●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. 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