Query clustering using user logs

By Ji-rong Wen, Jian-Yun Nie, HongJiang Zhang. TOIS, 2002

444 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Information Systems, Signal Processing

View Paper: https://www.semanticscholar.org/paper/b6361bcb1592fc718e6e81bd7aef3cc75b7298f1

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Citations in the corpus

Clickthrough-based translation models for web search: from word models to phrase models (2010, methodology): “Clickthrough data have been exploited for this purpose [3, 34].”
Query Expansion by Mining User Logs (2003, background): “It is generally observed that users on the Web typically submit very short queries to search engines and the average length of Web queries is less than two words [34].”
Finding similar questions in large question and answer archives (2005, background): “The idea of finding similar queries using user click logs or retrieval results has been proposed previously [23, 20, 1].”
Privacy in Search Logs (2009, background): “clustering [20], where the similarity measure of the clustering algorithm takes into account the implicit feedback given by user clicks.”
Query enrichment for web-query classification (2006, background): “Recently, some interesting works have emerged on using query logs to expand the meanings of user queries [Wen et al. 2002; Beeferman and Berger 2000].”
Query Expansion Techniques for Information Retrieval: a Survey (2017, unknown): “Query logs is another data source for query expansion, where user’s queries are expanded using correlation between query terms and document terms determined using user logs (e.g., [266, 75]).”
ST-DBSCAN: An algorithm for clustering spatial-temporal data (2007, methodology): “[29] adopted DBSCAN and Incremental DBSCAN as the core algorithms of their query clustering tool.”
Information re-retrieval: repeat queries in Yahoo's logs (2007, background): “The second category (DQ-OC) contains more possible variation in query intent, but is interesting to ex plore because search engines should support complex re-finding be havior in addition to the simple single repeat click behavior . Previous work has identified over-lapping click queries as likely t”