• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Proceedings of the Sixth Australasian conference on Data mining and analytics >Measuring data-driven ontology changes using text mining
【24h】

Measuring data-driven ontology changes using text mining

机译：使用文本挖掘来测量数据驱动的本体更改

获取原文
获取原文并翻译 | 示例
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

The Australasian Data Mining Conference series AusDM, started in 2002, is the annual flagship meeting for data mining and analytics professionals in Australia. Both scholars and practitioners present the stateof- the-art in the field. Endorsed by the peak professional body, the Institute of Analytics Professionals of Australia, AusDM has developed a unique profile in nurturing this joint community. The conference series has grown in size each year from early workshops held in Canberra (2002, 2003) and Cairns (2004) to conferences in Sydney (2005, 2006). This year we are delighted to be co-hosted with the Twentieth Australian Joint Conference on Artificial Intelligence on the Gold Coast, Queensland, and the Second International Workshop on Integrating AI and Data Mining. This year''s event has been supported by >• Togaware, again hosting the website and the conference management system, coordinating the review process and other essential expertise; >• Griffith University for providing the venue, registration facilities and various other support; >• the Institute of Analytic Professionals of Australia (IAPA) for facilitating the contacts with the industry; >• the ARC Research Network on Data Mining and Knowledge Discovery, for providing financial support; >• the e-Markets Research Group, for providing essential expertise for the event; >• the Australian Computer Society, for publishing the conference proceedings; >• StatSoft for their support; >• data mining postgraduate students from Queensland University of Technology for their local support. >This year the Steering Committee and IAPA have recognised the importance of education in data mining and we have included a special panel session devoted to Data Mining Education. Also this year, for the first time, we have presented a Best Paper Award (voted by the peer review) and a Best Presentation Award (voted by conference delegates). We are delighted to expand the social program this year and hope that conference attendees will enjoy this extra time to make new contacts and to trade "war stories". >The conference program committee reviewed 69 submissions. This was an almost 20% increase in the number of submissions from last year. From these submissions 26 were selected for publication and presentation. This was an acceptance rate of 38%. AusDM follows a rigid double blind peer-review process and ranking-based paper selection process. All papers were extensively reviewed by at least three referees drawn from the program committee. We would like to note that the cut-off threshold has been high (5 on a 7 point scale). This is testament to the high quality of submissions. We would like to thank all those who submitted their work to the conference. We will continue to extend the conference format to be able to accommodate more presentations. We are proud to include in these proceedings the papers from the Second International Workshop on Integrating AI and Data Mining. Papers published in both volumes by the Australian Computer Society are indexed and available for download. >Data mining and analytics today have advanced rapidly from the early days of pattern finding in commercial databases. They are now a core part of business intelligence and inform decision making in many areas of human endeavour including science, business, health care and security. Mining of unstructured text, semi-structured web information and multimedia data have continued to receive attention, as have professional challenges to using data mining in industry. Accepted submissions have been grouped into seven sessions reflecting these application areas. Three invited industry keynote sessions put the research into context.
机译：澳大利亚数据挖掘会议系列AusDM始于2002年，是澳大利亚数据挖掘和分析专业人员的年度旗舰会议。学者和实践者都介绍了该领域的最新技术。 AusDM得到了澳大利亚分析专业人士协会的鼎力支持，在培育这一联合社区方面已树立了独特的形象。从堪培拉（2002，2003）和凯恩斯（2004）举行的早期研讨会到悉尼（2005，2006）的研讨会，会议系列的规模每年都在增加。今年，我们很高兴与昆士兰州黄金海岸举行的第二十届澳大利亚人工智能联合会议以及第二届人工智能与数据挖掘集成国际研讨会共同举办。今年的活动得到了

•Togaware的支持，Togaware再次托管了网站和会议管理系统，协调了审核过程和其他必要的专业知识；

•格里菲斯大学（Griffith University）提供场地，注册设施和各种其他支持；

•澳大利亚分析专业协会（IAPA），以促进与行业的联系；

•ARC研究网络数据挖掘和知识发现，用于提供财务支持；

•电子市场研究小组，用于为活动提供必要的专业知识；

•澳大利亚计算机协会，用于发布会议程序；

•StatSoft的支持；

•昆士兰科技大学的数据挖掘研究生在本地的支持。

今年，指导委员会IAPA和IAPA已经认识到教育在数据挖掘中的重要性，并且我们专门举办了专门的小组会议数据挖掘教育。同样也是今年，我们第一次获得了最佳论文奖（由同行评审投票）和最佳演示奖（由会议代表投票）。我们很高兴今年扩大社交计划，并希望与会人员将有更多的空闲时间来建立新的联系并交换“战争故事”。

会议计划委员会审查了69份呈件。与去年相比，提交的数量几乎增加了20％。从这些提交物中选择了26种进行发表和介绍。接受率为38％。 AusDM遵循严格的双盲同行评审过程和基于排名的论文选择过程。从计划委员会选出的至少三名裁判员对所有论文进行了广泛的审查。我们要指出，截止阈值很高（在7分制中为5）。这证明了提交的高质量。我们要感谢所有向会议提交工作的人员。我们将继续扩展会议格式，以容纳更多的演示文稿。我们很自豪地将第二届AI与数据挖掘集成国际研讨会的论文纳入这些程序。澳大利亚计算机学会在这两卷书上发表的论文都被索引并可以下载。

从商业数据库中模式发现的早期开始，今天的数据挖掘和分析迅速发展。现在，它们已成为商业智能的核心部分，可为人类在许多领域的决策提供信息，包括科学，商业，医疗保健和安全。非结构化文本，半结构化Web信息和多媒体数据的挖掘一直受到关注，在工业中使用数据挖掘也面临着专业挑战。接受的意见分为七个会议，反映了这些应用领域。三场受邀的行业主题演讲将研究纳入了背景。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号