- Title
- Simplifying and improving ant-based clustering
- Creator
- Tan, Swee; Ting, Kaiming; Teng, Shyh
- Date
- 2011
- Type
- Text; Conference paper
- Identifier
- http://researchonline.federation.edu.au/vital/access/HandleResolver/1959.17/160034
- Identifier
- vital:12100
- Identifier
-
https://doi.org/10.1016/j.procs.2011.04.006
- Identifier
- ISBN:1877-0509
- Abstract
- Ant-based clustering (ABC) is a data clustering approach inspired from cemetery formation activities observed in real ant colonies. Building upon the premise of collective intelligence, such an approach uses multiple ant-like agents and a mixture of heuristics, in order to create systems that are capable of clustering real-world data. Many recently proposed ABC systems have shown competitive results, but these systems are geared towards adding new heuristics, resulting in increasingly complex systems that are harder to understand and improve. In contrast to this direction, we demonstrate that a state-of-the-art ABC system can be systematically evaluated and then simplified. The streamlined model, which we call SABC, differs fundamentally from traditional ABC systems as it does not use the ant-colony and several key components. Yet, our empirical study shows that SABC performs more effectively and effciently than the state-of-the-art ABC system.
- Publisher
- Elsevier Ltd
- Relation
- 11th International Conference on Computational Science, ICCS 2011; Singapore, Singapore; 1st-3rd June 2011, published in Procedia Computer Science Vol. 4, p. 46-55
- Rights
- http://creativecommons.org/licenses/by-nc-nd/3.0/
- Rights
- Copyright © 2011 Published by Elsevier Ltd. Open access under CC BY-NC-ND license.
- Rights
- Open Access
- Rights
- This metadata is freely available under a CCO license
- Subject
- 08 Information and Computing Sciences; 10 Technology; Data Clustering; Ant-Based Clustering; Swarm-Based Clustering
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