@article{keyhere,
        title = {Fuzzy Clustering for Topic Analysis and Summarization of Document Collections},
        author = {René Witte and Sabine Bergler},
        journal = {Advances in Artificial Intelligence},
        pages = {476--488},
        year = 2007,
        url = {http://dx.doi.org/10.1007/978-3-540-72665-4_41},
        description = {SpringerLink - Book Chapter},
	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 ofmulti-document summaries, can greatly ease the burden of information management. We show how this can be achieved with a clusteringalgorithm 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.},
	biburl = {http://www.bibsonomy.org/bibtex/2bbdcaeb1167d2eec89427b07b510605c/renew},
	keywords = {clustering summarization fuzzy}
}