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DMKD 2023 : 2023 6th International Conference on Data Mining and Knowledge Discovery(DMKD 2023) | |||||||||||||||
Link: http://www.icdmkd.org/ | |||||||||||||||
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Call For Papers | |||||||||||||||
●2023 6th International Conference on Data Mining and Knowledge Discovery(DMKD 2023)-- Ei Compendex & Scopus—Call for papers
March 17-19, 2023 |Seoul, South Korea|Website: www.icdmkd.org ●DMKD 2023 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 (Engineering Village), CPCI, Chemical Abstracts Service (CAS), Conference Proceedings Citation Index (Web of Science), DOAJ, EBSCO (EBSCO Discovery Service), Google Scholar, Inspec, Polymer Library, Scopus, Materials Science & Engineering Database (ProQuest), SciTech Premium Collection (ProQuest), Technology Collection (ProQuest), etc. A selection of papers will be recommended to be published in international journals. ●Program Preview/ Program at a glance March 17, 2023: Registration + Icebreaker Reception March 17, 2023: Opening Ceremony+ KN Speech+ Technical Sessions March 17, 2023: Technical Sessions+ Half day tour/Lab tours ●Paper Submission 1. Submit Via CMT: https://cmt3.research.microsoft.com/DMKD2023 2. Submit Via email directly to: dmkd@iased.org ●CONTACT US Ms. Rita J. Ma 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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