HIGHLIGHT
Learn the techniques used by Google, Netflix, and Amazon to transform raw
data into actionable information―including recommendations, predictions,
and intelligent search.
DESCRIPTION
Web 2.0 applications provide a rich user experience, but the parts you can't see
are just as important―and impressive. They use powerful techniques to process
information intelligently and offer features based on patterns and relationships
in data. Algorithms of the Intelligent Web shows readers how to use the same
techniques employed by household names like Google Ad Sense, Netflix, and
Amazon to transform raw data into actionable information.
Algorithms of the Intelligent Web is an example-driven blueprint for creating
applications that collect, analyze, and act on the massive quantities of data users
leave in their wake as they use the web. Readers learn to build Netflix-style recommendation
engines, and how to apply the same techniques to social-networking
sites. See how click-trace analysis can result in smarter ad rotations. All the
examples are designed both to be reused and to illustrate a general technique―
an algorithm―that applies to a broad range of scenarios.
As they work through the book’s many examples, readers learn about recommendation
systems, search and ranking, automatic grouping of similar objects,
classification of objects, forecasting models, and autonomous agents. They also
become familiar with a large number of open-source libraries and SDKs, and
freely available APIs from the hottest sites on the internet, such as Facebook,
Google, eBay, and Yahoo.
KEY POINTS
• Create recommendations like those on Netflix and Amazon
• Implement Google’s Pagerank and the HITS algorithm
• Discover matches on social-networking sites
• Business techniques like sorting email based on content, targeted
advertising, and fraud detection
MARKET INFORMATION
The fields of Collective Intelligence and Web 2.0 are driving much of the interest
in new web development techniques. This book is front-and-center in this
hot area.
Dr. Haralambos Marmanis
holds a Ph.D. in applied mathematics from Brown
University, an M.S. degree in theoretical and applied mechanics from the
University of Illinois at Urbana-Champaign, and B.S. and M.S. degrees in civil
engineering from the Aristotle University of Thessaloniki in Greece. He was the
recipient of the Sigma Xi award for innovative research in 2000, and he is the
author of numerous publications in peer-reviewed international scientific journals,
conferences, and technical periodicals.
Dmitry Babenko is the lead for the data warehouse infrastructure at Emptoris,
Inc. He is a software engineer and architect with 13 years of experience in the IT
industry. He has designed and built a wide variety of applications and infrastructure
frameworks for banking, insurance, supply-chain management, and business
intelligence companies. He received a M.S. degree in computer science from
Belarussian State University of Informatics and Radioelectronics.
MANNING
