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DMKD 2019

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

Shanghai, China, China
26 - 28 April 2019
The conference ended on 28 April 2019

Important Dates

Early Bird Deadline
22nd February 2019
Abstract Submission Deadline
31st March 2019
Abstract Acceptance Notification
31st March 2019
Final Abstract / Full Paper Deadline
31st March 2019

About DMKD 2019

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.

Call for Papers

●2019 2nd International Conference on Data Mining and Knowledge Discovery(DMKD 2019)-- Ei Compendex & Scopus—Call for papers  

Website:www.icdmkd.org      

●Paper Submission

1. PDF version submit via CMT: https://cmt3.research.microsof...9

2. Submit Via email directly to: dmkd@iased.org      

●CONTACT US

Ms. Yedda Q. YE

Email: dmkd@iased.org 

Website: www.icdmkd.org 

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

  • Anomaly detection

  • Applications to healthcare, bioinformatics, computational chemistry, finance, eco-informatics, marketing, gaming, cyber-security etc.

  • Association analysis

  • Classification

  • Clustering

  • Data pre-processing

  • Feature extraction and selection

  • Fraud and risk analysis

  • Human, domain, organizational and social factors in data mining

  • Integration of data warehousing, OLAP and data mining

  • Interactive and online mining

  • 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

  • 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 and agent-based data mining

  • Visual data mining

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