Rekodi ya ushahidi wa mbinu

Relevance Feedback Evaluation

Relevance feedback evaluation measures how much a retrieval system improves when it reformulates a query using user judgments on the first results. The technique that defined the field is Rocchio's vector-space feedback, in which documents the user marks relevant pull the query vector toward themselves and documents marked non-relevant push it away; Salton and Buckley's 1990 study systematized its evaluation and showed substantial effectiveness gains. The central methodological challenge is fairness: because the user has already seen and judged some documents, naively re-scoring the whole collection rewards the system for re-finding documents it was just told about. Residual-collection and frozen-rank evaluation solve this by measuring improvement only on documents the user has not yet seen.

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Rekodi ya chanzo

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Relevance Feedback Evaluation (Measuring Retrieval Gains from Query Reformulation)

Rekodi ya mbinu ya kiajenda · process-pipeline / library-information-science

Salton, G., & Buckley, C. (1990). Improving retrieval performance by relevance feedback. Journal of the American Society for Information Science, 41(4), 288-297. · DOI 10.1002/(SICI)1097-4571(199006)41:4<288::AID-ASI8>3.0.CO;2-H
Manning, C. D., Raghavan, P., & Schütze, H. (2008). Introduction to Information Retrieval. Cambridge University Press. · ISBN 9780521865715
Voorhees, E. M., & Harman, D. K. (Eds.). (2005). TREC: Experiment and Evaluation in Information Retrieval. MIT Press. · ISBN 9780262220736

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Taxonomic bucketCranfield Evaluation Paradigmmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketQuery Expansion Evaluationmachine-suggested · Relational suggestion, not evidence.Taxonomic bucketTREC Pooling and Relevance Judgmentsmachine-suggested · Relational suggestion, not evidence.