Ryan Rosario

English

Research Papers in Economics

JSS Journal of Statistical Software
January 2008, Volume 29, Book Review 9. http://www.jstatsoft.org/
Reviewer: Ryan Rosario
University of California at Los Angeles
Practical Text Mining with Perl
Roger Bilisoly
John Wiley & Sons, Hoboken, NJ, 2008.
ISBN 978-0-470-17643-6. 296 pp. USD 89.95.
http://www.wiley.com/WileyCDA/WileyTitle/productCd-0470176431.html
Introduction
Bilisoly's Practical Text Mining with Perl is the fourth volume in the Wiley series on data
mining and discusses the application of Perl to the eld of text mining. Text mining is a
subdiscipline of data mining that focuses on the extraction of patterns from text. The author
divides this volume into four main topics which he denotes as transitions: a blend of Perl basics
and pattern extraction, probability and statistics applied to information theory, methods for
multivariate analysis, and miscellaneous topics. These topics span nine chapters. The author
concludes each chapter with a comprehensive set of exercises that use the material introduced
in the chapter. Some of the exercises are basic comprehension exercises, while others involve
critical thinking and a thirst for programming. Some exercises also provide the beginner
with strategies for learning programming languages such as Perl. This book focuses on the
use of Perl for mining, cleaning and basic analysis and uses R for statistical analysis and
visualization.
Book content
Perl syntax and concepts are cleverly integrated with text mining tasks throughout the book.
Perl lessons do not follow the typical sequence of lessons one would expect from a Perl pro-
gramming text (such as, e.g., Wall, Christiansen, and Orwant 2000). Rather, concepts are
introduced and discussed as necessary to the task at hand. Of course, any book cannot cover
all of the issues related to text mining, so the author introduces several references in each
chapter with a synopsis of what is discussed in the reference. The organization of the book, as
well as the numerous references included provides an inspiring experience for the reader. Ex-
ercises sometimes involve Perl concepts that have not yet been discussed to keep the advanced
reader busy. Chapters also include various code snippets and programs. The author describes
the syntax in each line and clearly explains how the syntax is used. Discussion about the2 Practical Text Mining with Perl
various challenges in text mining inspires the reader to think critically about programming
and the iterative nature of rening code.
Chapter 1 presents the reader with a breakdown of the content in the book as well as some
helpful advice for reading the book for all programming ability levels. Chapter 2, Text Pat-
terns, dives into regular expressions. This section contains a lot of material that moves at
a quick pace, but there are enough explanations and references for beginners to become ac-
quainted with the concepts. This chapter also explores the various complications of text
mining, and how regular expressions can be further rened to minimize false matches and
missed matches in text. Topics include pattern matching, match variables, substitutions,
greediness, backreferences and lookaround. Perl concepts include basic le input/output,
loops, tokenization, sentence segmentation.
Chapter 3, Quantitative Text Summaries, introduces Perl data types and the usage of numeric
variables and data structures for token counting and text storage. Concepts include scalars,
arrays and hashes, as well as predened functions and subsetting methods for these data
types. Complex data structures such as references, pointers, and arrays of arrays are briey
described.
Chapter 4, Probability and Text Sampling, introduces the denition and concept of probability.
Introductory discussion uses coin ipping as motivation and progresses to using probabilities
to describe text. This chapter introduces conditional probability, independence, random
variables, mean, variance, the eect of sample size, and the concept of a sampling distribution.
Chapter 4 also introduces the bag of words model.
Chapter 5, Applying Information Retrieval to Text Mining, discusses the vector space model
including the term document matrix, cosine distance, and inverse document frequency. The
author begins by reviewing the use of Perl for counting and is introduced to Perl subroutines
to create functions of counts. The author also introduces the reader to importing modules.
This is the rst chapter that introduces the reader to R syntax. The author uses R for basic
tasks such as matrix multiplication and calculating the cosine distance.
Chapter 6, Concordance Lines and Corpus Linguistics, discusses statistical sampling and the
challenges of extracting meaning from text including word morphologies, collocations and
phrasal verbs. Readers learn to write more complex subroutines to clean and display text as
well as describe it quantitatively.
Chapter 7, Multivariate Techniques with Text requires more background in statistics than
previous chapters, and immediately mentions principal components analysis (PCA) in the
introduction. The second section takes a step backwards and introduces the reader to basic
statistics such as the mean and standard deviation as well as z scores, correlations, covari-
ances and cosines. The author provides a quick review of basic linear algebra for correlation
matrices. The fourth section is rather short and discusses PCA but does not clearly describe
the connection between PCA and text analysis. Chapter 7 concludes with a brief note of
factor analysis and the author describes his preference for PCA over factor analysis. Bilisoly
uses R throughout the entire chapter.
Chapter 8, Text Clustering introduces k-means and other clustering techniques with R. Bilisoly
discusses the use of PCA for clustering as well as hierarchical clustering and the dendogram.
Classication is discussed througout the chapter, but is not discussed thoroughly due to the
lack of availability of public domain training sets.
Chapter 9, A Sample of Additional Topics, wraps up this volume in data mining with someJournal of Statistical Software { Book Reviews 3
other topics the author did not feel t into other parts of the book. Topics include Perl modules
for text mining, tagging, analysis of text in languages other than English, permutation tests
and hypothesis testing.
The author also provides reference appendices on Perl and R.
Conclusion
Practical Text Mining with Perl is an excellent book for readers at a variety of dierent
programming skill levels. In particular, readers with some programming background in non-
scripting languages, graduate students, and the\ambitious beginner"that is willing to put in
the extra time to develop a good foundation, will nd this book very useful. This book does
not assume any programming ability, however, there are sections that are heavy and detail-
oriented that can overwhelm readers that have never seen a scripting language or the concept
of regular expressions. To curtail these diculties, the author provides several references
throughout the chapter, which are summarized at the end of the chapter. Readers can refer
to any of these references to delve deeper into the content of the chapter, or to clarify or revisit
any concepts that may have been dicult to understand. 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. On the other hand, the author's choice of Perl
strongly dates this volume, as other languages, particularly Python, seem to have gained more
traction for text mining recently.
References
Wall L, Christiansen T, Orwant J (2000). Programming Perl. 3rd edition. O'Reilly Media,
Inc., Sebastopol, CA.
Reviewer:
Ryan Rosario
University of California at Los Angeles
Department of Statistics
Los Angeles, CA 90095, United States of America
E-mail: rosario@stat.ucla.edu
URL: http://www.stat.ucla.edu/~rosario/
Journal of Statistical Software http://www.jstatsoft.org/
published by the American Statistical Association http://www.amstat.org/
Volume 29, Book Review 9 Published: 2008-01-14
January 2008

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