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Joint model of topics, expertises, activities and trends for question answering Web applications

Zide Meng 1 Fabien Gandon 1 Catherine Faron Zucker 2, 1
1 WIMMICS - Web-Instrumented Man-Machine Interactions, Communities and Semantics
CRISAM - Inria Sophia Antipolis - Méditerranée , Laboratoire I3S - SPARKS - Scalable and Pervasive softwARe and Knowledge Systems
Abstract : Users in question-answer sites generate huge amounts of high quality and highly reusable information. This information can be categorized by topics but since users' interests change with time, it's important to uncover the temporal patterns and trends in their activity to detect their current expertize. These temporal variations remained unexplored in question-answer sites while detecting them enables us to improve tasks such as: question routing, expert recommending and community life-cycle management. In this paper, we proposed a generative model of such a community and its dynamics , and we performed experiments with real-world data to confirm the effectiveness of our joint model, studying the users' behaviors and topics dynamics on a dataset extracted from the popular question-answer site StackOverflow.
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Submitted on : Friday, March 25, 2016 - 6:49:56 PM
Last modification on : Friday, January 21, 2022 - 3:13:11 AM
Long-term archiving on: : Monday, November 14, 2016 - 6:32:28 AM


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  • HAL Id : hal-01293968, version 1



Zide Meng, Fabien Gandon, Catherine Faron Zucker. Joint model of topics, expertises, activities and trends for question answering Web applications. 2016 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT), Oct 2016, USA, Oct 2016, Omaha, United States. ⟨hal-01293968⟩



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