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Graph-based cluster analysis to identify similar questions: a design science approach

John, Blooma Mohan, Goh, Dion Hoe Lian, Chua, Alton Yeow Kuan and Wickramasinghe, Nilmini 2016, Graph-based cluster analysis to identify similar questions: a design science approach, Journal of the association of information systems, vol. 17, no. 9, pp. 590-613.

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Title Graph-based cluster analysis to identify similar questions: a design science approach
Author(s) John, Blooma Mohan
Goh, Dion Hoe Lian
Chua, Alton Yeow Kuan
Wickramasinghe, Nilmini
Journal name Journal of the association of information systems
Volume number 17
Issue number 9
Article ID 2
Start page 590
End page 613
Total pages 24
Publisher Association of Information Systems
Place of publication Atlanta, Ga.
Publication date 2016-09
ISSN 1536-9323
1558-3457
Keyword(s) cluster analysis
graph theory
design science
social question answering
Summary Social question answering (SQA) services allow users to clarify their queries by asking questions and obtaining answers from other users. To enhance the responsiveness of such services, one can identify similar questions and, thereafter, return the answers available. However, identifying similar questions is difficult because of the complex language structure of user-generated questions. For this reason, we developed an approach to cluster similar questions based on a web of social relationships among the questions, the answers, the askers, and the answerers. To do so, we designed a graph-based cluster analysis using design science research guidelines. In evaluating the results, we found that the proposed graph-based cluster analysis is more promising than baseline methods.
Language eng
Field of Research 080699 Information Systems not elsewhere classified
0806 Information Systems
1503 Business And Management
Socio Economic Objective 970111 Expanding Knowledge in the Medical and Health Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2016, Association for Information Systems
Persistent URL http://hdl.handle.net/10536/DRO/DU:30089071

Document type: Journal Article
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