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Determining subject-matter expert for a collaborative reading environment

IP.com Disclosure Number: IPCOM000241843D
Publication Date: 2015-Jun-03
Document File: 4 page(s) / 927K

Publishing Venue

The IP.com Prior Art Database

Abstract

When reading technical documentation, sometimes is hard to understand the true meaning of words. It is not rare the case when the same documentation paragraph is understood differently by peoples. This is due multiple reasons: • Language barrier • Previous technical background required • Different/custom architecture using the same terms but having different functionality It is hard to find into organization a true subject-matter expert on what you are interested. Usually it takes many days or weeks to really find the right person that can help.

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Determining subject-matter expert for a collaborative reading environment

Abstract:

When reading technical documentation, sometimes is hard to understand the true meaning of words. It is not rare the case when the same documentation paragraph is understood differently by peoples. This is due multiple reasons:

·         Language barrier

·         Previous technical background required

·         Different/custom architecture using the same terms but having different functionality

It is hard to find into organization a true subject-matter expert on what you are interested.  Usually it takes many days or weeks to really find the right person that can help.

Description:

The proposed solution is a system that automatically determines the subject-matter expert on a certain portion of technical documentation and provides recommendations to new readers.

The system has a Reading detection component that determine for each registered user what is his reading activity. The Reading detection is collecting information on how often reader accesses a certain document (region, paragraph, etc), how much spent on it, how many times reads it. The Correlation component determines for a user what related documents read it and calculates a correlation factor. A subject-matter Expert indicator component is calculating for a given document (region, paragraph, etc) a list of experts, by searching into experts database and correlating the current document with experts knowledge. [Fig. 1]

Fig. 1

For online and offline documentation and for in-tools documentation used by a collaborative group (a team of developers, for example) it is useful to have a tool that records each user what had read.

When another user reads a document (complete or partial), he can see for each section/line/paragraph which else team member read that before. In that way, he can talk or ask for help, for better understanding the docs.
The Expertise level of each user is determined using a list of attributes specific to system...