Algorithms of the Intelligent Web - Haralambos Marmanis, Dmitry Babenko

Algorithms of the Intelligent Web

Haralambos Marmanis, Dmitry Babenko

出版时间

2009-07-08

ISBN

9781933988665

评分

★★★★★
书籍介绍
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.
精彩摘录
  • "the similarity matrix is symmetrical. This simply means that if user A is similarity to user B with a similarity value X then user B will be similar to user A with a similarity value equal to X."
  • "Bell and Keorren are leading the Netflix prize competitioin (at the time of this writing), and their assessment was the following: "we found no perfect models. Instead, our best results came from combining predictions of models that complemented each other.""
  • "推荐引擎的核心功能在于计算任意两个用户或两个条目之间的相似程度。"
  • "智能Web应用所必须的基本元素: 内容集合(数据),与具体应用有关的大量数据; 参考架构(结构化和语义化),为内容提供了结构化,语义化的解释; 算法:对数据中的结构化和语义化的内容进行分析; Mashup是一种激动人心的交互式Web应用,它从外部数据源获取内容,然后创建出全新的富有创意的服务。"
  • "如何构建智能Web应用: 1. 审查应用的功能:分析user case和实际的商业价值 2. 了解你需要和拥有的数据 爬虫Crawler也被成为spider,是用于从互联网上获取公开内容的程序,爬虫通常会访问一份URL列表,然后跟踪其中的每个链接,这个过程会不断的重复,重复的次数被成为爬虫深度。 AI的目标是极具野心的,试图开发出像人类一样思考的机器。机器学习,数据挖掘,软计算都是其中最基础的一些探索。 机器学习是指软件系统能从已有的经验中抽象出普遍的规则,然后利用这些规则回答各种问题,包括曾经遇到过的或者没有遇到过的问题。 智能Web应用需要考虑的8个误区: 1. 数据不可靠 2. 计算需要"
作者简介
Dr. Haralambos (Babis) Marmanis is a pioneer in the adoption of machine learning techniques for industrial solutions, and also a world expert in supply management. He has about twenty years of experience in developing professional software. Currently, he is the director of R&D and chief architect, for expense management solutions, at Emptoris, Inc. Babis 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.
用户评论
正在读这本书的中译本,是阿稳和陈钢译的,看得过程如沐春风。原稿很有特点,除了这个很难得的主题,以及别无分号的方法论(虽然定位为初级,但国内绝大多数业者都需要看),更主要的是他教学的思路很独特。最让我印象深刻的是译稿的质量,真得是许久未见的佳作!
这种书里使劲贴什么代码...注意品味...
很不错,但是距离好的实现还是有一大段距离,摸索中前进吧。
很不错的科普,但是不够系统全面,只有一些例子
这种风格的书真心不是我的菜。
简略介绍了一些常用的算法和技术,需要一些数学背景知识,讲的不详细
Great book in to Intelligence.
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