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Stratified analysis of AOL query log

dc.contributor.authorBrenes Martínez, David José 
dc.contributor.authorGayo Avello, Daniel 
dc.date.accessioned2013-01-30T10:07:45Z
dc.date.available2013-01-30T10:07:45Z
dc.date.issued2009
dc.identifier.citationInformation Sciences, 179 (12), p. 1844-1858 (2009); doi:10,1016/j.ins.2009.01.027spa
dc.identifier.issn0020-0255
dc.identifier.urihttp://hdl.handle.net/10651/8385
dc.description.abstractCharacterizing user's intent and behaviour while using a retrieval information tool (e.g a search engine) is a key question on web research, as it hold the keys to know how the users interact, what they are expecting and how we can provide them information in the most bene cial way. Previous research has focused on identifying the average characteristics of user interactions. This paper proposes a strati ed method for analyzing query logs that groups queries and sessions according to their hit frequency and analyzes the characteristics of each group in order to nd how representative the average values are. Findings show that behaviours typically associated with the average user do not t in most of the aforementioned groups.en
dc.format.extentp. 1844-1858spa
dc.language.isoeng
dc.publisherElsevier
dc.relation.ispartofInformation Sciences, 179 (12)spa
dc.rights© Elsevier
dc.subjectQuery log analysisen
dc.subjectUser behaviouren
dc.subjectUser interactionsen
dc.subjectUser intenten
dc.subjectUser profilingen
dc.titleStratified analysis of AOL query logspa
dc.typeinfo:eu-repo/semantics/article
dc.identifier.doi10.1016/j.ins.2009.01.027
dc.type.dcmitextspa
dc.relation.publisherversionhttp://dx.doi.org/10.1016/j.ins.2009.01.027


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