Browsing-based User Language Models for Information Retrieval
Fernando G. Diaz, James Allan · 2003
Traditional information retrieval systems have ignored the potential improvement in precision provided by personalization. We present a study of the behavior and evaluation of personalized information retrieval systems. We describe the construction of a collection of user web browsing data for application in retrieval evaluation. Several novel techniques for personalizing retrieval are presented and evaluated. Although performance is mixed, results point to the need to develop other algorithms within this evaluation framework.