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Programming Collective Intelligence: Building Smart Web 2.0 Applications ペーパーバック – 2007/8/26
購入オプションとあわせ買い
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
"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
- 本の長さ362ページ
- 言語英語
- 出版社O'Reilly Media
- 発売日2007/8/26
- 寸法17.78 x 2.29 x 23.34 cm
- ISBN-100596529325
- ISBN-13978-0596529321
商品の説明
著者について
Toby Segaran is the author of Programming Collective Intelligence, a very popular O'Reilly title. He was the founder of Incellico, a biotech software company later acquired by Genstruct. He currently holds the title of Data Magnate at Metaweb Technologies and is a frequent speaker at technology conferences.
登録情報
- 出版社 : O'Reilly Media; 第1版 (2007/8/26)
- 発売日 : 2007/8/26
- 言語 : 英語
- ペーパーバック : 362ページ
- ISBN-10 : 0596529325
- ISBN-13 : 978-0596529321
- 寸法 : 17.78 x 2.29 x 23.34 cm
- Amazon 売れ筋ランキング: - 398,955位洋書 (洋書の売れ筋ランキングを見る)
- - 224位Web 2.0
- - 1,164位Programming Algorithms
- - 1,320位Machine Learning
- カスタマーレビュー:
著者について
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I start my working day with consuming two sweet drinks. One drink is a cup of coffee. Another is a virtual information soup made of 100 blogs. I glance over most of the stories quickly using Google Reader and select those that I am interested in. I might read them in greater detail later on during the day, in the evening, or on a weekend. I do not know which drink gives me more pleasure - the delicious cup of coffee or sweet virtual soup. I like the latter a lot because it is rich with media content - with bright images, cool videos, wow-type web pages.
However, I often discover news that I wish I found out earlier. In other words, there are so many news sources that reading them all or just looking at the headlines of major blogs will take too much time. We need targeted information delivery service.
This is the main idea of this book. In fact, it starts with explaining how to make recommendations given a set of preferences of a number of people and your own preferences. What are those cool things that you have not tried out yet but everybody else did? The example described in the book is applied to Delicious which does not offer recommendations yet.
I often try to decide what my interests are. The blogs that I am reading might answer this question if one builds groups of them. In fact, I have done this manually, but I found out that this categorization is not perfect. The book answers this question in Chapter 3.
After that the book deviates into a number of additional topics such as search, neural networks, discrete optimization. The author Toby Segaran has a great ability to explain difficult concepts using simple words and pictures. As most of the stuff was familiar to me I was wondering how easy a new concept seemed and how much time I spent originally understanding it.
After that the main melody of the book is there again - the next chapter explains how to filter documents, for example to decide if a particular news story is interesting to you or not. Then the book deviates again into decision trees and building price models and even matching people on a dating site. However, there comes our melody again - this time it explains how to extract trends from a lot of news sources, that is decide what people are discussing today. This feature is similar to Google News except that the user has no control of news sources.
I was surprised when I found out that Python is such a popular language in a scientific community. The book describes lots of libraries dealing with numerical data or displaying various charts. The book will serve as a great introduction to Python language even though there are lots of introductory books available. In fact, learning Python this way it easier and more enjoyable.
After reading the book I definitely want to try out the tricks explained there and improve my information soup. This book is my virtual cookbook.