Join Amazon Prime and ship Two-Day for free and Overnight for $3.99. Already a member? Sign in.

Learning to Classify Text Using Support Vector Machines and over 300,000 other books are available for Amazon Kindle � Amazon�s new wireless reading device. Learn more

Quantity:

More Buying Choices

27 used & new from $134.09

Have one to sell? Sell yours here

Share with Friends

Share your own customer images

Search inside this book

Start reading Learning to Classify Text Using Support Vector Machines on your Kindle in under a minute. Don�t have a Kindle? Get yours here.

Learning to Classify Text Using Support Vector Machines: Methods, Theory and Algorithms (The Springer International Series in Engineering and Computer Science) (Hardcover)

by Thorsten Joachims (Author) "With the rapid growth of the World Wide Web, the task of classifying natural language documents into a predefined set of semantic categories has become..." (more)
Key Phrases: learning text classifiers, transductive approach, transductive setting, Nervous System, Chunking Minimum, Cornell University (more...)

5.0 out of 5 stars See all reviews (2 customer reviews)

List Price:	$175.00
Price:	$157.50 & this item ships for FREE with Super Saver Shipping. Details
You Save:	$17.50 (10%)

Upgrade this book for $26.60 more, and you can read, search, and annotate every page online. See details

In Stock.
Ships from and sold by Amazon.com. Gift-wrap available.

Want it delivered Tuesday, July 14? Choose One-Day Shipping at checkout. Details

18 new from $134.09 9 used from $141.41

Also Available in:	List Price:	Our Price:	Other Offers:
Kindle Edition (Kindle Book)		$127.20

Frequently Bought Together

Customers Who Bought This Item Also Bought

An Introduction to Support Vector Machines and Other Kernel-based Learning Methods

by Nello Cristianini

4.1 out of 5 stars (9) $64.79

Pattern Recognition and Machine Learning (Information Science and Statistics)

by Christopher M. Bishop

4.0 out of 5 stars (42) $62.89

Learning with Kernels: Support Vector Machines, Regularization, Optimization, and Beyond (Adaptive Computation and Machine Learning)

by Bernhard Schlkopf

4.6 out of 5 stars (9) $50.62

Data Mining: Practical Machine Learning Tools and Techniques, Second Edition (Morgan Kaufmann Series in Data Management Systems)

by Ian H. Witten

4.0 out of 5 stars (30) $44.51

The Elements of Statistical Learning: Data Mining, Inference, and Prediction, Second Edition (Springer Series in Statistics)

by Trevor Hastie

3.8 out of 5 stars (33) $71.96

› Explore similar items

Related Items


Computer Viruses and Malware (Advances in Information Security) $99.00 $79.20	The Physics of Quantum Information: Quantum Cryptography, Quantum Teleportation, Quantum Computation $119.00 $92.00	Introduction to Cryptography: Principles and Applications (Information Security and Cryptography) $69.95 $60.37

Editorial Reviews

Product Description
Presents a new approach to generating text classifiers from examples. Combines high performance and efficiency with theoretical understanding and improved relationship in particular, and gives a complete and detailed explanation of the SVM approach to learning text classifiers.

Product Details

Hardcover: 228 pages
Publisher: Springer; 1 edition (April 30, 2002)
Language: English
ISBN-10: 079237679X
ISBN-13: 978-0792376798
Product Dimensions: 9.2 x 6.1 x 0.8 inches
Shipping Weight: 14.4 ounces (View shipping rates and policies)

Average Customer Review: 5.0 out of 5 stars See all reviews (2 customer reviews)

Amazon.com Sales Rank: #967,081 in Books (See Bestsellers in Books)
Popular in this category: (What's this?)
#83 in Books > Computers & Internet > Business & Culture > Technical Support

Would you like to update product info or give feedback on images?

Inside This Book (learn more)

First Sentence:
With the rapid growth of the World Wide Web, the task of classifying natural language documents into a predefined set of semantic categories has become one of the key methods for organizing online information. Read the first page

Key Phrases - Statistically Improbable Phrases (SIPs): (learn more)
learning text classifiers, transductive approach, transductive setting, transductive support vector machines, stopword removal, inverse margin, transductive learning, expected generalization error, inductive setting, little training data, average training time, statistical learning model, binary tasks, large test sets, text classification, test set size, negative documents, unlabeled examples, negative training examples, unlabeled data, positive training examples, transductive inference, discriminative features, small training sets, generalization performance

