Term-weighting approaches in automatic text retrieval
Information Processing and Management: an International Journal
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
A Markov random field model for term dependencies
Proceedings of the 28th annual international ACM SIGIR conference on Research and development in information retrieval
An exploration of proximity measures in information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
A study of Poisson query generation model for information retrieval
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Incorporating term dependency in the dfr framework
SIGIR '07 Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval
Investigation of partial query proximity in web search
Proceedings of the 17th international conference on World Wide Web
Discovering key concepts in verbose queries
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Understanding user's query intent with wikipedia
Proceedings of the 18th international conference on World wide web
Entropy-biased models for query representation on the click graph
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Reducing long queries using query quality predictors
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Two-stage query segmentation for information retrieval
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Learning concept importance using a weighted dependence model
Proceedings of the third ACM international conference on Web search and data mining
Exploring web scale language models for search query processing
Proceedings of the 19th international conference on World wide web
Web site traffic ranking estimation via SVM
ICIC'10 Proceedings of the Advanced intelligent computing theories and applications, and 6th international conference on Intelligent computing
Boosting web retrieval through query operations
ECIR'05 Proceedings of the 27th European conference on Advances in Information Retrieval Research
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It has been widely observed that queries of search engine are becoming longer and closer to natural language. Actually, current search engines do not perform well with natural language queries. Accurately discovering the key concepts of these queries can dramatically improve the effectiveness of search engines. It has been shown that queries seem to be composed in a way that how users summarize documents, which is so much similar to anchor texts. In this paper, we present a technique for automatic extraction of key concepts from queries with anchor texts analysis. Compared with using web counts of documents, we proposed a supervised machine learning model to classify the concepts of queries into 3 sets according to their importance and types. In the end of this paper, we also demonstrate that our method has remarkable improvement over the baseline.