PAKDD 2018 - 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining
Topics/Call fo Papers
The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is a leading international conference in the areas of knowledge discovery and data mining (KDD). It provides an international forum for researchers and industry practitioners to share their new ideas, original research results and practical development experiences from all KDD related areas, including data mining, data warehousing, machine learning, artificial intelligence, databases, statistics, knowledge engineering, visualization, decision-making systems and the emerging applications.
The topics of relevance for the conference papers include but not limited to the following:
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.
The topics of relevance for the conference papers include but not limited to the following:
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.
Other CFPs
- 14th Artificial Intelligence Applications and Innovations 2018
- World Summit on Nanoscience and Nanoengineering
- 3rd International Conference On Advances In Computer Science And Information Technology
- Global Engineering & Applied Science Conference (2018 GEASC)
- International Symposium on Business and Social Sciences
Last modified: 2017-08-07 22:26:23