Future meeting evaluation using implicit device feedback

Patent metadata

Field	Value
Publication number	US-2016104094-A1
Application number	US-201414510891-A
Country	US
Kind code	A1
Filing date	Oct 9, 2014
Priority date	Oct 9, 2014
Publication date	Apr 14, 2016
Grant date	—

Abstract

This document relates to meeting evaluation. One example determines previous meeting attributes of previous meetings that were attended by a user or to which the user was invited, and obtains implicit feedback about the previous meetings from a device of the user. The example includes training a predictive algorithm to evaluate future meetings for the user using the previous meeting attributes and the implicit feedback about the previous meetings.

First claim

1 . A method performed by at least one hardware processor, the method comprising:
obtaining previous meeting attributes of previous meetings that were attended by a user or to which the user was invited; obtaining implicit feedback for the previous meetings from a device of the user; and training a predictive algorithm to evaluate future meetings for the user using the previous meeting attributes and the implicit feedback about the previous meetings.

2 . The method of claim 1 , further comprising:
obtaining other previous meeting attributes of other previous meetings attended by another user or to which the another user was invited; obtaining other implicit feedback about the other previous meetings from another device of the another user; and training the predictive algorithm to evaluate other future meetings for the another user using the other previous meeting attributes and the other implicit feedback.

3 . The method of claim 2 , further comprising:
obtaining explicit feedback from the device of the user about the previous meetings and other explicit feedback from the another device of the another user; and training the predictive algorithm for the user using the explicit feedback and for the another user using the other explicit feedback.

4 . The method of claim 3 , wherein the explicit feedback comprises ratings of the previous meetings and the other explicit feedback comprises other ratings of the other previous meetings.

5 . The method of claim 1 , wherein training the predictive algorithm comprises training a mapping algorithm to evaluate individual previous meetings using the implicit feedback.

6 . The method of claim 1 , wherein the previous meetings comprise both physical meetings and virtual meetings.

7 . The method of claim 1 , further comprising:
obtaining future meeting attributes for an individual future meeting; and evaluating the future meeting attributes of the individual future meeting using the trained predictive algorithm to obtain an evaluation of the individual future meeting.

8 . The method of claim 1 , wherein the previous meeting attributes identify meeting participants.

9 . The method of claim 1 , wherein the previous meeting attributes identify a relationship between the user and a meeting organizer determined using an organizational hierarchy.

10 . The method of claim 1 , wherein the previous meeting attributes identify meeting locations.

11 . A method performed by at least one hardware processor, the method comprising:
obtaining explicit evaluations of certain previous meetings attended by a user; obtaining implicit feedback about the certain previous meetings from a device of the user; and training a mapping algorithm to map the implicit feedback to the explicit evaluations.

12 . The method of claim 11 , wherein the explicit evaluations comprise usefulness ratings of the certain previous meetings.

13 . The method of claim 11 , wherein the implicit feedback reflects application usage by the user during the certain previous meetings.

14 . The method of claim 11 , wherein the implicit feedback reflects whether the user was physically present during the certain previous meetings.

15 . The method of claim 11 , wherein the implicit feedback reflects whether the user spoke at the certain previous meetings.

16 . The method of claim 11 , wherein the implicit feedback reflects whether the user communicated via telephone or email during the certain previous meetings.

17 . The method of claim 11 , further comprising:
obtaining other implicit feedback from the user about other previous meetings attended by the user; and applying the trained mapping algorithm to the other implicit feedback to obtain other evaluations of the other previous meetings.

18 . A computing system comprising:
one or more hardware processing units; and one or more computer-readable storage devices storing computer-executable instructions which, when executed by the one or more hardware processing units, cause the one or more processing units to:
monitor usage of the computing device during certain meetings to obtain implicit feedback about the certain meetings;
provide the implicit feedback to a meeting evaluation module having a predictive algorithm trained to evaluate future meetings; and
obtain an evaluation of an individual future meeting from the meeting evaluation module.

19 . The computing system of claim 18 , wherein the meeting evaluation module is executed on another computing device located remotely from the computing system and the computer-executable instructions cause the one or more hardware processing units to:
provide the implicit feedback to the meeting evaluation module by sending the implicit feedback over a network to the another computing device that executes the meeting evaluation module.

20 . The computing system of claim 18 , wherein the computer-executable instructions cause the one or more hardware processing units to:
display a graphical user interface that conveys the evaluation of the individual future meeting.

Assignees

• Microsoft Corp

Inventors

• Yom-Tov Elad
• Schain Mariano R
• Tennenholtz Moshe

Classifications

• G06Q10/06395 Primary

  Quality analysis or management · CPC title

• G06Q10/109

  Time management, e.g. calendars, reminders, meetings or time accounting · CPC title