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.
Rezensionen / Stimmen
"Practical Text Mining with Perl is an excellent book for readers at a variety of different programming skill levels ... Bilisoly's book would serve as a good text for an introductory text mining course, and could be supplemented with lecture notes for Web mining or data mining courses." (Journal of Statistical Software, January 2009)
Reihe
Auflage
Sprache
Verlagsort
Zielgruppe
Produkt-Hinweis
Fadenheftung
Gewebe-Einband
Maße
Höhe: 260 mm
Breite: 183 mm
Dicke: 22 mm
Gewicht
ISBN-13
978-0-470-17643-6 (9780470176436)
Schweitzer Klassifikation
Roger Bilisoly, PhD, is an Assistant Professor of Statistics at Central Connecticut State?University, where he developed and teaches a new graduate-level course in text mining for the school's data mining program.
Autor*in
Central Connecticut State University
List of Figures.
List of Tables.
Preface.
Acknowledgments.
1. Introduction.
2. Text Patterns.
3. Quantitative Text Summaries.
4. Probability and Text Sampling.
5. Applying Information Retrieval to Text Mining.
6. Concordance Lines and Corpus Linguistics.
7. Multivariate Techniques with Text.
8. Text Clustering.
9. A Sample of Additional Topics.
Appendix A. Overview of Perl for Text Mining.
Appendix B. Summary of R used in this Book.
References.
Index.
