Programming Collective Intelligence: Building Smart Web 2.0 Applications

Toby Segaran

ISBN 10: 0596529325 / ISBN 13: 9780596529321

Published by O'Reilly Media, Sebastopol, CA., USA, 2007

About this Item

Business. This book is in very good condition. The front cover is bent up slightly but there are no stains or tears. This book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by participatory Internet applications. With the sophisticated algorithms in this book, you can write smart programs to access interesting data sets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it. Proceeds from the sale of this book benefit environmental restoration and education. Seller Inventory # 005367

Bibliographic Details

Title: Programming Collective Intelligence: ...

Publisher: O'Reilly Media, Sebastopol, CA., USA

Publication Date: 2007

Binding: Soft cover

Condition: Very Good

Dust Jacket Condition: No Jacket

Edition: 1st Edition

About this title

Synopsis:

Want to tap the power behind search rankings, product recommendations, social bookmarking, and online matchmaking? This fascinating book demonstrates how you can build Web 2.0 applications to mine the enormous amount of data created by people on the Internet. With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.

Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:

• Collaborative filtering techniques that enable online retailers to recommend products or media
• Methods of clustering to detect groups of similar items in a large dataset
• Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm
• Optimization algorithms that search millions of possible solutions to a problem and choose the best one
• Bayesian filtering, used in spam filters for classifying documents based on word types and other features
• Using decision trees not only to make predictions, but to model the way decisions are made
• Predicting numerical values rather than classifications to build price models
• Support vector machines to match people in online dating sites
• Non-negative matrix factorization to find the independent features in a dataset
• Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game

Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you.

"Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."
-- Dan Russell, Google

"Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."
-- Tim Wolters, CTO, Collective Intellect

Review:

..you should buy this book.... It's well written manual that'll handily expand your repetoire.
-- London Perl M(ou)ngers, london.pm.org, December 2007