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Title: A Distributed Agent Implementation of Multiple Species Flocking Model for Document Partitioning Clustering

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 Kmeans or the Ant clustering algorithms for data clustering. This algorithm generates a clustering of a given set of data through the embedding of the highdimensional 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.

Authors:
 [1];  [1]
  1. ORNL
Publication Date:
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States)
Sponsoring Org.:
Work for Others (WFO)
OSTI Identifier:
1003673
DOE Contract Number:  
DE-AC05-00OR22725
Resource Type:
Book
Country of Publication:
United States
Language:
English
Subject:
99 GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE; ALGORITHMS; IMPLEMENTATION; PERFORMANCE; Swarm; Bio-inspired; Clustering; Agent; Flocking; VSM.

Citation Formats

Cui, Xiaohui, and Potok, Thomas E. A Distributed Agent Implementation of Multiple Species Flocking Model for Document Partitioning Clustering. United States: N. p., 2006. Web.
Cui, Xiaohui, & Potok, Thomas E. A Distributed Agent Implementation of Multiple Species Flocking Model for Document Partitioning Clustering. United States.
Cui, Xiaohui, and Potok, Thomas E. Sun . "A Distributed Agent Implementation of Multiple Species Flocking Model for Document Partitioning Clustering". United States. doi:.
@article{osti_1003673,
title = {A Distributed Agent Implementation of Multiple Species Flocking Model for Document Partitioning Clustering},
author = {Cui, Xiaohui and Potok, Thomas E},
abstractNote = {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 Kmeans or the Ant clustering algorithms for data clustering. This algorithm generates a clustering of a given set of data through the embedding of the highdimensional 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.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Sun Jan 01 00:00:00 EST 2006},
month = {Sun Jan 01 00:00:00 EST 2006}
}

Book:
Other availability
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