Effective Text Data extraction using Hierarchical Clustering Technique
D.Saravanan
D.Saravanan, Department of Operations & IT, ICFAI Business School IBS, Hyderabad (Telangana), India.
Manuscript received on 29 May 2019 | Revised Manuscript received on 11 June 2019 | Manuscript Published on 22 June 2019 | PP: 741-743 | Volume-8 Issue-3S, February 2019 | Retrieval Number: C11580283S19/19©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In the digital era, text plays an important role it has come forward in a variety of data mining applications. In text mining, information are extracted and clustered from an unstructured data-set. For efficient retrieval many procedures are involved. Text mining is used in a variety of data mining approaches such as market research, survey research, statistical process and more. The objective of this paper is to analyze the relevant data that leads to a novel multidimensional data mining package. The method is based on the use of text mining. Data collection and analysis of data related to the text of a real-world test are also presented
Keywords: Text Mining, Clusters, Text Clusters, Segmentation, Text Retrieval, Hierarchical Cluster.
Scope of the Article: Clustering