Introduction数据挖掘.ppt

中国计算机学会认定的相关期刊和会议 中国计算机学会推荐国际学术会议和期刊目录 （2012年） 中国计算机学会 (数据库、数据挖掘与内容检索) (人工智能与模式识别) 数据挖掘研究院： 学 者 国际： Michael I. Jordan， /~jordan/，Graphical model, Baysian learning, hierarchical J.D.Lafferty：semi learning,kernel leraning, graphical models. Bernhard Sch?lkopf：Machine learning中的optimization problem，kernel trick的算法等等。 Jiawei Han ，/~hanj/ …… 国内： 周志华，南京大学，/zhouzh/ 李建中 朱军，清华大学副教授，/~jun/ * * * * * * This chapter will not be in the new version, will it? BUT SHOULD WESTILL INTRODCE THEM SO THAT THEY WILL GET AN OVERALL PICTURE? * * * * Add a definition/description of “traditional data analysis”. * * * * * * * * * * * * * Applications of Data Mining Web page analysis: from web page classification, clustering to PageRank HITS algorithms Collaborative analysis recommender systems Basket data analysis to targeted marketing Biological and medical data analysis: classification, cluster analysis (microarray data analysis), biological sequence analysis, biological network analysis Data mining and software engineering (e.g., IEEE Computer, Aug. 2009 issue) From major dedicated data mining systems/tools (e.g., SAS, MS SQL-Server Analysis Manager, Oracle Data Mining Tools) to invisible data mining * Chapter 1. Introduction Why Data Mining? What Is Data Mining? A Multi-Dimensional View of Data Mining What Kind of Data Can Be Mined? What Kinds of Patterns Can Be Mined? What Technology Are Used? What Kind of Applications Are Targeted? Major Issues in Data Mining A Brief History of Data Mining and Data Mining Society Summary * Major Issues in Data Mining (1) Mining Methodology 挖掘方法 Mining various and new kinds of knowledge Mining knowledge in multi-dimensional space Data mining: An interdisciplinary effort Boosting the power of discovery in a networked environment Handling noise, uncertainty, and incompleteness of data Pattern evaluation and pattern- or constraint-guided mining User Interaction 用户界面 Interactive mining Incorporation of background knowledge Presenta