Provides readers with the methods, algorithms, and means to perform
text mining tasks
This book is devoted to the fundamentals of text mining using
Perl, an open-source programming tool that is freely available via
the Internet (www.perl.org). It covers mining ideas from several
perspectives--statistics, data mining, linguistics, and information
retrieval--and provides readers with the means to successfully
complete text mining tasks on their own.
The book begins with an introduction to regular expressions, a
text pattern methodology, and quantitative text summaries, all of
which are fundamental tools of analyzing text. Then, it builds upon
this foundation to explore:
Probability and texts, including the bag-of-words model
Information retrieval techniques such as the TF-IDF similarity
measure
Concordance lines and corpus linguistics
Multivariate techniques such as correlation, principal
components analysis, and clustering
Perl modules, German, and permutation tests
Each chapter is devoted to a single key topic, and the author
carefully and thoughtfully introduces mathematical concepts as they
arise, allowing readers to learn as they go without having to refer
to additional books. The inclusion of numerous exercises and
worked-out examples further complements the book's student-friendly
format.
Practical Text Mining with Perl is ideal as a textbook for
undergraduate and graduate courses in text mining and as a
reference for a variety of professionals who are interested in
extracting information from text documents.
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