Advances in Information Retrieval: Recent Research from the Center for Intelligent Information Retrieval(7 The Information Retrieval Series)

The NSF Center for Intelligent Information Retrieval (CIIR) was formed in the Computer Science Department of the University of Massachusetts, Amherst, in 1992. Through its efforts in basic research, applied research, and technology transfer, the CIIR has become known internationally as one of the leading research groups in the area of information retrieval. The CIIR focuses on research that results in more effective and efficient access and discovery in large, heterogeneous, distributed text and multimedia databases. The scope of the work that is done in the CIIR is broad and goes significantly beyond traditional areas of information retrieval such as retrieval models, cross-lingual search, and automatic query expansion. The research includes both low-level systems issues such as the design of protocols and architectures for distributed search, as well as more human-centred topics such as user interface design, visualization and data mining with text, and multimedia retrieval. This collection of papers from the Center for Intelligent Information Retrieval covers a wide variety of topics in the general area of information retrieval. They represent a snapshot of the state of the art in information retrieval at the turn of the century and at the end of a decade that has seen the advent of the World-Wide Web. The papers provide overviews and in-depth analysis of theory and experimental results. This book can be used as source material for graduate courses in information retrieval, and as a reference for researchers and practitioners in industry.

Table of Contents:
Combining Approaches to Information Retrieval.- The use of Exploratory Data Analysis in Information Retrieval Research.- Language Models for Relevance Feedback.- Topic Detection and Tracking: Event Clustering as a Basis for First Story Detection.- Distributed Information Retrieval.- Topic-Based Language Models for Distributed Retrieval.- The Effect of Collection Organization and Query Locality on Information Retrieval System Performance.- Cross-Language Retrieval via Transitive Translation.- Building, Testing, and Applying Concept Hierarchies.- Appearance-Based Global Similarity Retrieval of Images.

Review :
`The book makes very interesting reading for casual or serious developers of IR systems and anyone who is interested in obtaining pragmatic knowledge from text passages.' Computational Linguistics, 27:2 (2001)