Preliminary Call for Papers
The 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) is a leading international conference in the areas of data mining and knowledge discovery (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, and decision-making systems. The conference calls for research papers reporting original investigation results and industrial papers reporting real data mining applications and system development experience. The conference will confer Best Paper Awards to the Best full papers, the Best student papers and the Best application papers from the submissions. The proceedings of the conference will be published by Springer as a volume of the LNAI series and selected best papers will be invited for publications in high-quality journals.

TOPICS
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 miningmining
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, etc

Organizing Committee
Honorary Chairs
Hiroshi Motoda, Osaka University, Japan
Philip S. Yu, University of Illinois at Chicago, USA
General Chairs
Zhi-Hua Zhou, Nanjing University, China
Arbee L.P. Chen, National Chengchi University, Taiwan
Program Committee Chairs
Vincent S. Tseng, National Cheng Kung University, Taiwan
Tu Bao Ho, JAIST, Japan