第16届ACM SIGKDD知识发现与数据挖掘国际会议论文集

Bharat Rao, Balaji Krishnapuram, A. Tomkins, Qiang Yang
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引用次数: 25

摘要

第16届ACM SIGKDD知识发现与数据挖掘国际会议于2010年7月24日至28日在美国华盛顿特区举行。KDD是知识发现和数据挖掘领域研究成果和实践经验交流的主要国际论坛。随着组织和个人可用的数据量持续快速增长,并且从中提取有用知识的需求变得更加强烈,科学家、政府工作人员和业务人员转向KDD社区寻求解决方案。本卷简要介绍了这一领域一年的发展情况;我们希望你会发现它是有用的和有益的。KDD-2010技术计划包括四个平行的研究轨道和一个工业/政府轨道。该计划还包括来自领先的KDD技术创作者和消费者的主题演讲,12个研讨会,12个教程和一个小组讨论。2010年KDD杯比赛的重点是教育数据挖掘,以支持计算机辅助教学领域的改进。来自供应商和其他组织的数十个技术演示和展览强调了会议作为主要行业和学术论坛的双重作用,以讨论该研究领域的进展。此次论文征集活动吸引了来自世界各地的578篇研究论文和101份工业和政府意见书。每篇论文都由项目委员会的三位成员独立审查,以评估其独创性、重要性、技术质量和表达的清晰度。今年的研究轨道在评审过程中引入了作者反馈阶段,在这个阶段,作者被邀请对他们收到的初步评审发表评论。反馈阶段的目标是确保更大的透明度和公平性,因为作者的回应会在随后的讨论阶段由高级项目委员会(SPC)成员主持。在最终决定之前的后续讨论阶段,审稿人之间进行了许多讨论。最终,计划委员会接受了77篇长篇报告和24篇短篇报告进入研究轨道,总体录取率为17.4%。今年的行业和政府专题强调了KDD技术的成功应用,包括整合KDD技术的部署应用,以及从行业和政府的大型数据集中发现有效、新颖、可理解和明显有用的模式,以及新兴的应用和技术,包括尝试部署KDD技术来解决特定行业或政府问题所产生的挑战和问题。本次会议的行业和政府轨道共接收了11篇长篇论文和9篇短篇论文,总录取率为19.8%。我们高兴地看到,这次会议仍然具有很强的竞争性和很高的质量。由此产生的项目以其多样性和活力而著称。除了传统的KDD主题,如分类、聚类、频繁集和时间数据,我们还看到了一些快速增长的领域的论文,如社交网络和图挖掘、隐私、推荐、排名、主题建模和迁移学习。应用程序领域包括Web、生物信息学、移动数据、医疗保健、市场营销和许多其他领域。
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Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining
KDD-2010, the 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, is being held in Washington, DC, USA, on July 24--28, 2010. KDD is the leading international forum for the exchange of research results and practical experience in the field of knowledge discovery and data mining. As the quantity of data available to organizations and individuals continues to grow rapidly, and the need to extract useful knowledge from them becomes more intense, scientists, government workers and business people turn to the KDD community for solutions. This volume contains a snapshot of a year of developments in this field; we hope you will find it useful and rewarding. The KDD-2010 technical program features four parallel research tracks and an industrial / government track. The program also features keynotes from leading creators and consumers of KDD technology, 12 workshops, 12 tutorials and one panel. The 2010 KDD Cup competition focuses on educational data mining to support improvements in the field of computer aided instruction. Dozens of technical demonstrations and exhibits from vendors and other organizations underscore the conference's dual role as the leading industry and academic forum to discuss the advances in this field of research. The call for papers attracted 578 research papers and 101 industrial and government submissions from around the world. Each paper was independently reviewed by three members of the program committee for originality, significance, technical quality, and clarity of presentation. This year's research track introduced an author-feedback phase in the review process, in which authors were invited to comment on the preliminary reviews that they received. The objective of the feedback phase is to ensure greater transparency and fairness, as the authors' responses are taken into account in a subsequent discussion phase moderated by Senior Program Committee (SPC) members. There was much discussion among the reviewers in the subsequent discussion phase before the final decisions. In the end, the program committee accepted 77 papers for long presentations and 24 papers for short presentations into the research track, representing an aggregated acceptance rate of 17.4%. This year's Industry and Government track emphasized the successful uses of KDD technology, including deployed applications incorporating KDD technologies and discoveries of valid, novel, understandable, and demonstrably useful patterns from large datasets in industry and government, as well as emerging applications and technology, including challenges and issues arising from attempts to deploy KDD technology to solve specific industry or government problems. The industry and government track of the conference accepted 11 papers for long presentations and 9 papers for short presentations into the program, representing an aggregated acceptance rate of 19.8%. We are glad to see that the conference remains strongly competitive and of very high quality. The resulting program was notable for its diversity and vitality. Alongside traditional KDD topics like classification, clustering, frequent sets, and temporal data, we also saw papers in rapidly growing areas like social network and graph mining, privacy, recommendation, ranking, topic modeling and transfer learning. Application areas included the Web, bio-informatics, mobility data, healthcare, marketing, and many others.
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