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A Comprehensive Survey and Classification of Approaches for Community Question Answering

Published: 16 August 2016 Publication History

Abstract

Community question-answering (CQA) systems, such as Yahoo! Answers or Stack Overflow, belong to a prominent group of successful and popular Web 2.0 applications, which are used every day by millions of users to find an answer on complex, subjective, or context-dependent questions. In order to obtain answers effectively, CQA systems should optimally harness collective intelligence of the whole online community, which will be impossible without appropriate collaboration support provided by information technologies. Therefore, CQA became an interesting and promising subject of research in computer science and now we can gather the results of 10 years of research. Nevertheless, in spite of the increasing number of publications emerging each year, so far the research on CQA systems has missed a comprehensive state-of-the-art survey. We attempt to fill this gap by a review of 265 articles published between 2005 and 2014, which were selected from major conferences and journals. According to this evaluation, at first we propose a framework that defines descriptive attributes of CQA approaches. Second, we introduce a classification of all approaches with respect to problems they are aimed to solve. The classification is consequently employed in a review of a significant number of representative approaches, which are described by means of attributes from the descriptive framework. As a part of the survey, we also depict the current trends as well as highlight the areas that require further attention from the research community.

Supplementary Material

ZIP File (a18-srba.zip)
Excel file containing detail information about papers involved in survey

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      ACM Transactions on the Web  Volume 10, Issue 3
      August 2016
      201 pages
      ISSN:1559-1131
      EISSN:1559-114X
      DOI:10.1145/2988335
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      2. adaptive collaboration support
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      7. user modeling

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