning model (par 67-69; The insights are the information extracted from the audio. The structured summary log is the summary 310.);
presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting (par 67-69; Fig. 4A, elements {400, 402, 430, 432}, par 98-99; The insights are the information extracted from the audio. The structured summary log is the summary 310. The collaborative canvas is the meeting interface.);
and generating one or more customized meeting summaries for one or more participants after the collaborative meeting (par 103; The customized meeting summary is the text transcript.),
Daredia does not explicitly teach generative machine learning model; wherein the one or more customized meeting summaries are generated using the generative machine learning model.
Tadesse teaches generative machine learning model (par 44);
wherein the one or more customized meeting summaries are generated using the generative machine learning model (par 44).
It would have been obvious to one of ordinary skill in the art before the effective filing date of the claimed invention to modify the invention of Daredia with the generative machine learning of Tadesse because generative machine learning models provide data augmentation, cost reduction, and improved anomaly detection.
Regarding Claim 5, Daredia and Tadesse teach the method of claim 1.
Daredia further teaches wherein the structured summary log captures the insights that represent the meeting contents that are deemed important to the participants (par 123-129; par 67-69; The insights are the information extracted from the audio. The structured summary log is the summary 310.).
Regarding Claim 7, Daredia and Tadesse teach the method of claim 5.
Daredia further teaches wherein generating the structured summary log includes determining information from the meeting contents as important based on
engagement and interests of the participants by monitoring a density of dialog,
a number of participants speaking or texting (par 123-129; par 67-69; The insights are the information extracted from the audio. The structured summary log is the summary 310.),
and/or a number of hand-raised or emojis in a chat box when a particular meeting content is shared in the collaborative meeting.
Regarding Claim 8, Daredia and Tadesse teach the method of claim 1.
Daredia teaches further comprising receiving, from a participant to the collaborative meeting, a change to content in the collaborative canvas (Fig. 4E, element 438, par 107; The change to content is rejecting the content in the meeting summary.).
Regarding Claim 9, Daredia and Tadesse teach the method of claim 8.
Daredia teaches further comprising: accepting the change to the content in the collaborative canvas (Fig. 4E, element 438, par 107; Fig. 4E, element 438, par 107; The change to content is rejecting the content in the meeting summary. Accepting the change is clicking on the “X”.);
and resharing the collaborative canvas with the participants (Fig. 4E, element 438, par 107; Fig. 4E, element 438, par 107).
Allowable Subject Matter
Claims 2-4 and 6 would be allowable if rewritten to overcome the rejection(s) under 35 U.S.C. 112(b) or 35 U.S.C. 112 (pre-AIA ), 2nd paragraph, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
Claims 10-14 would be allowable if rewritten to overcome the rejection under double patenting, set forth in this Office action.
Claims 16 and 18 would be allowable if rewritten to overcome the rejection under double patenting, set forth in this Office action and to include all of the limitations of the base claim and any intervening claims.
The following is a statement of reasons for the indication of allowable subject matter:
In interpreting the currently amended claims, in light of the specification, the Examiner finds the claimed invention to be patentably distinct from the prior art of record.
Regarding Claim 2, the closest prior art of record Daredia et al (“Daredia”, US 20200403817) in view of Tadesse et al (“Tadesse”, US 20220385758) does not teach a method for facilitating a collaborative meeting in near real-time, the method comprising: monitoring activities of participants of the collaborative meeting in near real-time; extracting insights from meeting contents shared by the participants in near real-time, wherein the insights are extracted using a generative machine learning model; generating a structured summary log based on the insights associated with the collaborative meeting, wherein the structured summary log is generated using the generative machine learning model; presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting; and generating one or more customized meeting summaries for one or more participants after the collaborative meeting, wherein the one or more customized meeting summaries are generated using the generative machine learning model; wherein the meeting contents include voice of the participants, text transcript of speech of participants, text chat messages, links and documents, and presentation materials shared by the participants during the collaborative meeting.
Particularly, after a thorough search, no reference was found that teaches or could be reasonably combined with Daredia and Tadesse to teach wherein the meeting contents include voice of the participants, text transcript of speech of participants, text chat messages, links and documents, and presentation materials shared by the participants during the collaborative meeting. Thus, the claim is novel and nonobvious.
Regarding Claim 3, the closest prior art of record Daredia in view of Tadesse does not teach a method for facilitating a collaborative meeting in near real-time, the method comprising: monitoring activities of participants of the collaborative meeting in near real-time; extracting insights from meeting contents shared by the participants in near real-time, wherein the insights are extracted using a generative machine learning model; generating a structured summary log based on the insights associated with the collaborative meeting, wherein the structured summary log is generated using the generative machine learning model; presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting; and generating one or more customized meeting summaries for one or more participants after the collaborative meeting, wherein the one or more customized meeting summaries are generated using the generative machine learning model; wherein the insights include key points, action items, question-and-answer (QnA) pairs, contents from links and documents, and screenshots of presentation materials.
