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| Data Stream Clustering Based on Immune Principle |
| WANG Shu-Yun1,2, ZHANG Cheng-Hong3, HAO Xiu-Lan1, HU Yun-Fa1 |
1. Department of Computing Information and Technology, Fudan University, Shanghai 200433
2.School of Public Administration, Fuzhou University, Fuzhou 350002
3.Department of Information Management and Information System, Fudan University,Shanghai 200433 |
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Abstract The learning based on immune principle adapts well to the dynamic environment, and thus it can be applied to the data stream processing which is dynamic and requires high-speed processing. Therefore, an algorithm of clustering data streams based on immune principle is proposed, namely AIN-STREAM. The proposed algorithm can track the evolving clusters on noisy data sets. AIN-STREAM is capable of adjusting the recognition zone of B-cells automatically according to the requirement of users by creating and maintaining the B-Cell feature vectors. Thus, the stability of the clustering result is ensured. Theoretical analysis and comprehensive experimental results demonstrate that AIN-STREAM is superior over other immune principle based clustering algorithms under the circumstance of similar clustering results. Moreover, the results show that AIN-STREAM has a high clustering quality.
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Received: 21 December 2007
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2009, Vol. 22 
