Effective Text Data Extraction using Hierarchical Clustering Technique
D. Saravanan
D. Saravanan, Faculty of Operations & Information Technology, Institute of Chartered Financial Analysts of India, Deemed University, Hyderabad, India.
Manuscript received on 08 April 2019 | Revised Manuscript received on 15 April 2019 | Manuscript Published on 24 May 2019 | PP: 373-377 | Volume-8 Issue-6S3 April 2019 | Retrieval Number: F10760486S319/19©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: Community Information Systems