Real life, real users, and real needs: a study and analysis of user queries on the web
Information Processing and Management: an International Journal
Improving Automatic Query Classification via Semi-Supervised Learning
ICDM '05 Proceedings of the Fifth IEEE International Conference on Data Mining
KDD CUP-2005 report: facing a great challenge
ACM SIGKDD Explorations Newsletter
Q2C@UST: our winning solution to query classification in KDDCUP 2005
ACM SIGKDD Explorations Newsletter
Proceedings of the 15th international conference on World Wide Web
Measuring Qualities of Articles Contributed by Online Communities
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Identifying Document Topics Using the Wikipedia Category Network
WI '06 Proceedings of the 2006 IEEE/WIC/ACM International Conference on Web Intelligence
Talk Before You Type: Coordination in Wikipedia
HICSS '07 Proceedings of the 40th Annual Hawaii International Conference on System Sciences
Semantic Convergence of Wikipedia Articles
WI '07 Proceedings of the IEEE/WIC/ACM International Conference on Web Intelligence
Exploiting Wikipedia for Directional Inferential Text Similarity
ITNG '08 Proceedings of the Fifth International Conference on Information Technology: New Generations
Automatic Web Query Classification Using Large Unlabeled Web Pages
WAIM '08 Proceedings of the 2008 The Ninth International Conference on Web-Age Information Management
Domain Ontology Based Automatic Question Answering
ICCET '09 Proceedings of the 2009 International Conference on Computer Engineering and Technology - Volume 02
Understanding user's query intent with wikipedia
Proceedings of the 18th international conference on World wide web
Computing semantic relatedness using Wikipedia-based explicit semantic analysis
IJCAI'07 Proceedings of the 20th international joint conference on Artifical intelligence
DBpedia: a nucleus for a web of open data
ISWC'07/ASWC'07 Proceedings of the 6th international The semantic web and 2nd Asian conference on Asian semantic web conference
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Identifying the intended topic that underlies a user's query can benefit a large range of applications, from search engines to question-answering systems. However, query classification remains a difficult challenge due to the variety of queries a user can ask, the wide range of topics users can ask about, and the limited amount of information that can be mined from the query. In this paper, we develop a new query classification system that accounts for these three challenges. Our system relies on the freely-available online encyclopedia Wikipedia as a natural-language knowledge-based, and exploits Wikipedia's structure to infer the correct classification of any given query. We will present two variants of this query classification system in this paper, and demonstrate their reliability compared to each other and to the literature benchmarks using the query sets from the KDD CUP 2005 and TREC 2007 competitions.