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Web Intelligence and Intelligent Agent Technology, IEEE/WIC/ACM International Conference on (2013)
Atlanta, GA, USA USA
Nov. 17, 2013 to Nov. 20, 2013
pp: 139-146
ABSTRACT
Diversifying query suggestions has emerged recently, by which the recommended queries can be both relevant and diverse. Most existing works diversify suggestions by query log analysis, however, for structured data, not all query logs are available. To this end, this paper studies the problem of suggesting diverse query terms by using topics from Wikipedia. Wikipedia is a successful online encyclopedia, and has high coverage of entities and concepts. We first obtain all relevant topics from Wikipedia, and then map each term to these topics. As the mapping is a nontrivial task, we leverage information from both Wikipedia and structured data to semantically map each term to topics. Finally, we propose a fast algorithm to efficiently generate the suggestions. Extensive evaluations are conducted on a real dataset, and our approach yields promising results.
INDEX TERMS
topics, query suggestion diversification, Wikipedia
CITATION

H. Hu, M. Zhang, Z. He, P. Wang and W. Wang, "Diversifying Query Suggestions by Using Topics from Wikipedia," 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)(WI-IAT), Atlanta, GA, USA, 2013, pp. 139-146.
doi:10.1109/WI-IAT.2013.21
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