A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques
July 10, 2017 ยท The Cartographer ยท ๐ arXiv.org
"No code URL or promise found in abstract"
"Title-pattern auto-detect: A Brief Survey of Text Mining: Classification, Clustering and Extraction Techniques"
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Authors
Mehdi Allahyari, Seyedamin Pouriyeh, Mehdi Assefi, Saied Safaei, Elizabeth D. Trippe, Juan B. Gutierrez, Krys Kochut
arXiv ID
1707.02919
Category
cs.CL: Computation & Language
Cross-listed
cs.AI,
cs.IR
Citations
566
Venue
arXiv.org
Last Checked
1 day ago
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.
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