IACSIT-2014 3rd International Conference on Database and Data Mining
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Website http://www.icddm.org/ |
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Category Database;Data Mining
Deadline: March 20, 2014 | Date: June 07, 2014-June 08, 2014
Venue/Country: Bangkok, Thailand
Updated: 2014-02-21 12:16:42 (GMT+9)
Call For Papers - CFP
IACSIT-2014 3rd International Conference on Database and Data MiningICDDM 2014June 7-8, 2014Bangkok, Thailandhttp://www.icddm.org/Paper Submission February 20, 2014Tel: +86-28-8652-7868 (International)Topics of interest for submission include, but are not limited to:Data mining foundations Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) Algorithms for new, structured, data types, such as arising in chemistry, biology, environment, and other scientific domains Developing a unifying theory of data mining Mining sequences and sequential data Mining spatial and temporal datasets Mining textual and unstructured datasets High performance implementations of data mining algorithms Mining in targeted application contexts Mining high speed data streams Mining sensor data Distributed data mining and mining multi-agent data Mining in networked settings: web, social and computer networks, and online communities Data mining in electronic commerce, such as recommendation, sponsored web search, advertising, and marketing tasks Methodological aspects and the KDD process Data pre-processing, data reduction, feature selection, and feature transformation Quality assessment, interestingness analysis, and post-processing Statistical foundations for robust and scalable data mining Handling imbalanced data Automating the mining process and other process related issues Dealing with cost sensitive data and loss models Human-machine interaction and visual data mining Security, privacy, and data integrity Integrated KDD applications and systems Bioinformatics, computational chemistry, geoinformatics, and other science & engineering disciplines Computational finance, online trading, and analysis of markets Intrusion detection, fraud prevention, and surveillance Healthcare, epidemic modeling, and clinical research Customer relationship management Telecommunications, network and systems management Data mining foundations Novel data mining algorithms in traditional areas (such as classification, regression, clustering, probabilistic modeling, and association analysis) Algorithms for new, structured, data types, such as arising in chemistry, biology, environment, and other scientific domains Developing a unifying theory of data mining Mining sequences and sequential data Mining spatial and temporal datasets Mining textual and unstructured datasets High performance implementations of data mining algorithms Mining in targeted application contexts Mining high speed data streams Mining sensor data Distributed data mining and mining multi-agent data Mining in networked settings: web, social and computer networks, and online communities Data mining in electronic commerce, such as recommendation, sponsored web search, advertising, and marketing tasks Methodological aspects and the KDD process Data pre-processing, data reduction, feature selection, and feature transformation Quality assessment, interestingness analysis, and post-processing Statistical foundations for robust and scalable data mining Handling imbalanced data Automating the mining process and other process related issues Dealing with cost sensitive data and loss models Human-machine interaction and visual data mining Security, privacy, and data integrity Integrated KDD applications and systems Bioinformatics, computational chemistry, geoinformatics, and other science & engineering disciplines Computational finance, online trading, and analysis of markets Intrusion detection, fraud prevention, and surveillance Healthcare, epidemic modeling, and clinical research Customer relationship management Telecommunications, network and systems managementAll full paper submissions will also be peer reviewed and evaluated based on originality, technical and/or research content/depth, correctness, relevance to conference, contributions, and readability. The full paper submissions will be chosen based on technical merit, interest, applicability, and how well they fit a coherent and balanced technical program.PublicationsAll accepted papers will be published in the volume of International Journal of Machine Learning and Computing (IJMLC), and will be included in theEngineering & Technology Digital Library, Google Scholar, Crossref, ProQuest,Electronic Journals Library, DOAJ and EI (INSPEC, IET).SUBMISSION METHODS:1. Electronic Submission System; ( .pdf)http://www.easychair.org/conferences/?conf=icddm2014If you can't login the submission system, please try to submit through method 2.2. Email: ICDDMIACSIT.ORG ( .pdf and .doc)
Keywords: Accepted papers list. Acceptance Rate. EI Compendex. Engineering Index. ISTP index. ISI index. Impact Factor.
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