web2.0
The Tipping Point 豆瓣
8.0 (9 个评分) 作者: [加拿大] 马尔科姆·格拉德威尔 Back Bay Book 2002 - 1
"The best way to understand the dramatic transformation of unknown books into bestsellers, or the rise of teenage smoking, or the phenomena of word of mouth or any number of the other mysterious changes that mark everyday life," writes Malcolm Gladwell, "is to think of them as epidemics. Ideas and products and messages and behaviors spread just like viruses do." Although anyone familiar with the theory of memetics will recognize this concept, Gladwell's The Tipping Point has quite a few interesting twists on the subject.
For example, Paul Revere was able to galvanize the forces of resistance so effectively in part because he was what Gladwell calls a "Connector": he knew just about everybody, particularly the revolutionary leaders in each of the towns that he rode through. But Revere "wasn't just the man with the biggest Rolodex in colonial Boston," he was also a "Maven" who gathered extensive information about the British. He knew what was going on and he knew exactly whom to tell. The phenomenon continues to this day--think of how often you've received information in an e-mail message that had been forwarded at least half a dozen times before reaching you.
Gladwell develops these and other concepts (such as the "stickiness" of ideas or the effect of population size on information dispersal) through simple, clear explanations and entertainingly illustrative anecdotes, such as comparing the pedagogical methods of Sesame Street and Blue's Clues, or explaining why it would be even easier to play Six Degrees of Kevin Bacon with the actor Rod Steiger. Although some readers may find the transitional passages between chapters hold their hands a little too tightly, and Gladwell's closing invocation of the possibilities of social engineering sketchy, even chilling, The Tipping Point is one of the most effective books on science for a general audience in ages. It seems inevitable that "tipping point," like "future shock" or "chaos theory," will soon become one of those ideas that everybody knows--or at least knows by name. --Ron Hogan, Amazon.com
维基经济学 豆瓣
Wikinomics:How Mass Collaboration Changes Everything
作者: [加] 唐·泰普斯科特 / [英] 安东尼·D·威廉姆斯 译者: 何帆 / 林季红 中国青年出版社 2007 - 10
维基经济学的得名,缘于维基百科全书网站的巨大成功,它向世界证明:如果有一种方法充分利用组织里每一个人的智慧,它的能量将无比惊人!维基经济学所揭示的四个新法则——开放、对等、共享以及全球运作——正在取代一些旧的商业教条,许多成熟的传统公司正在从这种新的商务范式中受益。我们所熟知的企业如Google、亚马逊、宝洁、IBM、乐高、英特尔、宝马、波音、百思买、Youtube、MySpace等,都已经从维基经济中获得巨大的成功。
《维基经济学》的结论源自900万美元的研究项目,素有“数字经济之父”美誉的新经济学家唐·泰普斯科特向我们展示了个体力量的上升是如何改变商业社会的传统规则,这种利用大规模协作生产产品和提供服务的新方式,正颠覆我们对于传统知识创造模式的认识。
面对变化激烈的未来,企业和个人必须更有远见,掌握维基技术,拥抱维基理念,是21世纪最重要的商业素质。
集体智慧编程 豆瓣
Programming Collective Intelligence
8.3 (15 个评分) 作者: Toby Segaran 译者: 莫映 / 王开福 电子工业出版社 2009 - 1
本书以机器学习与计算统计为主题背景,专门讲述如何挖掘和分析Web上的数据和资源,如何分析用户体验、市场营销、个人品味等诸多信息,并得出有用的结论,通过复杂的算法来从Web网站获取、收集并分析用户的数据和反馈信息,以便创造新的用户价值和商业价值。全书内容翔实,包括协作过滤技术(实现关联产品推荐功能)、集群数据分析(在大规模数据集中发掘相似的数据子集)、搜索引擎核心技术(爬虫、索引、查询引擎、PageRank算法等)、搜索海量信息并进行分析统计得出结论的优化算法、贝叶斯过滤技术(垃圾邮件过滤、文本过滤)、用决策树技术实现预测和决策建模功能、社交网络的信息匹配技术、机器学习和人工智能应用等。
本书是Web开发者、架构师、应用工程师等的绝佳选择。
图书馆2.0 豆瓣
作者: 图书馆2.0工作室 北京图书馆出版社 2008 - 4
《图书馆2.0:升级你的服务》是在构筑图书馆服务的基础上,以图书馆服务为切入点,并围绕服务展开的。《图书馆2.0:升级你的服务》共分三大部分:第一部分是“总纲”,它们从总体上论述了Web2.0与图书馆2.0的基本思想,以及作者对于Web2.0和图书馆2.0的思考;第二部分是分论,分别论述了RSS、Blog、Wiki、Tag和SNS在图书馆的应用,它们是图书馆2.0的主体内容;第三部分是Web2.0技术与理念在图书馆服务中的综合性应用,主要论述了Web2.0在参考咨询、个性化服务、OPAC和图书馆员中的应用,这些内容是Web2.0技术与理念综合应用于图书馆服务的直接体现。
Library 2.0 豆瓣
作者: Michael E. Casey and Laura C. Savastinuk Information Today, Inc. 2007 - 5
Two of the first and most original thinkers on Library 2.0 introduce the essential concepts and offer ways to improve service to better meet the changing needs of 21st century library users. Describing a service model of constant and purposeful change, evaluation and updating of library services, and user participation, the book both outlines the theoretical underpinnings of Library 2.0 and provides practical advice on how to get there. From incorporating technology to reaching the long tail, from getting buy-in to maintaining momentum, all aspects of Library 2.0 are covered.