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Text mining application: 10 examples improving our today life


The following 10 text mining examples demonstrate how practical application of unstructured data management techniques can impact not only your organizational processes, but also your ability to be competitive. Text mining can be used to make the large quantities of unstructured data accessible and useful, thereby generating not only value, but delivering ROI from unstructured data management as we've seen with applications of text mining for Risk Management Software and Cybercrime applications. Through techniques such as categorization, entity extraction, sentiment analysis and others, text mining extracts the useful information and knowledge hidden in text content. In the business world, this translates in being able to reveal insights, patterns and trends in even large volumes of unstructured data. In fact, it's this ability to push aside all of the non-relevant material and provide answers that is leading to its rapid adoption, especially in large organizations.

Text Mining 101: Mining Information From A Resume


This article demonstrates a framework for mining relevant entities from a text resume. It shows how separation of parsing logic from entity specification can be achieved. Although only one resume sample is considered here, the framework can be enhanced further to be used not only for different resume formats, but also for documents such as judgments, contracts, patents, medical papers, etc. Majority of world's unstructured data is in the textual form. To make sense of it, one must, either go through it painstakingly or employ certain automated techniques to extract relevant information. Looking at the volume, variety and velocity of such textual data, it is imperative to employ Text Mining techniques to extract the relevant information, transforming unstructured data into structured form, so that further insights, processing, analysis, visualizations are possible.

Software: Text Mining

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Text-mining software is one of the front-line tools that the government is now using to tease out valuable connections. These specialized search engines can quickly sift through mountains of unstructured text anything that's not carefully arranged in a database or spreadsheet and pull out the meaningful stuff. They can infer relationships within data that are not stated explicitly. It is something we do all the time automatically but is enormously complicated for computers. "We bridge the gap between information and action," says Barak Pridor, CEO of ClearForest, a text-mining company.