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Method and System for Cognitive Association Prediction and Notification Based on Predicted Discussion Topic

IP.com Disclosure Number: IPCOM000247238D
Publication Date: 2016-Aug-17
Document File: 2 page(s) / 22K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a method and system that provide an organization with the ability to predict conversations of interest to parties in proximity of a discussion and then determine when to schedule/plan a break based on the real time cognitive state of users. The system notifies associated users about the topic and appropriate times to meet for the discussion.

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Method and System for Cognitive Association Prediction and Notification Based on Predicted Discussion Topic

Informal and casual discussions among people in the workplace, at locations other than an office (e.g., break room, cafeteria, common area, etc.), often produce new and creative ideas. Throughout the day, different groups will pass through the same areas, and each might be engaged in different or related discussions. If people from different groups can connect and converse, then perhaps more and better ideas can be generated for the benefit of the organization.

A method and system are needed that can predict the association of users, predict possible discussion topics of the group, and enable an organization to plan for user participation in a common discussion.

The novel contribution is a method and system that provide an organization with the ability to predict conversations of interest to parties in proximity of a discussion and then determine when to schedule/plan a break based on the real time cognitive state of users.

Software installed in users' mobile and/or wearable devices gathers detailed information about each user (e.g., assigned activities, calendar meeting schedule, spoken content, activity behavior, facial pattern, body language, etc.). The system predicts the user's current cognitive state (e.g., interested, tired, alert, bored, curious, doubtful, confused, panicked, etc.) based on the data captured. Based on the user's predicted cognitive state, the software identifies if the user needs a work break.

The software installed on the server identifies anyone else that needs a break during the approaching (same) period and is a member of the same communications network. The system also identifies the group of people who regularly go for a break together and notifies the identified group of an approaching, recommended break.

Software installed in the server identifies the recent social contributions and discussions (e.g., travel experience, political contribution, etc.) to identify possible discussion topics. It ranks the identified discussion topics based on the common interests amongst those who need a break.

The software predicts the time required to discuss any topic based on content volume. For example, to discuss travel story the group needs more than 30 minutes, as there is a lot of conte...