The 18th Pacific-Asia Conference on Knowledge Discovery and Data Mining (PAKDD-2014)


May 13-16, 2014, Tainan, Taiwan


http://pakdd2014.pakdd.org/
  • Paper Submission Due: Oct. 1, 2013 Oct. 8, 2013 [23:59:59 Pacific Time](fianl due)
  • Author Notification: Dec. 20, 2013
  • Camera Ready Due: Jan. 12, 2014

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 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

Paper submission system is available at https://cmt.research.microsoft.com/PAKDD2014/Default.aspx.

The submitted paper should adhere to the double-blind review policy. All papers will be double-blind reviewed by the Program Committee on the basis of technical quality, relevance to data mining, originality, significance, and clarity. All paper submissions will be handled electronically. Detailed instructions are provided on the conference home page. Papers that do not comply with the Submission Guidelines will be rejected without review.


Each submitted paper should include an abstract up to 200 words and be not longer than 12 single-spaced pages with 10pt font size. Authors are strongly encouraged to use Springer LNCS/LNAI manuscript submission guidelines (available at http://www.springer.de/comp/lncs/authors.html) for their initial submissions. All papers must be submitted electronically through the paper submission system in PDF format only.


The submitted papers must not be previously published anywhere, and must not be under consideration by any other conferences or journal during the PAKDD review process. Submitting a paper to the conference means that if the paper were accepted, at least one author will attend the conference to present the paper. For no-show authors, their affiliations will receive a notification. The program committee chairs are not allowed to submit papers to the conference for a fair review process.


The conference will confer several awards including Best Paper Awards, Best student Paper Awards and Best Application Paper Awards 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 special issues of high-quality journals including Knowledge and Information Systems (KAIS) and ACM Transactions on Intelligent Systems and Technologies (TIST).


Before submitting your paper, please carefully read and agree with the PAKDD submission policy and no-show policy: http://pakdd.togaware.com/policy.html

    Honorary Co-chairs

  • Hiroshi Motoda, Osaka University, Japan
  • Philip S. Yu, University of Illinois at Chicago, USA

    General Co-chairs

  • Zhi-Hua Zhou, Nanjing University, China
  • Arbee L.P. Chen, National Chengchi University, Taiwan

    Program Committee Co-hairs

  • Vincent S. Tseng, National Cheng Kung University, Taiwan
  • Tu Bao Ho, JAIST, Japan

    Workshop Co-chairs

  • Wen-Chih Peng, National Chiao Tung University, Taiwan
  • Haixun Wang, Google Inc., USA
  • James Bailey, University of Melbourne, Australia

    Tutorial Co-chairs

  • Mi-Yen Yeh, Academia Sinica, Taiwan
  • Guandong Xu, University of Technology Sydney, Australia
  • Seung-Won Hwang, POSTECH, Korea

    Publicity Co-chairs

  • Takashi Washio, Osaka University, Japan
  • Tzung-Pei Hong, National University of Kaohsiung, Taiwan
  • Yu Zheng, Microsoft Research Asia, China
  • George Karypis, University of Minnesota, USA

    Proceedings Chair

  • Hung-Yu Kao, National Cheng Kung University, Taiwan

    Contest Co-chairs

  • Shou-De Lin, National Taiwan University, Taiwan
  • Nitesh Chawla, University of Notre Dame, USA

    Local Arrangement Co-chairs

  • Jen-Wei Huang, National Cheng Kung University, Taiwan
  • Kun-Ta Chuang, National Cheng Kung University, Taiwan
  • Ja-Hwung Su, Kainan University, Taiwan

For further information, please contact the Program Committee Chairs by pakdd2014@gmail.com.

    General Inquiries

  • Vincent S. Tseng
  • Email: pakdd2014@gmail.com
  • Phone: (886)6-2757575 ext 62536
  • Fax: (886)6-2747076