At SIGIR 2006, there is a two-day workshop about Personal Information Management (PIM). We submit a paper about capturing and exploiting personal search history to improve retrieval accuracy. Here is the abstract of the submission.
Personal search history is an important type of personal information that is critical for learning a user’s interests and information needs and can be exploited to improve the search service for a user. In this paper, we describe our recent work on User-Centered Adaptive Information Retrieval (UCAIR), which aims at capturing personal search history with a client-side search agent and exploiting the history information to help a user optimize search results.
We propose a decision theoretic framework and develop techniques for implicit user modeling based on a user’s personal search history. We propose several context-sensitive retrieval algorithms based on statistical language models to combine the personal search history with the current query for better ranking of documents. Using these techniques, we have developed an intelligent client-side web search agent, i.e., the UCAIR search agent, which can automatically capture a user’s personal search history, store it in XML format on the local disk, and exploit it to provide personalized search.
