@inproceedings{adce2c6bd4364674afe962c72839f419,
title = "Quadripartite graph-based clustering of questions",
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 = "Agglomerative Clustering, Community Question Answering, Performance Metrics, Yahoo! Answers",
author = "Blooma, \{Mohan John\} and Chua, \{Alton Y.K.\} and Goh, \{Dion Hoe Lian\}",
year = "2011",
doi = "10.1109/ITNG.2011.108",
language = "English",
isbn = "9780769543673",
series = "Proceedings - 2011 8th International Conference on Information Technology: New Generations, ITNG 2011",
publisher = "IEEE Computer Society",
pages = "591--596",
booktitle = "Proceedings - 2011 8th International Conference on Information Technology",
address = "United States",
}