Building Smart Web 2.0 Applications

Successful internet companies have learned the hard way how to use the collective intelligence of users:

• Amazon, Netflix and others have built recommendation engines
• Goole has invented a unique page ranking system based on links

In his new book, Programming Collective Intelligence: Building Smart Web 2.0 Applications, Toby Segaran teaches the secrets of harnessing the power of user generated content. This practical book 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. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. The 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