Relevance-based language modelling for recommender systems
نویسندگان
چکیده
منابع مشابه
Relevance-based language modelling for recommender systems
Relevance-Based Language Models, commonly known as Relevance Models, are successful approaches to explicitly introduce the concept of relevance in the statistical Language Modelling framework of Information Retrieval. These models achieve state-of-the-art retrieval performance in the pseudo relevance feedback task. On the other hand, the field of Recommender Systems is a fertile research area w...
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Language Models have been traditionally used in several fields like speech recognition or document retrieval. It was only recently when their use was extended to collaborative Recommender Systems. In this field, a Language Model is estimated for each user based on the probabilities of the items. A central issue in the estimation of such Language Model is smoothing, i.e., how to adjust the maxim...
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1. Introduction This paper addresses three questions about the Language Modelling (LM) approach to information retrieval. These questions are about LM and relevance. They arise because relevance has always been taken as fundamental to information retrieval (see, e.g. Saracevic, 1975, or Mizzaro, 1997). Thus from the standpoint of retrieval theory, the presumption has been that as relevance is t...
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ژورنال
عنوان ژورنال: Information Processing & Management
سال: 2013
ISSN: 0306-4573
DOI: 10.1016/j.ipm.2013.03.001