Relevance Feedback and Personalization: A Language Modeling Perspective.
W. Bruce Croft, Stephen Cronen-Townsend, Victor P. Lavrenko · 2001
Many approaches to personalization involve learning short-term and long-term user models. The user models provide context for queries and other interactions with the information system. In this paper, we discuss how language models can be used to represent context and support context-based techniques such as relevance feedback and query disambiguation. 1. Overview From some perspectives, personalization has been studied in information retrieval for some time. If the goal of personalization is to improve the effectiveness of information access by adapting to individual users' needs, then techniques such as relevance feedback and filtering would certainly be considered to support personalization. There has also been considerable research done, mostly in the 1980s, on user modeling for information retrieval. This research had essentially the same goal as current research on personalization, which is to build a model of a user's interests and preferences over time. Filtering systems, too...