Discovering context-topic rules in search engine logs
Author | dc.contributor.author | Hurtado, Carlos | |
Author | dc.contributor.author | Levene, Mark | es_CL |
Admission date | dc.date.accessioned | 2009-04-09T10:45:45Z | |
Available date | dc.date.available | 2009-04-09T10:45:45Z | |
Publication date | dc.date.issued | 2006 | |
Cita de ítem | dc.identifier.citation | STRING PROCESSING AND INFORMATION RETRIEVAL, PROCEEDINGS Book Series: LECTURE NOTES IN COMPUTER SCIENCE Volume: 4209 Pages: 346-353 Published: 2006 | en |
Identifier | dc.identifier.issn | 0302-9743 | |
Identifier | dc.identifier.uri | https://repositorio.uchile.cl/handle/2250/124890 | |
Abstract | dc.description.abstract | In this paper, we present a class of rules, called context-topic rules, for discovering associations between topics and contexts, where a context is defined as a set of features that can be extracted from the log file of a Web search engine. We introduce a notion of rule interesting-ness that measures the level of the interest of the topic within a context, and provide an algorithm to compute concise representations of interesting context-topic rules. Finally, we present the results of applying the methodology proposed to a large data log of a search engine. | en |
Lenguage | dc.language.iso | en | en |
Publisher | dc.publisher | SPRINGER-VERLAG BERLIN | en |
Título | dc.title | Discovering context-topic rules in search engine logs | en |
Document type | dc.type | Artículo de revista |
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