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DMKD 2021 : 2021 4th International Conference on Data Mining and Knowledge Discovery(DMKD 2021) | |||||||||||||||
Link: http://www.icdmkd.org/ | |||||||||||||||
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Call For Papers | |||||||||||||||
●2021 4th International Conference on Data Mining and Knowledge Discovery(DMKD 2021)-- Ei Compendex & Scopus—Call for papers
February 19-21, 2021 | Chiang Mai, Thailand|Website: www.icdmkd.org ●DMKD 2021 provides researchers and industry experts with one of the best platforms to meet and discuss groundbreaking research and innovations in the field of Data Mining and Knowledge Discovery. International invited speakers are invited to present their state-of-the-art work on various aspects, which will highlight important and developing areas. ●Publication and Indexing All accepted papers will be published in the digital conference proceedings which will be sent to be Indexed by all major citation databases such as Ei Compendex, SCOPUS, Google Scholar, Cambridge Scientific Abstracts (CSA), Inspec, SCImago Journal & Country Rank (SJR), EBSCO, CrossRef, Thomson Reuters (WoS), etc. A selection of papers will be recommended to be published in international journals. ●Keynote Speakers Prof. Amir H Gandomi, The University of Technology Sydney, Australia Prof. Hai Jin, Huazhong University of Science and Technology, China Prof. Yang Kuang, Arizona State University, USA ●Program Preview/ Program at a glance Feb. 19, 2021: Registration + Icebreaker Reception Feb. 20, 2021: Opening Ceremony+ KN Speech+ Technical Sessions Feb. 21, 2021: Technical Sessions+ Half day tour/Lab tours ●Paper Submission 1. PDF version submit via CMT: https://cmt3.research.microsoft.com/DMKD2021 2. Submit Via email directly to: dmkd@iased.org ●CONTACT US Ms. Kiki.Y. P. Kwok Email: dmkd@iased.org Website: www.icdmkd.org Call for papers(http://www.icdmkd.org/cfp): Agent-based data mining Anomaly detection Association analysis Bioinformatics Classification Cyber-security analysis Data pre-processing Eco-informatics Feature extraction and selection Fraud and risk analysis Human, domain, organizational and social factors in data mining Integration of data warehousing Interactive and online mining Marketing Mining behavioral data Mining dynamic/streaming data Mining graph and network data Mining heterogeneous/multi-source data Mining high dimensional data Mining imbalanced data Mining multimedia data Mining scientific data Mining sequential data Mining social networks Mining spatial and temporal data Mining uncertain data Mining unstructured and semi-structured data Novel models and algorithms OLAP and data mining Opinion mining and sentiment analysis Parallel, distributed, and cloud-based high performance data mining Post-processing including quality assessment and validation Privacy preserving data mining Security and intrusion detection Statistical methods for data mining Theoretic foundations Ubiquitous knowledge discovery Visual data mining |
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