Natural Language Processing for Online Applications: Text Retrieval, Extraction, and Categorization (Natural Language Processing, 5) Review

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Natural Language Processing for Online Applications: Text Retrieval, Extraction, and Categorization (Natural Language Processing, 5) ReviewWork on Natural Language processing has been going on for at least
thirty years. In the past most natural language processing (NLP)
applications where mainly in the research realm. The rapid
increase in computer processing power and disk storage capacity
have moved NLP from research into the area of applied science.
This gives NLP the feel of a new and vibrant area. Progress is
being made rapidly, but the research literature can be difficult
for someone who has no experience with NLP. Simply learning the
terminology can be time consuming.
This book by Jackson and Moulinier provides an excellent overview
of several sub-areas of NLP applied to natural language text.
Both Jackson and Moulinier have been involved in implementing
NLP applications in a commercial context, so there is a
some concentration on applying NLP in real applications, rather
than artificial contexts like the Message Understand Conference
data set.
I purchased this book for its coverage of Information Extraction.
Along with this book I read a number of papers from the research
literature. One paper I found particularly interesting was
a paper on the FASTUS NLP system developed by researchers at
SRI. I was very happy to see that FASTUS and finite automata
approaches were covered in more detail in this book.
For my purposes I would have liked a book that moved from
an overview of various NLP applications to more implementation
detail. For example, while I think that I understand
push down automata from working on parsers for compilers,
I don't fully understand them in the NLP context. This book
did not go into enough detail to make this clear.
I cannot really offer this lack of detail as a criticism
since I don't believe that it was the authors intention to
provide this level of detail. Their objective is to provide
a detailed overview and I think that they succeeded in doing
this. A book that provided this overview with
details on implementation would be much longer, perhaps the
size of Manning and Schutze's excellent book "Foundations of
Natural Language Processing" (Manning and Schutze provide
a great deal of detail, but they do not cover information
extraction).Natural Language Processing for Online Applications: Text Retrieval, Extraction, and Categorization (Natural Language Processing, 5) Overview

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Practical Text Mining with Perl (Wiley Series on Methods and Applications in Data Mining) Review

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Practical Text Mining with Perl (Wiley Series on Methods and Applications in Data Mining) ReviewNot just one of the best Perl books I've ever read but one of the best programming books in general.
The author does an excellent job building up your Perl skill set from basic introduction to complex regexs.
The fact that all the examples are from the literary works of Edgar Allan Poe doesn't hurt either.
Very well written and makes an excellent reference book later on A++Practical Text Mining with Perl (Wiley Series on Methods and Applications in Data Mining) OverviewProvides 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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