BiCWS: mining cognitive differences from bilingual web search results

Authors:
Xiaojiang Huang;Xiaojun Wan;Jianguo Xiao
Affiliations:
Institute of Computer Science and Technology & The MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China;Institute of Computer Science and Technology & The MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China;Institute of Computer Science and Technology & The MOE Key Laboratory of Computational Linguistics, Peking University, Beijing, China
Venue:
WISE'12 Proceedings of the 13th international conference on Web Information Systems Engineering
Year:
2012

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Abstract

In this paper we propose a novel comparative web search system --- BiCWS, which can mine cognitive differences from web search results in a multi-language setting. Given a topic represented by two queries (they are the translations of each other) in two languages, the corresponding web search results for the two queries are firstly retrieved by using a general web search engine, and then the bilingual facets for the topic are mined by using a bilingual search results clustering algorithm. The semantics in Wikipedia are leveraged to improve the bilingual clustering performance. After that, the semantic distributions of the search results over the mined facets are visually presented, which can reflect the cognitive differences in the bilingual communities. Experimental results show the effectiveness of our proposed system.