เปรียบเทียบวิธี

	Query Expansion Evaluation	Cranfield Evaluation Paradigm
สาขาวิชา	Library Information Science	Library Information Science
ตระกูล	Process / pipeline	Process / pipeline
ปีกำเนิด	2008	1967
ผู้ริเริ่ม	Information retrieval evaluation tradition (Salton; Manning, Raghavan & Schütze)	Cyril W. Cleverdon
ประเภท	Evaluation pipeline for query-expansion effectiveness	Test-collection evaluation pipeline for retrieval effectiveness
แหล่งต้นตำรับ	Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to Information Retrieval. Cambridge University Press. ISBN: 9780521865715	Cleverdon, C. W. (1967). The Cranfield tests on index language devices. Aslib Proceedings, 19(6), 173-194.
ชื่อเรียกอื่น	Query Reformulation Evaluation, Term Expansion Assessment, Expansion Effectiveness Measurement, Automatic Query Expansion Evaluation	Cranfield Methodology, Test Collection Evaluation, Cranfield Tests, Laboratory IR Evaluation
ที่เกี่ยวข้อง	3	3
สรุป	Query 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.