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Erschienen in:
2006 | OriginalPaper | Buchkapitel
A Distributed Agent Implementation of Multiple Species Flocking Model for Document Partitioning Clustering
verfasst von : Xiaohui Cui, Thomas E. Potok
Erschienen in: Cooperative Information Agents X
Verlag: Springer Berlin Heidelberg
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The Flocking model, first proposed by Craig Reynolds, is one of the first bio-inspired computational collective behavior models that has many popular applications, such as animation. Our early research has resulted in a flock clustering algorithm that can achieve better performance than the K-means or the Ant clustering algorithms for data clustering. This algorithm generates a clustering of a given set of data through the embedding of the high-dimensional data items on a two-dimensional grid for efficient clustering result retrieval and visualization. In this paper, we propose a bio-inspired clustering model, the Multiple Species Flocking clustering model (MSF), and present a distributed multi-agent MSF approach for document clustering.