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A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques - 2017

A Brief Survey Of Text Mining: Classification, Clustering And Extraction Techniques

Survey Paper on Text Mining: Classification, Clustering And Extraction Techniques

Research Area:  Machine Learning

Abstract:

The amount of text that is generated every day is increasing dramatically. This tremendous volume of mostly unstructured text cannot be simply processed and perceived by computers. Therefore, efficient and effective techniques and algorithms are required to discover useful patterns. Text mining is the task of extracting meaningful information from text, which has gained significant attentions in recent years. In this paper, we describe several of the most fundamental text mining tasks and techniques including text pre-processing, classification and clustering. Additionally, we briefly explain text mining in biomedical and health care domains.

Keywords:  
Text Mining
Classification
Clustering
Extraction Techniques
biomedical
health care
Machine Learning
Deep Learning

Author(s) Name:  Mehdi Allahyari, Seyedamin Pouriyeh, Mehdi Assefi, Saied Safaei, Elizabeth D. Trippe, Juan B. Gutierrez, Krys Kochut

Journal name:  Computer Science

Conferrence name:  

Publisher name:  arXiv:1707.02919

DOI:  10.48550/arXiv.1707.02919

Volume Information: