A Review of Text Mining Techniques & Applications

Kanak Sharma, Ashish Sharma, Dhananjay Joshi, Nikhil Vyas, Arpit Bapna

Abstract


Due to the ever increasing rate at which information is generated, text mining and its automated analysis have become the need of the hour. The paper discusses some of the developments in text mining applications, primarily reviewing techniques in the classification, summarization and analysis of text, as advocated by academia. The goal is, in essence, to ultimately turn unstructured text into useful data and information for analysis using critical methods. We introduce the paper by introducing the concept of “textual analysis” similar to text mining done using the analysis of Natural Language texts, their respective techniques in use and the open source tools in use to do so. We survey varied topics that use NLP, and also expand the horizons of this domain by devising new techniques for improving the efficiency even in limited amounts of data, improved accuracy, new methods, novel approaches, and new application areas for it, and relating to text summarization and text classification. Various text mining techniques used in text classification and summarization are reviewed, followed by the application areas of text mining being worked upon by businesses. Finally, the paper concludes by introducing “organizational text mining” and emphasizing the need for it.


Keywords


natural language processing; text mining; text classification; text summarization.

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