Improving Answer Retrieval from Web Forums with Topic Model and Ontology

Kanda Runapongsa SAIKAEW; Seksan POLTREE; Kornchawal CHAIPAH; Choochart HARUECAIYASAK

Authors

Kanda Runapongsa SAIKAEW Department of Computer Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002
Seksan POLTREE Department of Computer Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002
Kornchawal CHAIPAH Department of Computer Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002
Choochart HARUECAIYASAK National Electronics and Computer Technology Center, Pathum Thani 12120

Keywords:

Latent dirichlet allocation, ontology construction, question answering system, natural language processing

Abstract

Searching for information online has become an essential part of modern living. For a general domain, one can use a tool such as a search engine to find information. However, for domain-specific questions, other means, such as a web forum, are preferable. Common problems with web forums are post duplication and poor search results for long query strings, such as sentences. To overcome these issues, we propose a system based on a language model and ontology. Given a question, the system performs language processing to analyze the syntactic structure of the sentence and its category. The question sentence is classified using regular expressions, keyword matching, and query templates. Based on knowledge constructed from the existing information in the web forum, we can retrieve the suggested links to the answers for the given question. To the best of our knowledge, our paper is the first article that attempts to understand questions and to suggest existing sources of answers in a Thai web forum. We compared our 2 proposed subsystems, language-model-based and ontology-based, with the Google custom web search engine. We evaluated the systems by using a Thai breastfeeding web forum containing 6,823 threads with 75,906 messages. The evaluation results show that the proposed systems have fewer duplicated suggestions compared with the Google search engine. Moreover, for the input with some ambiguous keywords, our proposed system, based on a language model, outperforms the Google search engine, because the system based on a language model is better at finding related terms. For a question with no frequently found keywords, our proposed system, based on ontology, suggests answers which are more appropriate than answers from the Google search engine, because it contains related knowledge defined by experts.

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Author Biography

Kanda Runapongsa SAIKAEW, Department of Computer Engineering, Faculty of Engineering, Khon Kaen University, Khon Kaen 40002

Kanda Runapongsa Saikaew was born in Chiang Rai, Thailand, in 1975. He received the B.S. degree in electrical and computer engineering from Carnegie Mellon University, Pennsylvania, USA, in 1997, and the M.S. and Ph.D. degrees in computer science and engineering from the University of Michigan at Ann Arbor, in 1999 and 2003, respectively.

In 2003, she joined the Department of Computer Engineering, Khon Kaen University, as a Lecturer, and became an Assistant Professor in 2006. Her current research interests include social network analysis, biomedical engineering, and mobile web information systems.

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