Evaluating user knowledge in large scale online knowledge communities

Xiaomo Liu, Weiguo Fan, Gang Wang, Jian Jiao

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

It is an important knowledge management task to evaluate a user's domain knowledge in a knowledge community. We present a new domain knowledge representation method that considers both user-document associations and document-topic relevance. We provide three alternative user-document association models with varying syntactic and semantic inferences and two alternative document-topic relevance models with different assumptions on knowledge diffusion. We compare the effectiveness of different knowledge representation methods using the combinations of these alternatives. Using a real data set collected from the Sun forums, we find that the vector space model for user-document association combined with the medium-level diffusion model outperform all other model combinations.

Original languageEnglish (US)
Title of host publication2nd International Conference on Software Engineering and Data Mining, SEDM 2010
Pages404-409
Number of pages6
StatePublished - Sep 17 2010
Externally publishedYes
Event2nd International Conference on Software Engineering and Data Mining, SEDM 2010 - Chengdu, China
Duration: Jun 23 2010Jun 25 2010

Publication series

Name2nd International Conference on Software Engineering and Data Mining, SEDM 2010

Conference

Conference2nd International Conference on Software Engineering and Data Mining, SEDM 2010
Country/TerritoryChina
CityChengdu
Period6/23/106/25/10

Keywords

  • Online communities
  • Topic modeling
  • User knowledge

ASJC Scopus subject areas

  • Software

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