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》。
拥有加拿大康考迪亚大学计算机科学硕士学位,现在加拿大西蒙弗雷泽大学从事博士后研究工作。
发表于2024-11-22
Data Mining 2024 pdf epub mobi 电子书
这本书是准备跟随浙江大学的课程学习而购买的课本,里面的知识比较全面。部分比较深入的知识由于课上没有 讲解,因此我也将它跳过了。因为这学期选修了数据挖掘的课,需要一个中文版的课本进行学习,选择这本书还是不错的。 这本书很适合自学,因为是将理论与算法相结合讲解的...
评分//2017-05-20 13:30 这篇文章我已经欠了至少一年了,周五写记录时,本想写开始认真搞黑客,但突然发现之前的总结少这篇,心里实在过不去,遂补上,顺便梳理一下之前的学习总结,也了却一心愿。 数据挖掘的目标是从数据集中识别出一种或多种模式,并用所发现的模式进行分析或...
评分应该说这部书可以把人引进门,但看了之后,总觉得还有些概念模糊之处,比如说数据挖掘的理论来源是什么?如何把这些算法从本质上分类? 我觉得,这方面,《实用数据挖掘》会更好些。另外,如何使用简单的软件,为企业或政府部门实现一个简单可见的数据挖掘呢?这方面,我只读...
评分浙大的王灿老师的讲课视频: http://www.businessanalysis.cn/viewthread.php?tid=13320&extra=&page=1 韩家炜自己的讲课视频: http://v.youku.com/v_playlist/ct250f1903290o1p0
评分这本书是刚上研究生的时候开始看的,这本书介绍的数据挖掘基本上是从数据库的概念出发的,对各种算法都有提及,但是很多算法基本上是语焉不详,对于刚开始学习数据挖掘和机器学习的学生来说,能对数据挖掘的基本概念有所了解,对算法也只能了解个大概了。 如果不是纯搞数据仓库...
图书标签: 数据挖掘 机器学习 Data-Mining 计算机 计算机科学 互联网 个性化推荐 信息检索
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
The most verbose textbook I've read in a while.
评分当年ML的指定教材
评分在读书会合作者的敦促下,每周读几节,读了好多个月,终于考古完了。有几章节写的太简略了,我们换书继续接上。 每次读书会会总结一下哪些地方还有用,哪些已经真的过时了,感觉考古还挺好玩的。
评分The most verbose textbook I've read in a while.
评分韩老师的书确实不敢恭维,可能不是自己亲自写的吧。看的是英文版的,看来一般就看不下去了,讲了很多东西,到那时都是一笔带过,读完之后不知所云。
Data Mining 2024 pdf epub mobi 电子书