The Text Mining Handbook: Advanced Approaches in Analyzing Unstructured Data

by Ronen Feldman, James Sanger

Text mining tries to solve the crisis of information overload by combining techniques from data mining, machine learning, natural language processing, information retrieval, and knowledge management. In addition to providing an in-depth examination of core text mining and link detection algorithms and operations, this book examines advanced pre-processing techniques, knowledge representation considerations, and visualization approaches. Finally, it explores current real-world, mission-critical applications of text mining and link detection in such varied fields as M&A business intelligence, genomics research and counter-terrorism activities.

Genres: Computer Science, Software, Technology

424 pages, Hardcover

First published July 31, 2006

Reviews

[Chris Wood · Rating 5 out of 5]

Rarely does a popular textbook present a complex topic in an easily digestable manner without, at the same time, becoming content-less. The Text Mining handbook does an excellent job introducing the reader to text processing and data mining / machine learning techniques at a high level. While Feldman does not offer proofs and, in many cases, does not show the entire algorithm, he does do a fantastic job surveying the major techniques.

I highly recommend this book to anyone who wants to enter into the field of unstructured data mining.

[Jill · Rating 3 out of 5]

Very much a handbook and sometiems completely over my head but gave me the intro information needed for my column and for that I'm grateful.