Text analytics

The term text analytics describes a set of linguistic, statistical, and machine learning techniques that model and structure the information content of textual sources for business intelligence, exploratory data analysis, research, or investigation. The term is roughly synonymous with text mining; indeed, Prof. Ronen Feldman modified a 2000 description of "text mining" notably life-sciences research and government intelligence.

Text analytics involves information retrieval, lexical analysis to study word frequency distributions, pattern recognition, tag/annotation, information extraction, data mining techniques including link and association analysis, visualization, and predictive analytics. The overarching goal is, essentially, to turn text into data for analysis via application of natural language processing (NLP) and analytical methods.

The termalso describes that application of text analytics to respond to businessproblems, whether independently or in conjunction with query and analysis of fielded, numerical data. It is a truism that 80 percent of business-relevant information originates in unstructured form, primarily text. These...
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