●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