BiCWS: Mining cognitive differences from bilingual web search results
|BiCWS: Mining cognitive differences from bilingual web search results|
|Author(s)||Huang X., Wan X., Xiao J.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||Comparative Text Mining, Cross Lingual Text Mining, Information Retrieval (Extra: Bilingual search, Search results, Semantic distribution, Text mining, Web search system, Web searches, Wikipedia, Clustering algorithms, Data mining, Information retrieval, Search engines, Semantics, Systems engineering, Websites)|
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BiCWS: Mining cognitive differences from bilingual web search results is a 2012 conference paper written in English by Huang X., Wan X., Xiao J. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
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.
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