With the increasing importance of the Web and other text-heavy application
areas, the demands for and interest in both text mining and natural
language processing (NLP) have been rising. Researchers in text mining have
hoped that NLP - the attempt to extract a fuller meaning representation
from free text - can provide useful improvements to text mining
applications of all kinds.
Bringing together a variety of perspectives from internationally renowned
researchers, Natural Language Processing and Text Mining not only discusses
applications of certain NLP techniques to certain Text Mining tasks, but
also the converse, i.e. use of Text Mining to facilitate NLP. It explores a
variety of real-world applications of NLP and text-mining algorithms in
comprehensive detail, placing emphasis on the description of end-to-end
solutions to real problems, and detailing the associated difficulties that
must be resolved before the algorithm can be applied and its full benefits
realized. In addition, it explores a number of cutting-edge techniques and
approaches, as well as novel ways of integrating various technologies.
Nevertheless, even readers with only a basic knowledge of data mining or
text mining will benefit from the many illustrative examples and solutions.
Topics and features:
*Describes novel and high-impact text mining and/or natural language
*Points out typical traps in trying to apply NLP to text mining
*Illustrates preparation and preprocessing of text data – offering
practical issues and examples
*Surveys related supporting techniques, problem types, and potential
*Examines the interaction of text mining and NLP
This state-of-the-art, practical volume will be an essential resource for
professionals and researchers who wish to learn how to apply text mining
and language processing techniques to real world problems. In addition, it
can be used as a supplementary text for advanced students studying text
mining and NLP.