Quadripartite Graph-based Clustering of Questions

Author

Blooma, Mohan John ; Chua, Alton Y K ; Goh, Dion Hoe-Lian

Author_Institution

Div. of Inf. Studies, Nanyang Technol. Univ., Singapore, Singapore

fYear

2011

fDate

11-13 April 2011

Firstpage

591

Lastpage

596

Abstract

In a Community Question Answering (CQA) service, each user interaction is different and since there are a variety of complex questions, identifying similar questions for reusing answers is difficult. This is mainly because of lexical mismatch problem. This research aims to develop a quadripartite graph-based clustering (QGC) approach by harnessing relationship of a question with common answers and associated users. It was found that QGC approach outperformed other baseline clustering techniques in identifying similar questions in CQA corpora. We believe that these findings can serve to guide future developments in the reuse of similar question in CQA services.

Keywords

graph theory; pattern clustering; question answering (information retrieval); text analysis; CQA corpora; QGC approach; community question answering service; lexical mismatch problem; quadripartite graph based clustering; Bipartite graph; Clustering algorithms; Clustering methods; Communities; Insurance; Joining processes; Natural languages; Agglomerative Clustering; Community Question Answering; Performance Metrics; Yahoo! Answers;

fLanguage

English

Publisher

ieee

Conference_Titel

Information Technology: New Generations (ITNG), 2011 Eighth International Conference on

Conference_Location

Las Vegas, NV

Print_ISBN

978-1-61284-427-5

Electronic_ISBN

978-0-7695-4367-3

Type

conf

DOI

10.1109/ITNG.2011.108

Filename

5945303