A scaleable document clustering approach for large document corpora
Information Processing and Management: an International Journal
A relevance feedback mechanism for cluster-based retrieval
Information Processing and Management: an International Journal
An investigation into the stability of contextual document clustering
Journal of the American Society for Information Science and Technology
An investigation of Zipf's Law for fraud detection (DSS#06-10-1826R(2))
Decision Support Systems
The Journal of Supercomputing
A biological text retrieval system based on background knowledge and user feedback
VDMB'06 Proceedings of the First international conference on Data Mining and Bioinformatics
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The ability to perform an exploratory search and retrieval of relevant documents from a large collection of domain-specific documents is an important requirement both in the field of medicine and other areas. In this paper, we present a unsupervised distributional clustering technique called SOPHIA. SOPHIA provides a semantically meaningful visual clustering of the document corpus in conjunction with an intuitive interactive search facility. We assess the effectiveness of SOPHIA's cluster-based information retrieval for the MEDLINE testset collection known as OHSUMED.