Towards personalized distributed information retrieval

Abstract

Our aim is to investigate if and how the performance of Distributed Information Retrieval (DIR) systems can be improved through personalization. Toward this aim we are building a testbed of document collections and corresponding personalized relevance judgments. In this paper we discuss our intended approach for personalizing the three different phases of the DIR process. We also describe the test collection we are building and discuss our methodology for evaluating personalized DIR using relevance information taken from social bookmarking data.