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In-Context Experts from the Active Communication Threads

IP.com Disclosure Number: IPCOM000246606D
Publication Date: 2016-Jun-20
Document File: 3 page(s) / 124K

Publishing Venue

The IP.com Prior Art Database

Abstract

Disclosed is a cognitive system and a method for identifying a user's current learning requirements as presented in a social domain, email exchange, or instant messaging communication, and then analyzing the user's interactions to retrieve contacts that are also experts in a relevant area (i.e., matched in the context of learning requirements of the user). The system presents matched contacts as individuals that can help meet the user’s learning requirements.

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In-Context Experts from the Active Communication Threads

People often look to the Internet or nearby experts when trying to solve a difficult problem. It also happens that two people might interact with each other through email, on social networks, or through instant messages in some context, without knowing each

other's area(s) of expertise or ability to help solve a specific problem.

Current expertise locator systems across an enterprise can find experts based on keywords searches. The systems analyze location, keywords, etc. to provide a user

with a list of experts as search results; however, the user is not likely to be familiar with or personally know any of the experts presented in the list, and might then be reluctant to make contact. In addition, the user has to perform manual searches, which is not

only time consuming, but also ineffective if the user does not provide sufficient search terms.

A system is needed that can analyze a user's current requirements and then match said requirements to the skills set of people with whom the user is already familiar.

The novel contribution is a cognitive system and a method for analyzing a user's current learning requirements as presented in a social domain and then analyzing the user's active interactions to retrieve contacts that are also experts in a relevant area (i.e., matched in the context of learning requirements of the user). The system uses a personality evaluation kind of service to help suggest the contacts in the context of learning requirements of the user.

Thus, if two people interact through any medium, the system captures the skill levels of both parties for the top *n* skills. After determining that one user can benefit from any

skills of the other user, the system suggests that the users collaborate in context of that skill.

To implement the system in a preferred embodiment:

1. System determines the right contact(s) from the user's recent collaborations, including (but not limited to):

A. Email conversation

    B. Instant message conversation
C. Blog comments, forum questions/answers, etc. D. Social network message exchanges
2. System analyzes:

A. Current requirements of the user (e.g., it would know from analyzing user's recent searches that the user is looking for a tutorial on Software X)

    B. Skill levels of contacts with whom this user interacts 3. From the contacts whose skill levels match the user's current requirements, the system recommends a contact who also matches the user in perso...