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Improving Automatic Query Classification via Semi-Supervised Learning.

, , , , , and . ICDM, page 42-49. IEEE Computer Society, (2005)

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Predicting query difficulty on the web by learning visual clues., , , , and . SIGIR, page 615-616. ACM, (2005)A framework for determining necessary query set sizes to evaluate web search effectiveness., , , and . WWW (Special interest tracks and posters), page 1176-1177. ACM, (2005)Automatic Evaluation of Web Search Services.. Advances in Computers, (2005)Network Survivability Simulation of a Commercially Deployed Dynamic Routing System Protocol., , , and . IPDPS Workshops, volume 1800 of Lecture Notes in Computer Science, page 1281-1285. Springer, (2000)Recent Results on Fusion of Effective Retrieval Strategies in the Same Information Retrieval System., , , , , and . Distributed Multimedia Information Retrieval, volume 2924 of Lecture Notes in Computer Science, page 101-111. Springer, (2003)Hardening Fingerprinting by Context., and . CEAS, (2007)IIT at TREC 2002 Linear Combinations Based on Document Structure and Varied Stemming for Arabic Retrieval., , , , , and . TREC, volume 500-251 of NIST Special Publication, National Institute of Standards and Technology (NIST), (2002)Analysis of Combining Multiple Query Representations with Varying Lengths in a Single Engine., , and . ITCC, page 236-241. IEEE Computer Society, (2002)ZED: Explaining Temporal Variations in Query Volume., , , and . ADMA, volume 4093 of Lecture Notes in Computer Science, page 485-492. Springer, (2006)Use of Query Concepts and Information Extraction to Improve Information Retrieval Effectiveness., , , , and . TREC, volume 500-242 of NIST Special Publication, page 341-350. National Institute of Standards and Technology (NIST), (1998)