A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques
Computation and Language
2017-07-31 v2 Artificial Intelligence
Information Retrieval
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.
Cite
@article{arxiv.1707.02919,
title = {A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques},
author = {Mehdi Allahyari and Seyedamin Pouriyeh and Mehdi Assefi and Saied Safaei and Elizabeth D. Trippe and Juan B. Gutierrez and Krys Kochut},
journal= {arXiv preprint arXiv:1707.02919},
year = {2017}
}
Comments
some of References format have updated