Text mining is the analysis of data contained in natural language text. The application of text mining techniques to solve business problems is called text analytics. Text analytics have a broad description and set of responsibilities. It can add metadata to unstructured content, identify components, and convert information to structured form – to name a few. KM World brought this to our attention in their article, “Text analytics and beyond.”
The technology itself employs various approaches, including statistical, linguistic and machine learning. In its journey to extract meaningful information, it is deployed for a wide range of business purposes, from fraud detection to sentiment analysis.
Rather than focusing on just keyword searches or statistical analyses alone, text analytics incorporate a deeper understanding of language through greater semantic analysis and machine learning. This trend is moving text analytics past the traditional approaches into the realm of cognitive computing.
Melody K. Smith
Sponsored by Access Innovations, the world leader in thesaurus, ontology, and taxonomy creation and metadata application.
