Abstract : In this paper, we describe the QASM (Question & Answer Social Media) system based on social network analysis to manage the two main resources in CQA sites: users and contents. We first present the QASM vocabulary used to formalize both the level of interest and the expertise of users on topics. Then we present our method to extract this knowledge from CQA sites. Finally we show how this knowledge is used both to find relevant experts for a question and to search for similar questions. We tested QASM on a dataset extracted from the popular CQA site StackOverflow.
https://hal.archives-ouvertes.fr/hal-01187455
Contributor : Catherine Faron Zucker
<>
Submitted on : Wednesday, August 26, 2015 - 5:17:56 PM
Last modification on : Monday, November 5, 2018 - 3:52:09 PM
Document(s) archivé(s) le : Friday, November 27, 2015 - 11:04:46 AM
Zide Meng, Fabien Gandon, Catherine Faron Zucker. QASM: a Q&A Social Media System Based on Social Semantics. The 13th International Semantic Web Conference, ISWC 2014, Oct 2014, Riva del Garda, Italy. ⟨hal-01187455⟩
