Fuzzy Clustering for Topic Analysis and Summarization of Document Collections

Abstract. Large document collections, such as those delivered by Internet search engines, are difficult and time-consuming for users to read and analyse. The detection of common and distinctive topics within a document set, together with the generation of multi-document summaries, can greatly ease the burden of information management. We show how this can be achieved with a clustering algorithm based on fuzzy set theory, which (i) is easy to implement and integrate into a personal information system, (ii) generates a highly flexible data structure for topic analysis and summarization, and (iii) also delivers excellent performance.

• Type: Conference
• Year: 2007
• Where: AI
• Authors: René Witte, Sabine Bergler
• Keywords: AI 2007, Artificial Intelligence, Fuzzy Set Theory, Internet Search Engines, Large Document Collections