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Indexing Consistency Analysis×Query Log Analysis×
分野Library Information ScienceLibrary Information Science
系統Process / pipelineProcess / pipeline
提唱年19812000
提唱者L. Rolling; Pranas Zunde & Margaret Dexter (indexing-evaluation tradition)Bernard J. Jansen, Amanda Spink & Tefko Saracevic; Silverstein et al.
種類Diagnostic analysis of indexing variability and its retrieval consequencesTransaction-log analysis pipeline for search behavior
原典Rolling, L. (1981). Indexing consistency, quality and efficiency. Information Processing & Management, 17(2), 69-76. DOI ↗Jansen, B. J., Spink, A., & Saracevic, T. (2000). Real life, real users, and real needs: a study and analysis of user queries on the web. Information Processing & Management, 36(2), 207-227. DOI ↗
別名Indexing Variability Analysis, Indexing Reliability Analysis, Indexing Consistency Study, Within- and Between-Indexer Consistency AnalysisTransaction Log Analysis, Search Log Analysis, Web Query Log Analysis, Query Transaction Analysis
関連33
概要Indexing consistency analysis goes beyond reporting a single agreement number to diagnose why indexing varies and what that variability costs. It distinguishes between-indexer consistency (do different people agree?) from within-indexer consistency (does the same person agree with themselves on re-indexing?), models how factors such as indexing exhaustivity, vocabulary specificity, document subject, and indexer experience drive the variability, and — following Rolling's question of whether consistency stands in for quality — traces how inconsistency degrades retrieval. The aim is actionable: identify the terms, subjects, and conditions where indexers diverge most, and feed that back into guidelines, vocabulary design, and training.Query log analysis — also called transaction-log analysis — studies the records that search systems automatically keep of what users typed, what they clicked, and when. Rather than asking users what they do or testing systems in the laboratory, it observes millions of real searches as they actually happened. The landmark studies by Jansen, Spink, and Saracevic on the Excite engine and by Silverstein and colleagues on AltaVista revealed a consistent and surprising picture: real web queries are very short, rarely use advanced operators, and users almost never look past the first page of results. By cleaning logs, reconstructing sessions, and tabulating term, query, and session statistics, the method turns raw server records into a behavioral portrait of how people really search.
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  3. PUBLISHED

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ScholarGate手法を比較: Indexing Consistency Analysis · Query Log Analysis. 2026-06-24に以下より取得 https://scholargate.app/ja/compare