A common major limitation of existing retrieval models and systems is that the retrieval decision is, in general, based solely on the query and document collection; information about the actual user and the search context is largely ignored. This limitation makes the retrieval performance of existing IR systems inherently non-optimal, as seen clearly in the following two cases:
- Different users may use exactly the same query to search for different information, but existing IR systems return the same results for these users. For example, the query “IR applications” on Google returns a mixture of documents about “information retrieval” applications and “infrared” applications, as “IR” can be an acronym for both information retrieval and infrared. Without considering the actual user it is inherently impossible to know which sense “IR” refers to.
- A user’s information needs may change over time. The same user may sometimes use “java” to mean the Java island and some other times use “java” to mean the programming language. Without recognizing the search context, it would be again inherently impossible to recognize the correct sense.
It is therefore clear that an optimal retrieval system must incorporate both user information and search context into the retrieval decision process.
The UCAIR ( pronounced as “you care”, means User Centered Adaptive Information Retrieval) project seeks to break this limitation of the existing retrieval methods and formally develop a new retrieval paradigm called user-centered adaptive information retrieval (UCAIR), in which user information and search context are both exploited to improve retrieval performance.
Here is a paper which will be published in CIKM 2005 . The paper is Implicit User Modeling for Personalized Search by Xuehua Shen, Bin Tan, and ChengXiang Zhai. There are two main contributions of this paper. One is to propose a decision theoretic framework and develop techniques for implicit user modeling in information retrieval. The other is to develop and evaluate a client-side personalized search agent UCAIR.
