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DMKD 2019 2019 : 2019 2nd International Conference on Data Mining and Knowledge Discovery(DMKD 2019)

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Link: http://www.icdmkd.org/
 
When Apr 26, 2019 - Apr 28, 2019
Where Shanghai, China
Submission Deadline Oct 30, 2018
Notification Due Oct 30, 2018
Final Version Due Oct 30, 2018
Categories    data mining   knowledge discovery
 

Call For Papers

●2019 2nd International Conference on Data Mining and Knowledge Discovery(DMKD 2019)-- Ei Compendex & Scopus—Call for papers  
April 26-28, 2019. |Shanghai, China|Website: www.icdmkd.org

●DMKD 2019 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.
 

●Program Preview/ Program at a glance
April. 26, 2019: Registration + Icebreaker Reception
April. 27, 2019: Opening Ceremony+ KN Speech+ Technical Sessions 
April. 28, 2019: Technical Sessions+ Half day tour/Lab tours

●Paper Submission
1. PDF version submit via CMT: https://cmt3.research.microsoft.com/DMKD2019
2. Submit Via email directly to: dmkd@iased.org

●CONTACT US
Ms. Tiya T.Deng
Email: dmkd@iased.org
Website: www.icdmkd.org

Call for papers(http://www.icdmkd.org/cfp.html):

Theoretic foundations
•Novel models and algorithms
•Association analysis
•Clustering
•Classification
•Statistical methods for data mining
•Data pre-processing
•Feature extraction and selection
•Post-processing including quality assessment and validation
•Mining heterogeneous/multi-source data
•Mining sequential data
•Mining spatial and temporal data
•Mining unstructured and semi-structured data
•Mining graph and network data
•Mining social networks
•Mining high dimensional data
•Mining uncertain data
•Mining imbalanced data
•Mining dynamic/streaming data
•Mining behavioral data
•Mining multimedia data
•Mining scientific data
•Privacy preserving data mining
•Anomaly detection
•Fraud and risk analysis
•Security and intrusion detection
•Visual data mining
•Interactive and online mining
•Ubiquitous knowledge discovery and agent-based data mining
•Integration of data warehousing, OLAP and data mining
•Parallel, distributed, and cloud-based high performance data mining
•Opinion mining and sentiment analysis
•Human, domain, organizational and social factors in data mining
•Applications to healthcare, bioinformatics, computational chemistry, finance, eco-informatics, marketing, gaming, cyber-security etc.

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