Programming Collective Intelligence : Building Smart Web 2.0 Applications (Record no. 72665)

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008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION
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020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9788184043709
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.1
Cutter Seg
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Segaran, Toby
245 ## - TITLE STATEMENT
Title Programming Collective Intelligence : Building Smart Web 2.0 Applications
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Place of publication, distribution, etc Beijing
Name of publisher, distributor, etc O'reilly
Date of publication, distribution, etc 2007
300 ## - PHYSICAL DESCRIPTION
Number of Pages xxi;334+17p.
Other physical details 9x7
Dimensions pb
520 ## - Remark
Summary, etc This fascinating book demonstrates how you can build web 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.

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.
546 ## - LANGUAGE NOTE
Language note ENG
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Computer programming
Topical term or geographic name as entry element Web 2.0 - Applications
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Item type Book
Holdings
Withdrawn status Lost status Source of classification or shelving scheme Damaged status Not for loan Collection code Permanent location Current location Shelving location Date acquired Full call number Barcode Date last seen Koha item type
          Book HBCSE HBCSE Computer 2014-05-20 005.1/Seg 16498 2014-05-20 Book

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