Study of Text Mining Using Hybrid Agglomerative Clustering With ACO Algorithms
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

Research Paper | Computer Science & Engineering | India | Volume 3 Issue 8, August 2014

Study of Text Mining Using Hybrid Agglomerative Clustering With ACO Algorithms

Manpreet Kaur, Sukhpreet Kaur

Textual document clustering technique was introduced in the area of text mining. The two important main goals in document clustering are achieving high performance or efficiency and obtaining highly accurate data clusters that are closed to their natural classes or textual document cluster quality To enhance this work, we are going to propose a new hybrid clustering algorithm using Agglomerative Clustering with ACO (Ant Colony Optimization) algorithm. ACO algorithms are a class of algorithms inspired by the observation of real ants. In this paper single linkage and K-nearest Neighbor are used to achieve the high efficiency and high quality. And also used four parameters recall, precision, time, document are calculated for high efficiency and high quality.

Keywords: Data Mining, Text Mining in Clustering, Ant Colony Optimization ACO, Hierarchical Clustering, Single-Linkage Agglomerative Clustering

Edition: Volume 3 Issue 8, August 2014

Pages: 786 - 790

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Manpreet Kaur, Sukhpreet Kaur, "Study of Text Mining Using Hybrid Agglomerative Clustering With ACO Algorithms", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=10081406, Volume 3 Issue 8, August 2014, 786 - 790

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