Key Phrases - Capitalized Phrases (CAPs): (learn more)
Nervous System, Chunking Minimum, Cornell University, Examples Examples Figure, World Wide Web

New!
Books on Related Topics | Concordance | Text Stats

Citations (learn more)

This book cites 19 books:

Machine Learning by Tom M. Mitchell on 6 pages
Information Retrieval by C. J. Van Rijsbergen on 4 pages
Research and Development in Information Retrieval (British Computer Society Workshop Series) by C. J. van Rijsbergen in Back Matter (1), Back Matter (2), and Back Matter (3)
Machine Learning (Inaugural Lecture) by A. Gammerman in Back Matter (1), and Back Matter (2)
An Introduction to the Bootstrap (Monographs on Statistics and Applied Probability) by Bradley Efron in Back Matter

See all 19 books this book cites

Books on Related Topics (learn more)

Advances in Knowledge Discovery and Data Mining by Honghua Dai

Discusses:

Learning Theory by Peter Auer

Discusses:

Advances in Web-Age Information Management by Wenfei Fan

Discusses:

Encyclopedia of Data Warehousing and Mining by John Wang

Discusses:

Suggested Tags from Similar Products

(What's this?)

Be the first one to add a relevant tag (keyword that's strongly related to this product).

machine learning(50)

pattern recognition(33)

artificial intelligence(20)

nlp(15)

statistics(12)

data mining(12)

natural language processing(12)

algorithms(8)

computational linguistics(9)

statistical nlp(9)

text mining(10)

Help others find this product — tag it for Amazon search

No one has tagged this product for Amazon search yet. Why not be the first to suggest a search for which it should appear?

Sell a Digital Version of This Book in the Kindle Store

If you are a publisher or author and hold the digital rights to a book, you can sell a digital version of it in our Kindle Store. Learn more

Customer Reviews

2 Reviews

5 star:		(2)
4 star:		(0)
3 star:		(0)
2 star:		(0)
1 star:		(0)

Average Customer Review

5.0 out of 5 stars (2 customer reviews)

Share your thoughts with other customers:

Create your own review

Most Helpful Customer Reviews

2 of 2 people found the following review helpful:

5.0 out of 5 stars The Gold standard, May 16, 2007

By	S. Purpura - See all my reviews (REAL NAME)

This is a must read for anyone beginning to investigate the analysis of meaning in text using computational methods. I found the initial sections were useful in bringing together my thought on many different aspects of the topic.

Comment Comment | Permalink | Was this review helpful to you? Yes No (Report this)

1 of 9 people found the following review helpful:

5.0 out of 5 stars Wonderful book on the subject, September 3, 2005

By	Juan C. Zazueta Carpinteyro "Alpha" (Mexico City, M�xico) - See all my reviews (REAL NAME)

This is a Tesis Work, it contains a review and conmparation of several learners. It focuses mainly on SVM.

Comment Comment | Permalink | Was this review helpful to you? Yes No (Report this)

Share your thoughts with other customers: Create your own review

› See all 2 customer reviews...

.jsOffDisplayBlock { display: block; } .jsOffDisplayInline { display: inline; } .jsOffVisibility { visibility: visible; } .jsOnDisplayBlock { display: none; } .jsOnDisplayNoneBlock { display: block; } .jsOnDisplayNoneInline { display: inline; } .jsOnDisplayInline { display: none; } .jsOnVisibility { visibility: hidden; } .jsOnDisplayBlock { display: none; } .jsOnDisplayInline { display: none; } .jsOnVisibility { visibility: hidden; }

Customer Discussions

Beta (What's this?)

New! See all customer communities, and bookmark your communities to keep track of them.

This product's forum (0 discussions)

	Discussion	Replies	Latest Post
	No discussions yet

Ask questions, Share opinions, Gain insight

Start a new discussion

Topic:

First post:

Receive e-mail when new posts are made

Prompts for sign-in

[Cancel]

Guidelines

Active discussions in related forums

Discussion	Replies	Latest Post
science Step up and point out the flaws of evolution/science	2387	15 minutes ago
science Global warming is nothing but a hoax and a scare tactic	8738	1 hour ago
science The Opposite of Science is Religion	14	1 hour ago
medicine Medical Care in the United States	39	4 days ago
artificial intelligence Contemplation the downfall of AI?	5	12 days ago
artificial intelligence Artificial Intelligence: Self Aware Robots in our Near Future?	8	13 days ago
medicine Medicine's Mystery	3	15 days ago