PAKDD 2018

PAKDD 2018
22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining
Event in series	PAKDD
Dates	2018/06/03 (iCal) - 2018/06/06
Homepage:	https://mamsap.it.deakin.edu.au/pakdd18/prada-research.net/pakdd18/index.html
Location
Location:	Melbourne, Victoria, Australia
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Papers:	Submitted 592 / Accepted 164 (27.7 %)
Committees
General chairs:	Geoff Webb, Bao Ho
PC chairs:	Dinh Phung, Vincent Tseng
Table of Contents

Topics

As a premier international conference on knowledge discovery and data mining, PAKDD’18 welcomes all submissions on all aspects of knowledge discovery, data mining and machine learning. Suggestive topics of relevance for the conference include, but not limited to, the following:

• Theoretic foundations of KDD
• Deep learning theory and applications in KDD
• Novel models and algorithms
• Statistical methods and graphical models for data mining
• Anomaly detection and analytics
• Association analysis
• Clustering
• Classification
• 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 multi-media data
• Mining scientific data
• Privacy preserving data mining
• 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, and industry-related problems