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.
اقرأ الطريقة كاملة
سجّل الدخول بحساب مجاني لقراءة هذا القسم.
خريطة المناهج
محيط المناهج ذات الصلة — اختر عقدةً للاستكشاف.
المصادر
- 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
كيف تستشهد بهذه الصفحة
ScholarGate. (2026, June 23). Relevance Feedback Evaluation (Measuring Retrieval Gains from Query Reformulation). ScholarGate. https://scholargate.app/ar/library-information-science/relevance-feedback-evaluation
أيُّ منهج؟
ضع هذا المنهج إلى جانب أقرب نظائره واقرأهما جنباً إلى جنب — المكتبة تضع الكتب على الطاولة، والاختيار لك.
- Cranfield Evaluation ParadigmLibrary Information Science↔ قارن
- Query Expansion EvaluationLibrary Information Science↔ قارن
- TREC Pooling and Relevance JudgmentsLibrary Information Science↔ قارن