Topic-specific Analysis of search queries

Judit Bar-Ilan, Zheng Zhu, Mark Levene

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations


The analysis of search engine logs is important in order to understand how users interact with a search engine. Conventional analysis of search engine log data looks at various metrics such as query and session length aggregated over the full data set. Here we segment the data according to a top-level ontology of web search and compute the metrics on a topic by topic basis. Our results show that although for a given metric, such as query length, the statistics of most classes are similar to the aggregate statistic; there are usually some outlier classes which exhibit deviant behavior.

Original languageEnglish
Title of host publicationProceedings of Workshop on Web Search Click Data, WSCD'09
Number of pages8
StatePublished - 2009
EventWorkshop on Web Search Click Data, WSCD'09 - Barcelona, Spain
Duration: 9 Feb 20099 Feb 2009

Publication series

NameProceedings of Workshop on Web Search Click Data, WSCD'09


ConferenceWorkshop on Web Search Click Data, WSCD'09


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