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[交流] PAKDD 2013（第17届亚太地区知识发现与数据挖掘国际会议）征文通知

会议城市:

黄金海岸，澳大利亚 (Gold Coast, Australia)

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截稿日期:

2012年10月1日

PAKDD 2013（第17届亚太地区知识发现与数据挖掘国际会议）征文通知
　　黄金海岸，澳大利亚 (Gold Coast, Australia)
　　2013年4月14日—2013年4月17日
　 https://pakdd2013.pakdd.org/

The 17th Pacific-Asia Conference on Knowledge Discovery and Data Mining
Gold Coast, Australia
Conference Website
https://pakdd2013.pakdd.org/

Call For Papers PAKDD 2013

Important Dates
Paper submission due: Oct. 1 (Mon). 2012
Notification to author: Dec. 19 (Wed). 2012
Camera ready due: Jan. 6 (Sun). 2013
*[23:59:59 Pacific Standard Time]

Conference Scope
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.

Topics
The topics of relevance for the conference papers include but not limited to the following:

* Novel models and algorithms

* Clustering

* Classification

* Ranking

* Association analysis

* Anomaly detection

* Data pre-processing

* Feature extraction and selection

* Mining heterogeneous data

* Mining multi-source data

* Mining sequential data

* Mining spatial and temporal data

* Mining unstructured and semi-structured data

* Mining graph and network data

* Parallel, distributed, and high performance data mining on the cloud platform

* Privacy preserving data mining

* Mining high dimensional data

* Mining uncertain data

* Mining imbalanced data

* Mining dynamic/streaming data

* Statistical methods for data mining

* Visual data mining

* Interactive and online mining

* Mining behavioral data

* Mining multimedia data

* Mining scientific databases

* Ubiquitous knowledge discovery

* Agent-based data mining

* Mining social networks

* Financial data mining

* Fraud and risk analysis

* Security and intrusion detection

* Opinion mining and sentiment analysis

* Post-processing including quality assessment and validation

* Integration of data warehousing, OLAP and data mining

* Human, domain, organizational and social factors in data mining

* Applications to healthcare, bioinformatics, computational chemistry,

* Eco-informatics, marketing, online gaming, etc

All paper submissions will be handled electronically. Detailed instructions are provided on the conference home page.

Paper Submission
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 https://www.springer.de/comp/lncs/authors.html) for their initial submissions. All papers must be submitted electronically through Microsoft's Conference Management Service (CMT) 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.

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.

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

Conference Officers
Honorary Co-chairs
Jiawei Han. University of Illinois at Urbana-Champaign,USA
Ramamohanarao Kotagiri, University of Melbourne, Australia
Graham Williams. Australia Taxation Office, Australia

Conference Co-chairs
Hiroshi Motoda, AFOSR/AOARD and Osaka University, Japan
Longbing Cao. University of Technology, Sydney, Australia

Program Committee Co-chairs
Jian Pei. Simon Fraser University, Canada
Vincent S. Tseng. National Cheng Kung University, Taiwan

Local Arrangement Co-chairs
Vladimir Estivill-Castro. Griffith University (Gold Coast), Australia
Xue Li, University of Queensland, Australia
Richi Nayak, Queensland University of Technology, Australia
Xinhua Zhu, University of Technology, Sydney, Australia

Workshop Co-chairs
Jiuyong Li. University of South Australia, Australia
Kay Chen Tan. National University of Singapore, Singapore
Bo Liu. Guangdong University of Technology, China

Tutorial Co-chairs
Tu Bao Ho. Japan Advanced Institute of Science and Technology, Japan
Mengjie Zhang. Victoria University of Wellington, New Zealand

Award Chair
Chengqi Zhang, University of Technology, Sydney, Australia

Sponsorship Co-chair
Yue Xu, Queensland University of Technology, Australia

Publicity Co-chairs
P.Krishna Reddy, The International Institute of Information Technology, Hyderabad, India
Yifeng Zeng, Aalborg University, Denmark
Xin Wang, University of Calgary, Canada
Zhihong Deng, Peking University, China

Further Information
For further information, please contact the Program Committee Chairs by pakdd13-program@pakdd.org This e-mail address is being protected from spambots. You need JavaScript enabled to view it .

General inquiries

Longbing Cao

University of Technology Sydney, Australia

Email: pakdd13@pakdd.org This e-mail address is being protected from spambots. You need JavaScript enabled to view it

Phone: (61)2-9514-4477

Fax: (61)2-9514-1807

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