General information retrieval systems are designed to serve all users without considering individual needs. In this paper, we propose a novel approach to personalized search. It c...
Yuanhua Lv, Le Sun, Junlin Zhang, Jian-Yun Nie, Wa...
Information retrieval systems have typically concentrated on retrieving a set of documents which are relevant to a user's query. This paper describes a system that attempts t...
Abstract. We design and validate simulators for generating queries and relevance judgments for retrieval system evaluation. We develop a simulation framework that incorporates exis...
Bouke Huurnink, Katja Hofmann, Maarten de Rijke, M...
Abstract In this paper, we describe our Question Answering (QA) system called QUANTUM. The goal of QUANTUM is to find the answer to a natural language question in a large document ...
We study a novel problem of social context summarization for Web documents. Traditional summarization research has focused on extracting informative sentences from standard docume...
Zi Yang, Keke Cai, Jie Tang, Li Zhang, Zhong Su, J...