Algorithms of the Intelligent Web (Paperback)
Haralambos Marmanis, Dmitry Babenko
- 出版商: Manning
- 出版日期: 2009-06-01
- 定價: $1,575
- 售價: 5.0 折 $788
- 語言: 英文
- 頁數: 368
- 裝訂: Paperback
- ISBN: 1933988665
- ISBN-13: 9781933988665
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相關分類:
Algorithms-data-structures
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其他版本:
Algorithms of the Intelligent Web, 2/e (Paperback)
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商品描述
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.
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商品描述(中文翻譯)
Web 2.0應用程式提供了豐富的使用者體驗,但你看不到的部分同樣重要且令人印象深刻。它們使用強大的技術來智能處理資訊,並根據資料中的模式和關係提供功能。《智能網路演算法》向讀者展示如何使用像Google Ad Sense、Netflix和Amazon這樣的知名品牌所使用的相同技術,將原始資料轉化為可行動的資訊。
《智能網路演算法》是一本以實例為基礎的藍圖,用於創建應用程式,這些應用程式收集、分析並對使用者在使用網路時留下的大量資料進行操作。讀者將學習如何建立類似Netflix的推薦引擎,以及如何將相同的技術應用於社交網站。了解點擊追蹤分析如何產生更智能的廣告輪播。所有的實例都旨在可重複使用並且說明一般技術-一種適用於各種情境的演算法。
在閱讀本書的許多實例時,讀者將學習有關推薦系統、搜尋和排名、自動分組相似物件、物件分類、預測模型和自主代理的知識。他們還將熟悉許多開源庫和軟體開發套件,以及來自熱門網站(如Facebook、Google、eBay和Yahoo)的免費API。