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| 第四届国际高性能数据挖掘与应用大会（ADMA08） |
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[ 会议基本信息 ]
会议名称（中文）： 第四届国际高性能数据挖掘与应用大会（ADMA08）
会议名称（英文）： The Fourth International Conference on Advanced Data Mining and Applications
所属学科： 计算机科学技术
会议类型： 国际会议
会议论文集是否检索： SCI EI
开始日期： 2008-9-29
结束日期： 2008-9-30
所在国家： 中华人民共和国
所在城市： 四川省 成都市
[ 组织结构 ]
会议主席： Nick Cercone，Xiaofang Zhou
组织委员会主席： Jiliu Zhou，Chuan Li
程序委员会主席： Changjie Tang，Charles Ling
[ 重要日期 ]
全文截稿日期： 2008-4-27
论文录用通知日期 2008-5-6
交修订版截止日期：
[ 会务组联系方式 ]
会议背景介绍： Chengdu , also known as "Rong City"," Paradise Place", is the capital of Sichuan Province , one of the historical and cultural cities in China , a city full of exotic atmosphere, a city of glittering and translucence.
The 1st International Conference on Advanced Data Mining and Applications (ADMA 2005) was successfully held in Wuhan , China , and the proceedings were published by Springer in LNAI 3584. The 2 nd International Conference on Advanced Data Mining and Applications (ADMA 2006) was held in Xi'An , China , and the proceedings were also published by Springer in LNAI 4093. The 3 rd ADMA 2007 was sponsored by Harbin Institute of Technology.
A growing attention has been paid to the study, development and application of data mining. As a result there is an urgent need for sophisticated techniques and tools that can handle new fields of data mining, e.g. spatial data mining in the context of spatial-temporal characteristics, streaming data mining, and biomedical data mining. Our knowledge on data mining should also have to be expanded to new applications. The 4 th International Conference on Advanced Data Mining and Applications (ADMA2008) aims at bringing together the experts on data mining in the world, and provides a leading international forum for the dissemination of original research results in data mining, spanning applications, algorithms, software and systems, and different applied disciplines with potential in data mining.
征文范围及要求： Key Topics:
We invite authors to submit papers on any topics of advanced data mining and applications, including but not limited to:
Advanced Data Mining Topics
Grand challenges of data mining
Parallel and distributed data mining algorithms
Mining on data streams
Graph and subgraph mining
Spatial data mining
Text, video, multimedia data mining
Web mining
High performance data mining algorithms
Correlation mining
Bench marking and evaluations
Interactive data mining
Data-mining-ready structures and pre-processing
Data mining visualization
Information hiding in data mining
Security and privacy issues
Competitive analysis of mining algorithms
Data Mining Applications (applied data mining in following listed areas)
Database administration, indexing, performance tuning
Grid computing
DNA Sequencing, Bioinformatics, Genomics, and biometrics
Image interpretations
E-commerce and Web services
Medical informatics
Disaster prediction
Remote monitoring
Financial market analysis
Online filtering
