Research Catalog

Title

Ending spam : Bayesian content filtering and the art of statistical language classification / by Jonathan A. Zdziarski.

Author

Zdziarski, Jonathan A.

Publication

San Francisco : No Starch Press, [2005], ©2005.

Items in the Library & Off-site

Holdings

Details

Description

xx, 287 pages : illustrations; 24 cm

Summary

"This landmark title describes, in-depth, how statistical filtering is being used by next-generation spam filters to identify and filter unwanted messages, how spam filtering works, and how language classification and machine learning combine to produce remarkably accurate spam filters." "After reading Ending Spam, you'll have a complete understanding of the mathematical approaches used by today's spam filters as well as decoding, tokenization, various algorithms (including Bayesian analysis and Markovian discrimination), and the benefits of using open-source solutions to end spam. Zdziarski interviewed creators of many of the best spam filters and has included their insights in this revealing examination of the anti-spam crusade."--BOOK JACKET.

Subject

• Spam filtering (Electronic mail)
• Filters (Mathematics)

Note

• Includes index.

Contents

1. The history of spam -- 2. Historical approaches to fighting spam -- 3. Language classification concepts -- 4. Statistical filtering fundamentals -- 5. Decoding : uncombobulating messages -- 6. Tokenization : the building blocks of spam -- 7. The low-down dirty tricks of spammers -- 8. Data storage for a zillion records -- 9. Scaling in large environments -- 10. Testing theory -- 11. Concept identification : advanced tokenization -- 12. Fifth-order Markovian discrimination -- 13. Intelligent feature set reduction -- 14. Collaborative algorithms -- App. Shining examples of filtering.

ISBN

1593270526

LCCN

• 2005008221
• R6-514909

OCLC

• OCM58595154
• SCSB-5199443

Owning Institutions

Columbia University Libraries