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.
Catatan sumber
Kutipan disalin apa adanya dari catatan sumber metode. Tidak ada verifikasi tingkat klaim yang disimpulkan darinya.
- 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
Klaim yang dikurasi
Klaim tersimpan dalam buku besar bukti, masing-masing dengan penilaiannya sendiri.
Tampilan ini tidak menciptakan penilaian klaim ketika buku besar tidak memilikinya.
Metode terkait
Dihasilkan dari grafik metode dan ditampilkan sebagai relasi yang disarankan mesin — tidak ada klaim bukti yang disimpulkan.