Machine Learning Times
Machine Learning Times
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PAW Preview Video: Evan Wimpey, Director of Strategic Analytics at Elder Research
 In anticipation of his upcoming presentation at Deep Learning...
Podcast: P-Hacking—How to Know Your Predictive Discovery is Conclusive
  Welcome to the next episode of The Machine Learning...
PAW Preview Video: Piotr Wygocki, Ph.D., CEO & Co-Founder at MIM Solutions
 In anticipation of his upcoming presentation at Predictive Analytics...
PAW Preview Video: James Taylor, Decision Management Solutions
 In anticipation of his upcoming presentation at Predictive Analytics...
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Presently, text mining is in a loosely organized set of competing technologies with no clear dominance among them. This book chapter organizes text analytics methods as seven complementary practice areas, showing how to select amongst them for your objectives.

We can relate these technologies to seven different practice areas in text mining that are covered in the chapters in this book. In summary, this book is strongest in the practice area of document classification, solid in concept extraction and document clustering, reasonably useful on web mining, light on information extraction and natural
language processing, and almost silent on the (most popular) practice area of search and information retrieval.

Download your Free Book Chapter on Text Mining here

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