Fuzzy multiset model and methods of nonlinear document clustering for information retrieval. (English) Zbl 1109.68437
Torra, Vicenç (ed.) et al., Modeling decisions for artificial intelligence. First international conference, MDAI 2004, Barcelona, Catalonia, Spain, August 2–4, 2004. Proceedings. Berlin: Springer (ISBN 3-540-22555-2/pbk). Lecture Notes in Computer Science 3131. Lecture Notes in Artificial Intelligence, 273-283 (2004).
Summary: As a model of information retrieval on the WWW, a fuzzy multiset model is overviewed and a family of fuzzy document clustering algorithms is developed. The fuzzy multiset model is enhanced in order to adapt clustering applications. The standard proximity measure of the cosine coefficient is generalized in the multiset model, and two basic objective functions of fuzzy \(c\)-means are considered. Moreover two methods of handling nonlinear classification is proposed: introduction of a cluster volume variable and a kernel trick used in support vector machines. A crisp \(c\)-means algorithm and clustering by competitive learning are also studied. A numerical example based on real documents is shown.
For the entire collection see [Zbl 1056.68016].
For the entire collection see [Zbl 1056.68016].
MSC:
| 68P20 | Information storage and retrieval of data |
