Call for Papers

PAKDD-2018 Call for Papers
The 22nd Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD’18)
June 03 – 06, Melbourne, Australia |
Technical paper submission deadline (revised): November 21st, 2017

Dear Author(s),

Now in its 22nd edition, the Pacific-Asia conference on Knowledge Discovery and Data Mining is the second oldest conference and a leading venue in the area of knowledge discovery and data mining (KDD). With a great pleasure, the Program Committee cordially invites original research and industrial application paper submission for the main technical track of the conference which will be held in Melbourne, Australia from June 3rd to June 6th, 2018. Submission must be high-quality, original and previously unpublished research in the theory, practice, and application on all aspects of knowledge discovery, and data mining. Research papers reporting original real-world application problems and industrial papers reporting real-time mining applications and system development experience are also highly encouraged.

Important Dates

  • Paper submission due (revised): November 21, 2017
  • Notification to authors: January 28, 2018
  • Camera-ready due: February 20, 2018
  • Conference: June 03 – 06, 2018

Conference Scope

The Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD) provides an internationally prestigious 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 conference will also feature a high-quality and timely series of tutorials, and a wide range of workshops. Typically, the Program Committee will also select Best Paper Award, Best Student Paper Award and Best Application Award. The proceedings of the conference will be published by Springer as a volume of the LNAI series and a small number of selected papers will be invited for publications in special issues of high-quality journals including Knowledge and Information Systems (KAIS) and International Journal of Data Science and Analytics.


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

Paper Submission

Please visit for more details

Further Information

For further information, please contact the Program Committee Chairs at pakdd2018 (at)