Autonomic meeting effectiveness and cadence forecasting

US10171525B2 · US · B2

Patent metadata
FieldValue
Publication numberUS-10171525-B2
Application numberUS-201615200281-A
CountryUS
Kind codeB2
Filing dateJul 1, 2016
Priority dateJul 1, 2016
Publication dateJan 1, 2019
Grant dateJan 1, 2019

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  1. Title

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  2. Abstract

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  4. Key dates

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  5. First independent claim

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  6. CPC / IPC classifications

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Abstract

Official abstract text for this publication.

Meeting participation data of a meeting of a group of participants in-progress is collected. The meeting participation data is analyzed to identify a topic being discussed in the meeting. Using a trend of affective states of a participant, a future affective state of the participant is forecasted relative to the topic. The future affective state is evaluated to conclude that data contributed by the participant at a future time in the meeting is not likely to progress the topic to completion by at least a specified degree. A cognitive system (cog) trained in the subject-matter is selected. The cog is added to the meeting before the future time and while the meeting is in-progress.

First claim

Opening claim text (preview).

What is claimed is: 1. A method comprising: configuring an autonomous system to receive meeting participation data from a meeting participation tool that is configured in a meeting environment; collecting, using the autonomous system via the meeting participation tool of the meeting environment, the meeting participation data of a meeting in-progress, the meeting comprising a group of participants; analyzing, using the autonomous system, the meeting participation data to identify a topic being discussed in the meeting; forecasting, using the autonomous system, using a processor and a memory, using a trend of affective states of a participant, a future affective state of the participant relative to the topic; evaluating, using the autonomous system, the future affective state to conclude that data contributed by the participant at a future time in the meeting is not likely to progress the topic to completion by at least a specified degree; selecting, using the autonomous system, a cognitive system (cog) trained in the subject-matter; and adding, using the autonomous system, the cog to the meeting before the future time and while the meeting is in-progress, the adding the cog causing the cog to receive the meeting participation data from the meeting participation tool in the meeting environment, and further causing the cog to insert a cog output in the meeting participation data. 2. The method of claim 1 , further comprising: collecting a past meeting participation data of the past meeting; extracting a past affective state of the participant by analyzing the data contributed by the participant in the past meeting participation data; and using the past affective state as a data point in creating the trend of affective states of the participant for the topic. 3. The method of claim 1 , further comprising: collecting a past meeting participation data of the past meeting; extracting a past somatic state of the participant by analyzing the biometric data of the participant in the past meeting participation data; and using the past somatic state as a data point in creating the trend of somatic states of the participant for the topic, wherein the forecasting further uses the trend of somatic states. 4. The method of claim 1 , further comprising: further analyzing the meeting participation data to evaluate whether data contributed by the participant in the group is progressing the topic to completion by at least the specified degree; and performing the forecasting responsive to determining that the data contributed by the participant in the group is not progressing the topic to completion by at least the specified degree. 5. The method of claim 1 , further comprising: determining, by further analyzing the meeting participation data, that data contributed by the group is not progressing the topic to completion by at least a specified degree; selecting the topic for a future meeting; and scheduling the future meeting about the topic using a different group. 6. The method of claim 5 , further comprising: adding the cog to the different group as a substitution for the participant. 7. The method of claim 1 , further comprising: determining, by further analyzing the meeting participation data, that data contributed by the group is not progressing the topic to completion by at least a specified degree, wherein selecting the cog and adding the cog are responsive to determining that the data contributed by the group is not progressing the topic to completion by at least a specified degree. 8. The method of claim 1 , further comprising: processing, as a part of analyzing the meeting participation data to identify the topic, the meeting participation data using Natural Language Processing (NLP) to identify the subject-matter, the subject-matter comprising the topic. 9. The method of claim 1 , the meeting participation data comprising: data contributed by the group of participants to the meeting; and biometric data collected from at least one participant in the group during the meeting. 10. The method of claim 9 , wherein the data contributed by the group of participants includes data contributed by a participant one of before and after the meeting. 11. The method of claim 9 , wherein the biometric data comprises a voice characteristic of speech data contributed by the at least one participant. 12. The method of claim 9 , wherein the biometric data comprises a behavioral characteristic of the at least one participant. 13. The method of claim 9 , wherein the biometric data comprises an infrared image of the at least one participant. 14. The method of claim 9 , further comprising: using the biometric data to compute a somatic state of the at least one participant, wherein the somatic state of the at least one participant corresponds to an affective state of the at least one participant relative to the topic. 15. A computer usable program product comprising one or more computer-readable storage devices, and program instructions stored on at least one of the one or more storage devices, the stored program instructions comprising: program instructions to configure an autonomous system to receive meeting participation data from a meeting participation tool that is configured in a meeting environment; program instructions to collect, using the autonomous system via the meeting participation tool of the meeting environment, the meeting participation data of a meeting in-progress, the meeting comprising a group of participants; program instructions to analyze, using the autonomous system, the meeting participation data to identify a topic being discussed in the meeting; program instructions to forecast, using the autonomous system, using a processor and a memory, using a trend of affective states of a participant, a future affective state of the participant relative to the topic; program instructions to evaluate, using the autonomous system, the future affective state to conclude that data contributed by the participant at a future time in the meeting is not likely to progress the topic to completion by at least a specified degree; program instructions to select, using the autonomous system, a cognitive system (cog) trained in the subject-matter; and program instructions to add, using the autonomous system, the cog to the meeting before the future time and while the meeting is in-progress, adding the cog causing the cog to receive the meeting participation data from the meeting participation tool in the meeting environment, and further causing the cog to insert a cog output in the meeting participation data. 16. The computer usable program product of claim 15 , further comprising: program instructions to collect a past meeting participation data of the past meeting; program instructions to extract a past affective state of the participant by analyzing the data contributed by the participant in the past meeting participation data; and program instructions to use the past affective state as a data point in creating the trend of affective states of the participant for the topic. 17. The computer usable program product of claim 15 , further comprising: program instructions to collect a past meeting participation data of the past meeting; program instructions to extract a past somatic state of the participant by analyzing the biometric data of the participant in the past meeting participation data; and program instructions to use the past somatic state as a data point in creating the trend of somatic states of the participant for the topic, wherein the fore

Assignees

Inventors

Classifications

  • User profiles · CPC title

  • Office automation; Time management · CPC title

  • Semantic analysis · CPC title

  • H04L65/403Primary

    Arrangements for multi-party communication, e.g. for conferences (data switching systems for conference H04L12/18; arrangements for connecting several subscribers to a common circuit, i.e. affording conference facilities H04M3/56; television conferencing systems H04N7/15) · CPC title

  • G06F40/40Primary

    Processing or translation of natural language (natural language analysis G06F40/20; semantic analysis G06F40/30) · CPC title

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What does patent US10171525B2 cover?
Meeting participation data of a meeting of a group of participants in-progress is collected. The meeting participation data is analyzed to identify a topic being discussed in the meeting. Using a trend of affective states of a participant, a future affective state of the participant is forecasted relative to the topic. The future affective state is evaluated to conclude that data contributed by…
Who is the assignee on this patent?
IBM
What technology area does this patent fall under?
Primary CPC classification H04L65/403. Mapped technology areas include Electricity.
When was this patent published?
Publication date Tue Jan 01 2019 00:00:00 GMT+0000 (Coordinated Universal Time) (B2). Legal status and post-grant events are not shown on this page.
What related patents are in patentsdb?
We list 4 related publications on this page (citations in our corpus or others sharing the same primary CPC).