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What is Flocking Model

Handbook of Research on Text and Web Mining Technologies
The Flocking Model is a bio-inspired computational model for simulating the animation of a flock of entities. The Flocking model was first proposed by Craig Reynolds in 1987.
Published in Chapter:
Swarm Intelligence in Text Document Clustering
Xiaohui Cui (Oak Ridge National Laboratory, USA)
Copyright: © 2009 |Pages: 16
DOI: 10.4018/978-1-59904-990-8.ch010
In this chapter, we introduce three nature inspired swarm intelligence clustering approaches for document clustering analysis. The major challenge of today’s information society is being overwhelmed with information on any topic they are searching for. Fast and high-quality document clustering algorithms play an important role in helping users to effectively navigate, summarize, and organize the overwhelmed information. The swarm intelligence clustering algorithms use stochastic and heuristic principles discovered from observing bird flocks, fish schools, and ant food forage. Compared to the traditional clustering algorithms, the swarm algorithms are usually flexible, robust, decentralized, and self-organized. These characters make the swarm algorithms suitable for solving complex problems, such as document clustering.
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