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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
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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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28楼2012-07-13 18:52:08
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落花剑雨6楼
2012-07-13 17:42
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ttwolf(金币+1): 谢谢参与

假大空7楼
2012-07-13 17:45
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ttwolf(金币+1): 谢谢参与












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