Towards query log based personalization using topic models

Mark J. Carman, Fabio Crestani, Morgan Harvey, Mark Baillie

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

42 Citations (Scopus)

Abstract

We investigate the utility of topic models for the task of personalizing search results based on information present in a large query log. We define generative models that take both the user and the clicked document into account when estimating the probability of query terms. These models can then be used to rank documents by their likelihood given a particular query and user pair.
Original languageEnglish
Title of host publicationProceedings of the 19th ACM International Conference on Information and Knowledge Management
Place of PublicationNew York
PublisherACM
Pages1849-1852
ISBN (Print)978-1-4503-0099-5
DOIs
Publication statusPublished - 2010
EventProceedings of the 19th {ACM} Conference on Information and Knowledge Management, {CIKM} 2010, Toronto, Ontario, Canada, October 26-30, 2010 -
Duration: 1 Jan 2010 → …

Conference

ConferenceProceedings of the 19th {ACM} Conference on Information and Knowledge Management, {CIKM} 2010, Toronto, Ontario, Canada, October 26-30, 2010
Period1/01/10 → …

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