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Machine learning is the new search (part 3)

Jan Scholtes |August 10, 2017|Read time: 1 min

With the ever-growing volumes of data, machine learning methods designed to automate data analysis are indispensable.

Finding what you did not know - topic modelling and clustering

Topic Modelling and Cluster Analysis are two approaches to text-mining. A topic model is used to statistically explore abstract concepts (topics) that occur within a set of documents. Cluster analysis uses perceived relation between various groups of objects to create new sub-groups (clusters). These documents are ideal to submit for Machine Learning.

ZyLAB’s solutions use Topic Modeling to automatically generate an overview of the most used concepts or topics in a text collection. These algorithms automatically find the most dominant topics in a document set and use for each topic the best words to describe them. This works completely un-supervised. By clustering and visualizing the found topics in a hierarchical tree or by using an interactive Word Wheel, you get immediately a clear overview of the dominant topics.

Topic modeling is a useful method that enhances the users’ ability to interpret large volumes of information. With these techniques, you can actually find relevant documents even if you did not really know what words or topics to look for.


All blogs in this "Machine Learning is the New Search" series: PART 1 | PART 2 | PART 3

Jan Scholtes
Johannes (Jan) C. Scholtes, Ph.D. is Chairman and Chief Strategy Officer of ZyLAB. Scholtes, who was the company’s President and CEO from 1989 to 2009, shaped ZyLAB as an Information Management powerhouse across the globe. With his leadership and vision, ZyLAB is a partner for the United Nations War Crime Tribunals, FBI-Enron investigations, and the United States White House Executive Office of the President.

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