Towards query log based personalization using topic models


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.

DOI: 10.1145/1871437.1871745

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@inproceedings{Carman2010TowardsQL, title={Towards query log based personalization using topic models}, author={Mark James Carman and Fabio Crestani and Morgan Harvey and Mark Baillie}, booktitle={CIKM}, year={2010} }