ICDM
维基百科，自由的百科全书
ICDM, IEEE数据挖掘国际会议(IEEE International Conference on Data Mining)是世界范围内有影响的一个关于数据挖掘的国际会议。到目前为止已经召开了4届。
ICDM的主题：数据挖掘的理论，系统和应用的设计，分析和实现. 包括但不限于下列内容:
- 数据挖掘基础
- 数据挖掘和机器学习算法与方法 in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis), and in new areas
- Mining text and semi-structured data, and mining temporal, spatial and multimedia data
- Mining data streams
- Pattern recognition and trend analysis
- Collaborative filtering/personalization
- Data and knowledge representation for data mining
- Query languages and user interfaces for mining
- Complexity, efficiency, and scalability issues in data mining
- Data pre-processing, data reduction, feature selection and feature transformation
- Post-processing of data mining results
- Statistics and probability in large-scale data mining
- Soft computing (including neural networks, fuzzy logic, evolutionary computation, and rough sets) and uncertainty management for data mining
- Integration of data warehousing, OLAP and data mining
- Human-machine interaction and visual data mining
- High performance and parallel/distributed data mining
- Quality assessment and interestingness metrics of data mining results
- 安全，隐私和数据挖掘的社会影响
- Data mining applications in bioinformatics, electronic commerce, Web, intrusion detection, finance, marketing, healthcare, telecommunications and other fields
历年ICDM会议列表
即将召开的ICDM会议
