Advanced Text Mining & Natural Language Processing

Authors(2) :-Kamal M, Dr. R. Chinnaiyan

In the data driven world it is important for the organization to make important business decisions. Analytics helps in achieving the goals, Business analysts and data analyst work together for providing overall insights with historical data that has been generated by the organization. Tackling with the quantitative data has N numbers of methodologies. When it comes with qualitative data business analysts & data analysts face difficulties tackling huge amount of textual data and there are no proper techniques. To overcome these problems there is a techniques called text analytics. Text analytics always deals with textual data, refers to the representation, processing and modeling of the textual data to derive insights. An important component of text analysis is text mining, the process of discovering relationship and interesting patterns in the large text collections and extraction of meaningful information from the unstructured data can either enrich the customer like and dislike and new product sentiment for all of these tasks text analytics plays a vital role in business.

Authors and Affiliations

Kamal M
PG Scholar , Department of MCA, New Horizon College Of Engineering, Bangalore, Karnataka, India
Dr. R. Chinnaiyan
Professor, Department of MCA, New Horizon College of Engineering, Bangalore, Karnataka, India

Natural Language Processing, Text Mining, NLP

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  2. M.Hu and B.liu, "mining and summarization, International conference on knowledge Discovery and data mining,pp.168-177,2004

Publication Details

Published in : Volume 3 | Issue 4 | March-April 2018
Date of Publication : 2018-04-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 342-345
Manuscript Number : CSEIT1833211
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Kamal M, Dr. R. Chinnaiyan, "Advanced Text Mining & Natural Language Processing", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 4, pp.342-345, March-April-2018.
Journal URL : http://ijsrcseit.com/CSEIT1833211

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