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ASME Press Select Proceedings
International Conference on Computer Technology and Development, 3rd (ICCTD 2011)
By
Jianhong Zhou
Jianhong Zhou
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ISBN:
9780791859919
No. of Pages:
2000
Publisher:
ASME Press
Publication date:
2011

This paper presents a survey of evolutionary approach for Clustering and how Genetic Algorithm is applied to different problem domains in the field of Information Retrieval. The paper is original in two main aspects first it gives an overview of evolutionary approach for clustering and information retrieval and second it suggests a novel evolutionary approach which serves both the areas of Clustering and Information Retrieval by developing a single Genetic Algorithm. Conventional clustering algorithms are sensitive to the choice of cluster center. Such a partition is insufficient to represent many real situations. To improve the performance of clustering algorithm, Genetic Algorithms is applied to clustering algorithms. Genetic Algorithms are robust in searching a multidimensional space to find optimal solution. This paper tries to reflect the research profile of this area by focusing more on how Evolutionary Algorithms can effectively work in forming clusters and improving retrieval performance.

Abstract
Keywords:
1. Introduction
2. Evolutionary Approach for Clustering and Information Retrieval
3. Proposed Work:
4. Acknowledgement
5. Summaries
References
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