given lots of data->discover patterns and models that are: valid, useful, unexpected, understandable.
1. statistical modeling
2. machine learning
use data as a training set to train an algorithm, like Bayes nets, SVM, decision trees, HMM
Data mining uses algorithms to discover interesting patterns
3. computational approach to modeling
4. summarization
PageRank. clustering
5. feature extraction
extreme examples represent data(eg: similar items)
Data Ming Tasks:
1) Descriptive methods: eg, clustering
2) Predictive methods
中国计算机学会推荐国际学术期刊 （数据库/数据挖掘/内容检索）
http://www.ccf.org.cn/sites/ccf/biaodan.jsp?contentId=2903940690081