The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it's still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge. Since the pr...
The increasing volume of data in modern business and science calls for more complex and sophisticated tools. Although advances in data mining technology have made extensive data collection much easier, it's still always evolving and there is a constant need for new techniques and tools that can help us transform this data into useful information and knowledge. Since the previous edition's publication, great advances have been made in the field of data mining. Not only does the third of edition of Data Mining: Concepts and Techniques continue the tradition of equipping you with an understanding and application of the theory and practice of discovering patterns hidden in large data sets, it also focuses on new, important topics in the field: data warehouses and data cube technology, mining stream, mining social networks, and mining spatial, multimedia and other complex data. Each chapter is a stand-alone guide to a critical topic, presenting proven algorithms and sound implementations ready to be used directly or with strategic modification against live data. This is the resource you need if you want to apply today's most powerful data mining techniques to meet real business challenges.
* Presents dozens of algorithms and implementation examples, all in pseudo-code and suitable for use in real-world, large-scale data mining projects. * Addresses advanced topics such as mining object-relational databases, spatial databases, multimedia databases, time-series databases, text databases, the World Wide Web, and applications in several fields. *Provides a comprehensive, practical look at the concepts and techniques you need to get the most out of your data
作者简介
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Jiawei Han(韩家炜)，是伊利诺伊大学厄巴纳-尚佩恩分校计算机科学系的Bliss教授。他因知识发现和数据挖掘研究方面的贡献而获得许多奖励，包括ACM SIGKDD创新奖(2004)、IEEE计算机学会技术成就奖(2005)和IEEE W.Wallace McDowell奖(2009)。他是ACM和IEEE会士。他还担任《ACM Transactions on Knowledge Discovery from Data》的执行主编(2006—2011)和许多杂志的编委，包括《IEEE Transactions on Knowledge and Data Engineering》和《Data Mining Knowledge Discovery》。
corn
机械工业出版社2001版
Palmer
机械工业出版社2007版
冲民过人
机械工业出版社2001版
我是大猪:)
机械工业出版社2012版
0 有用 吮指原味鸡 2019-06-01 12:44:43
jiawei是个好同志
0 有用 么见过黑眼圈啊 2020-05-10 01:39:50
好久没有仔细看完一本教材了。 算是一本讲解基础知识的书。但是缺少很多细节method还有应用方式。倒是可以作为入门书籍。
0 有用 宜蘭七仔烤鮭魚 2020-09-07 17:27:22
狂赶死线总算学完了:) @2020-06-12 08:25:28
0 有用 Kai 2022-10-01 19:08:14 美国
这么厚的书当字典好了。
4 有用 流年闲草 2015-02-17 20:05:35
推荐和Coursera的专项课程一起听。Coursera的Slides给出了书中很多较为简略环节的参考文献，书和课程组合，兼顾基础与引申。在线课程精心准备，游戏化做得非常棒，习题集还搞了个名人堂机制，动力满满啊！论坛也很活跃，负责算法R实现那个TA尤其赞，学到了很多！
0 有用 Kai 2022-10-01 19:08:14 美国
这么厚的书当字典好了。
0 有用 丛林的薄雾 2020-10-19 00:45:58
看韩J的书<1.25倍听韩的课<读韩的PPT。
0 有用 宜蘭七仔烤鮭魚 2020-09-07 17:27:22
狂赶死线总算学完了:) @2020-06-12 08:25:28
0 有用 么见过黑眼圈啊 2020-05-10 01:39:50
好久没有仔细看完一本教材了。 算是一本讲解基础知识的书。但是缺少很多细节method还有应用方式。倒是可以作为入门书籍。
0 有用 61F_Kirk 2019-08-03 13:35:06
The most verbose textbook I've read in a while.