Particularly, after a thorough search, no reference was found that teaches or could be reasonably combined with Daredia and Tadesse to teach wherein the meeting contents include voice of the participants, text transcript of speech of participants, text chat messages, links and documents, and presentation materials shared by the participants during the collaborative meeting. Thus, the claim is novel and nonobvious.
Regarding Claim 4, the closest prior art of record Daredia in view of Tadesse does not teach a method for facilitating a collaborative meeting in near real-time, the method comprising: monitoring activities of participants of the collaborative meeting in near real-time; extracting insights from meeting contents shared by the participants in near real-time, wherein the insights are extracted using a generative machine learning model; generating a structured summary log based on the insights associated with the collaborative meeting, wherein the structured summary log is generated using the generative machine learning model; presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting; and generating one or more customized meeting summaries for one or more participants after the collaborative meeting, wherein the one or more customized meeting summaries are generated using the generative machine learning model; wherein generating the structured summary log based on the insights associated with the collaborative meeting comprises generating the structured summary log every determined time period or predetermined number of contents during the collaborative meeting.
Particularly, after a thorough search, no reference was found that teaches or could be reasonably combined with Daredia and Tadesse to teach wherein generating the structured summary log based on the insights associated with the collaborative meeting comprises generating the structured summary log every determined time period or predetermined number of contents during the collaborative meeting. Thus, the claim is novel and nonobvious.
Regarding Claim 6, the closest prior art of record Daredia in view of Tadesse does not teach a method for facilitating a collaborative meeting in near real-time, the method comprising: monitoring activities of participants of the collaborative meeting in near real-time; extracting insights from meeting contents shared by the participants in near real-time, wherein the insights are extracted using a generative machine learning model; generating a structured summary log based on the insights associated with the collaborative meeting, wherein the structured summary log is generated using the generative machine learning model; presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting; and generating one or more customized meeting summaries for one or more participants after the collaborative meeting, wherein the one or more customized meeting summaries are generated using the generative machine learning model; wherein the structured summary log captures the insights that represent the meeting contents that are deemed important to the participants; wherein generating the structured summary log includes determining information from the meeting contents as important based on engagement and interests of the participants by listening for sentiment analysis to determine if the participants have a strong reaction.
Particularly, after a thorough search, no reference was found that teaches or could be reasonably combined with Daredia and Tadesse to teach wherein the structured summary log captures the insights that represent the meeting contents that are deemed important to the participants; wherein generating the structured summary log includes determining information from the meeting contents as important based on engagement and interests of the participants by listening for sentiment analysis to determine if the participants have a strong reaction. Thus, the claim is novel and nonobvious.
Regarding Claims 10-14, the closest prior art of record Daredia in view of Tadesse does not teach a computing device for facilitating a collaborative meeting, the computing device comprising: a processor; and a memory having a plurality of instructions stored thereon that, when executed by the processor, causes the computing device to: monitor activities of participants of the collaborative meeting; extract insights from meeting contents shared by the participants, wherein the insights are extracted using a generative machine learning model; select data from the insights that is deemed important based on engagement and interests of the participants; generate a structured summary log based on the selected data from the insights associated with the collaborative meeting, wherein the structured summary log is generated using the generative machine learning model; present the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting; and generate one or more customized meeting summaries one or more of the participants after the collaborative meeting, wherein the one or more customized meeting summaries are generated using the generative machine learning model.
Particularly, after a thorough search, no reference was found that teaches or could be reasonably combined with Daredia and Tadesse to teach select data from the insights that is deemed important based on engagement and interests of the participants; generate a structured summary log based on the selected data from the insights associated with the collaborative meeting, wherein the structured summary log is generated using the generative machine learning model; present the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting. Thus, the claims are novel and nonobvious.
Regarding Claim 16, the closest prior art of record Daredia does not teach a non-transitory computer-readable medium storing instructions for facilitating a collaborative meeting, the instructions when executed by one or more processors of a computing device, cause the computing device to perform a method comprising: monitoring activities of participants of the collaborative meeting; extracting insights from meeting contents shared by the participants; generating a structured summary log based on the insights associated with the collaborative meeting; presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting; interacting with participants during the collaborative meeting; and generating a customized meeting summary for each of the participants after the collaborative meeting; wherein the meeting contents include voice of the participants, text transcript of speech of participants, text chat messages, links and documents, and presentation materials shared by the participants during the collaborative meeting, and the insights include key points, action items, question-and-answer (QnA) pairs, contents from links and documents, and screenshots of presentation materials.
Particularly, after a thorough search, no reference was found that teaches or could be reasonably combined with Daredia to teach wherein the meeting contents include voice of the participants, text transcript of speech of participants, text chat messages, links and documents, and presentation materials shared by the participants during the collaborative meeting, and the insights include key points, action items, question-and-answer (QnA) pairs, contents from links and documents, and screenshots of presentation materials. Thus, the claim is novel and nonobvious.
