A distributed agent implementation of multiple species Flocking model for document partitioning clustering

Xiaohui Cui, Thomas E. Potok

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

25 Scopus citations

Abstract

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.

Original languageEnglish
Title of host publicationCooperative Information Agents X - 10th International Workshop, CIA 2006. Proceedings
PublisherSpringer Verlag
Pages124-137
Number of pages14
ISBN (Print)354038569X, 9783540385691
DOIs
StatePublished - 2006
Event10th International Workshop on Cooperative Information Agents, CIA 2006 - Edinburgh, United Kingdom
Duration: Sep 11 2006Sep 13 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4149 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference10th International Workshop on Cooperative Information Agents, CIA 2006
Country/TerritoryUnited Kingdom
CityEdinburgh
Period09/11/0609/13/06

Keywords

  • Agent
  • Bio-inspired
  • Clustering
  • Flocking
  • Swarm
  • VSM

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