Personalizing information retrieval using task features, topic knowledge, and task product

摘要

Personalization of information retrieval tailors search towards individual users to meet their particular information needs. Personalization systems obtain additional information about users and their contexts beyond the queries they submit to the systems, and use this information to bring the desired documents to top ranks. The additional information can come from various sources: user preferences, user behaviors, contexts, etc. [1] To avoid users taking extra effort in providing explicit preferences, most personalization approaches have adopted an implicit strategy to obtain users' interests from their behaviors and/or contexts, such as query history, browsing history, and so on.