<div>Call For Papers PAKDD 2013</div><div><br></div><div>The 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining </div><div>Gold Coast, Australia</div><div>Conference Website</div><div><a href="http://pakdd2013.pakdd.org/">http://pakdd2013.pakdd.org/</a></div>
<div><br></div><div><br></div><div>Submission System</div><div><span class="Apple-tab-span" style="white-space:pre"> </span><a href="https://cmt.research.microsoft.com/PAKDD2013/">https://cmt.research.microsoft.com/PAKDD2013/</a></div>
<div><br></div><div>Important Dates</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>Paper submission due: Oct. 1 (Mon). 2012</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>Notification to author: Dec. 19 (Wed). 2012</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>Camera ready due: Jan. 6 (Sun). 2013</div><div><br></div><div><span class="Apple-tab-span" style="white-space:pre"> </span>*[23:59:59 Pacific Time]</div>
<div><br></div><div>==============================================================</div><div>Conference Scope</div><div><br></div><div>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.</div>
<div> </div><div>==============================================================</div><div>Topics</div><div><br></div><div>The topics of relevance for the conference papers include but not limited to the following:</div><div>
<br></div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Novel models and algorithms</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Clustering</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Classification</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Ranking</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Association analysis</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Anomaly detection</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Data pre-processing</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Feature extraction and selection</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining heterogeneous data</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining multi-source data</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining sequential data</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining spatial and temporal data</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining unstructured and semi-structured data</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining graph and network data</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Parallel, distributed, and high performance data mining on the cloud platform</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Privacy preserving data mining</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining high dimensional data</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining uncertain data</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining imbalanced data</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining dynamic/streaming data</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Statistical methods for data mining</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Visual data mining</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Interactive and online mining</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining behavioral data</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining multimedia data</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining scientific databases</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Ubiquitous knowledge discovery</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Agent-based data mining</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mining social networks</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Financial data mining</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Fraud and risk analysis</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Security and intrusion detection</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Opinion mining and sentiment analysis</div><div>
<span class="Apple-tab-span" style="white-space:pre"> </span>* Post-processing including quality assessment and validation</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Integration of data warehousing, OLAP and data mining</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Human, domain, organizational and social factors in data mining</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Applications to healthcare, bioinformatics, computational chemistry,</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Eco-informatics, marketing, online gaming, etc</div><div><br></div><div>All paper submissions will be handled electronically. Detailed instructions are provided on the conference home page.</div>
<div><br></div><div>==============================================================</div><div>Paper Submission</div><div><br></div><div>Each submitted paper should include an abstract up to 200 words. It should also adhere to the double-blind review policy and 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 <a href="http://www.springer.de/comp/lncs/authors.html">http://www.springer.de/comp/lncs/authors.html</a>) for their initial submissions. All papers must be submitted electronically through Microsoft's Conference Management Service (CMT) in PDF format only.</div>
<div><br></div><div>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.</div>
<div><br></div><div>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. Papers that do not comply with the Submission Guidelines will be rejected without review.</div>
<div><br></div><div>Before submitting your paper, please carefully read and agree with the PAKDD submission policy and no-show policy: <a href="http://pakdd.togaware.com/policy.html">http://pakdd.togaware.com/policy.html</a></div>
<div><br></div><div>==============================================================</div><div>Conference Officers</div><div><br></div><div>Honorary Co-chairs</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Jiawei Han. University of Illinois at Urbana-Champaign,USA</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Ramamohanarao Kotagiri, University of Melbourne, Australia</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Graham Williams. Australia Taxation Office, Australia</div>
<div><br></div><div>Conference Co-chairs</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Hiroshi Motoda, AFOSR/AOARD and Osaka University, Japan</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Longbing Cao. University of Technology, Sydney, Australia</div>
<div><br></div><div>Program Committee Co-chairs</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Jian Pei. Simon Fraser University, Canada</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Vincent S. Tseng. National Cheng Kung University, Taiwan</div>
<div><br></div><div>Local Arrangement Co-chairs</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Vladimir Estivill-Castro. Griffith University (Gold Coast), Australia</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Xue Li, University of Queensland, Australia</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Richi Nayak, Queensland University of Technology, Australia</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Xinhua Zhu, University of Technology, Sydney, Australia</div>
<div><br></div><div>Workshop Co-chairs</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Jiuyong Li. University of Sourth Australia, Australia</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Kay Chen Tan. National University of Singapore, Singapore</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Bo Liu. Guangdong University of Technology, China</div><div><br></div><div>Tutorial Co-chairs</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Tu Bao Ho. Japan Advanced Institute of Science and Technology, Japan </div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Mengjie Zhang. Victoria University of Wellington, New Zealand</div><div><br></div><div>Award Chair</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Chengqi Zhang, University of Technology, Sydney, Australia</div>
<div><br></div><div>Sponsorship Co-chair</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Yue Xu, Queensland University of Technology, Australia</div><div><br></div><div>Publicity Co-chairs</div><div>
<span class="Apple-tab-span" style="white-space:pre"> </span>* P.Krishna Reddy, The International Institute of Information <span class="Apple-tab-span" style="white-space:pre"> </span>* Technology, Hyderabad, India</div><div>
<span class="Apple-tab-span" style="white-space:pre"> </span>* Yifeng Zeng, Aalborg University, Denmark</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Xin Wang, University of Calgary, Canada</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span>* Zhihong Deng, Peking University, China</div><div> </div><div>==============================================================</div><div>Further Information</div>
<div><br></div><div>For further information, please contact the Program Committee Chairs by <a href="mailto:pakdd13-program@pakdd.org">pakdd13-program@pakdd.org</a> .</div><div><br></div><div>General inquiries</div><div><br>
</div><div><span class="Apple-tab-span" style="white-space:pre"> </span>* Longbing Cao</div><div><br></div><div><span class="Apple-tab-span" style="white-space:pre"> </span> University of Technology Sydney, Australia</div>
<div><br></div><div><span class="Apple-tab-span" style="white-space:pre"> </span> Email: <a href="mailto:pakdd13@pakdd.org">pakdd13@pakdd.org</a></div><div><span class="Apple-tab-span" style="white-space:pre"> </span> Phone: (61)2-9514-4477</div>
<div><span class="Apple-tab-span" style="white-space:pre"> </span> Fax: (61)2-9514-1807</div><div><br></div>