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Query Expansion Evaluation×Cranfield Evaluation Paradigm×
क्षेत्रLibrary Information ScienceLibrary Information Science
परिवारProcess / pipelineProcess / pipeline
उद्भव वर्ष20081967
प्रवर्तकInformation retrieval evaluation tradition (Salton; Manning, Raghavan & Schütze)Cyril W. Cleverdon
प्रकारEvaluation pipeline for query-expansion effectivenessTest-collection evaluation pipeline for retrieval effectiveness
मौलिक स्रोतManning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to Information Retrieval. Cambridge University Press. ISBN: 9780521865715Cleverdon, C. W. (1967). The Cranfield tests on index language devices. Aslib Proceedings, 19(6), 173-194. DOI ↗
उपनामQuery Reformulation Evaluation, Term Expansion Assessment, Expansion Effectiveness Measurement, Automatic Query Expansion EvaluationCranfield Methodology, Test Collection Evaluation, Cranfield Tests, Laboratory IR Evaluation
संबंधित33
सारांशQuery expansion evaluation measures whether adding terms to a user's query — drawn from a thesaurus, from corpus co-occurrence statistics, or from relevance or pseudo-relevance feedback — actually improves retrieval. Expansion attacks the vocabulary-mismatch problem, where relevant documents use words the searcher did not, and it tends to raise recall by bringing in synonymous and related terms. But it can also lower precision by introducing ambiguity, and it can help some queries while badly hurting others. Sound evaluation therefore reports not just the average effectiveness change but the recall-precision trade-off and a robustness analysis of how many individual queries were helped versus harmed.The Cranfield evaluation paradigm is the foundational experimental design for measuring how well an information retrieval system finds relevant documents. Devised by Cyril Cleverdon at the College of Aeronautics in Cranfield during the 1960s, it fixes three ingredients — a document collection, a set of search requests, and human relevance judgments linking requests to documents — and then holds them constant so that competing indexing methods or retrieval algorithms can be compared on recall and precision under controlled, repeatable conditions. By abstracting evaluation away from any single live user and turning it into a reusable laboratory experiment, Cranfield made retrieval effectiveness a measurable quantity and supplied the template that every later large-scale campaign, including TREC, has built upon.
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