Regarding Claim 18, the closest prior art of record Daredia does not teach a non-transitory computer-readable medium storing instructions for facilitating a collaborative meeting, the instructions when executed by one or more processors of a computing device, cause the computing device to perform a method comprising: monitoring activities of participants of the collaborative meeting; extracting insights from meeting contents shared by the participants; generating a structured summary log based on the insights associated with the collaborative meeting; presenting the structured summary log in a collaborative canvas accessible by the participants during the collaborative meeting; interacting with participants during the collaborative meeting; and generating a customized meeting summary for each of the participants after the collaborative meeting; wherein generating the structured summary log includes to determine information from the meeting contents as important based on engagement and interests of the participants by listening for sentiment analysis to determine if the participants have a strong reaction.
Particularly, after a thorough search, no reference was found that teaches or could be reasonably combined with Daredia to teach wherein generating the structured summary log includes to determine information from the meeting contents as important based on engagement and interests of the participants by listening for sentiment analysis to determine if the participants have a strong reaction. Thus, the claim is novel and nonobvious.
Conclusion
The prior art made of record and not relied upon is considered pertinent to applicant's disclosure:
Manda et al (US 20230153641), Abstract - An application instance that includes one or more machine learning models receives, from a subscriber computing system, a document comprising unstructured data. Based on the unstructured data, the application instance generates an optimized model input that includes a plurality of parsed document sections. For each parsed document section, the application instance generates an output set by performing, by a machine learning model, at least one key information extraction operation. The machine learning model transmits the output in structured form to a target application operated or hosted at least in part by a subscriber entity associated with the subscriber computing system.
Mahmoud (US 20190384813), Abstract - One embodiment of the present invention sets forth a technique for generating a summary of a recording. The technique includes generating an index associated with the recording, wherein the index identifies a set of terms included in the recording and, for each term in the set of terms, a corresponding location of the term in the recording. The technique also includes determining categories of predefined terms to be identified in the index and identifying a first subset of the terms in the index that match a first portion of the predefined terms in the categories. The technique further includes outputting a summary of the recording comprising the locations of the first subset of terms in the recording and listings of the first subset of terms under one or more corresponding categories.
Nawrocki (US 20190028520), Abstract - Methods and systems of the invention relate to automation of certain fiduciary tasks using machine learning techniques, including generation of corporate meeting minute documents in compliance with legal and organizational requirements. In part, these methods and systems use pre-trained machine learning based data model. The invention monitors and can proactively control meetings to ensure agenda completion among meeting participants and to create meeting minutes, among other tasks.
Ramamurthy et al (US 20200311122), Abstract - In general, the disclosure describes techniques for personalizing a meeting summary according to the relevance of different meeting items within a meeting to different users. In some examples, a computing system for automatically providing personalized summaries of meetings comprises a memory configured to store information describing a meeting; and processing circuitry configured to receive a plurality of meeting item summaries of respective meeting items included in the transcript of the meeting; determine, by applying a model of meeting item relevance to the meeting item summaries, a corresponding relevance to a user of each of the meeting item summaries; and output respective indications of relevance to the user for one or more of the meeting item summaries to provide a personalized summary of the meeting to the user.
Nelson et al (US 11573993), Abstract - Artificial intelligence is introduced into document review to identify content suggestions from input to generate suggested annotations for the reviewed document. An approach is provided for receiving an electronic document that contains original content from an original electronic document for review and electronic mark-ups provided by a first user. One or more electronic mark-ups that represent content suggestions proposed by the first user are identified from the electronic document. For each electronic mark-up of the one or more electronic mark-ups identified a document portion of the original content that corresponds to the electronic mark-up is identified, and an annotation is generated for the electronic mark-up comprising the electronic mark-up and a first user ID for the first user and associating the annotation to the document portion identified. The original content with one or more annotations generated from the one or more electronic mark-ups is displayed, in electronic form, within a display window.
Pandey et al (US 11095468), Abstract - Technologies are disclosed for to utilizing a meeting summary service to generate meeting notes. The meeting notes generated by the meeting summary service can include a variety of information such as participant information, meeting information (e.g., time, place, location, . . . ) meeting agenda information, identified action items, a transcript of the meeting, a recording of the meeting, meeting content presented and/or distributed during the meeting, and the like. The meeting summary service generates meeting notes utilizing a transcript created from a recording of the meeting. In some configurations, machine learning mechanisms may be utilized to identify action items and generating summary information for the meeting. Action items may be assigned to users and tracked to determine state of the action items (e.g., completed). The meeting summary service may also provide a user interface that allows a user, such as a meeting participant, to review the meeting notes.
Any inquiry concerning this communication or earlier communications from the examiner should be directed to RAQIUL AMIN CHOUDHURY whose telephone number is (571)272-2482. The examiner can normally be reached Monday-Friday 7:30 AM - 5:30 PM.
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If attempts to reach the examiner by telephone are unsuccessful, the examiner’s supervisor, John Follansbee can be reached on 571-272-3964. The fax phone number for the organization where this application or proceeding is assigned is 571-273-8300.
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/RAQIUL A CHOUDHURY/Examiner, Art Unit 2444
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