방법 비교

	Query Log Analysis	Search Session Analysis
분야	Library Information Science	Library Information Science
계열	Process / pipeline	Process / pipeline
기원 연도	2000	2000
창시자	Bernard J. Jansen, Amanda Spink & Tefko Saracevic; Silverstein et al.	Bernard J. Jansen, Amanda Spink & Tefko Saracevic; web-search session research
유형	Transaction-log analysis pipeline for search behavior	Analysis pipeline for multi-query search episodes
원전	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.	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.
별칭	Transaction Log Analysis, Search Log Analysis, Web Query Log Analysis, Query Transaction Analysis	Session Analysis, Search Episode Analysis, Multi-Query Session Analysis, Session-Based Search Evaluation
관련	3	3
요약	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.	Search session analysis studies the whole search episode — the sequence of queries, reformulations, clicks, and pauses a user produces while pursuing a single information need — rather than scoring one query in isolation. Real searching is rarely one shot: users issue a query, scan results, refine their wording, follow links, and try again until they succeed or give up. Building on the transaction-log tradition of Jansen, Spink, and Saracevic and the large-scale web studies of Silverstein and colleagues, session analysis reconstructs these episodes from logs, classifies how queries evolve, measures the effort expended, models the transitions between actions, and assesses whether and how the session succeeded. It is the bridge between single-query laboratory evaluation and the messy, iterative reality of how people actually find information.