In order to minimize redundancy and optimize coverage of multiple user interests, search engines and recommender systems aim to diversify their set of results. To date, these dive...
- We investigate extensions of the classical measurement of effectiveness in information retrieval systems, precision and recall, to situations where the answer is modeled by a fuz...
This article explores how to develop complex data driven user models that go beyond the bag of words model and topical relevance. We propose to learn from rich user specific info...
This paper proposes extending semi-supervised learning by allowing an ongoing interaction between a user and the system. The extension is intended to not only to speed up search fo...
Abstract. A key challenge in information retrieval is the use of contextual evidence within ad-hoc retrieval. Our contribution is particularly based on the belief that contextual r...