User relevance feedback is usually utilized by Web systems to interpret user information needs and retrieve effective results for users. However, how to discover useful knowledge in user relevance feedback and how to wisely use the discovered knowledge are two critical problems. However, understanding what makes an individual document good or bad for feedback can lead to the solution of the pre...

This document contains a description of experiments for the 2008 Relevance Feedback track. We experiment with different amounts of feedback, including negative relevance feedback. Feedback is implemented using massive weighted query expansion. Parsimonious query expansion using only relevant documents and Jelinek-Mercer smoothing performs best on this relevance feedback track dataset. Additiona...

We study in this paper how explicit user feedback can be used by a case-based reasoning system to improve the quality of its retrieval phase. More specifically, we explore how both ranking feedback and relevance feedback can be exploited to modify the weights of case features. We propose some options to cope with each type of feedback. We also evaluate, in an interactive setting, their impact o...

This literature review provides an overview of the various topics related to using implicit feedback for information retrieval. Specific topics which are addressed are explicit relevance feedback for query expansion and its advantages and disadvantages, user behaviors that provide implicit information to a system, techniques to implement implicit feedback in systems and the advantages and disad...

Thomson Legal and Regulatory participated in the CLEF-2004 monolingual and bilingual tracks. Monolingual experiments included Portuguese, Russian and Finnish. We investigated a new query structure to handle Finnish compounds. Our main focus was bilingual search from German to French. Our approach used query translation and post-translation pseudo-relevance feedback. We compared two translation ...

In this paper, we describe a new approach to managing large image databases which we call active browsing. Active browsing integrates relevance feedback into the browsing environment, so that users can modify the database’s organization to suit the desired task. Our method is based on a similarity pyramid data structure which hierarchically organizes the database so that it can be efficiently b...