Proceedings of the 23rd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

S. Matwin, Shipeng Yu, Faisal Farooq
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引用次数: 50

Abstract

It is our great pleasure to welcome you to the 2017 ACM Conference on Knowledge Discovery and Data Mining -- KDD 2017. We hope that the content and the professional networking opportunities at KDD 2017 will help you to succeed professionally by enabling you to: identify new technology trends; learn from contributed papers, presentations, and posters; discover new tools, processes and practices; identify new job opportunities; and hire new team members. The terms "Data Science", "Data Mining" and "Big Data" have, in the last few years, grown out of research labs and gained presence in the media and in everyday conversations. We also hear these terms on social media and from decision makers at various level of governments and corporations. The impact of these technologies is felt in almost every walk of life. Importantly, the current rapid progress in data science is facilitated by the timely sharing of newly discovered and developed representations and algorithms between those working in research and those interested in industrial deployment. It is the hallmark of KDD conferences in the past that they have been the bridge between theory and practise, the great facilitator and catalyst for this exchange. Researchers and practitioners meet in person and interact in a meaningful way over several days. The conference program, with its three parallel tracks - the Research Track, the Applied Data Science Track and the Applied Invited Speakers Track - brings the two groups together. Participants are welcome to freely attend any track, and the events common for all tracks. The conference this year continues with its tradition of a strong tutorial and workshop program on leading edge issues of data mining during the first two days of the program. The last three days are devoted to contributed technical papers, describing both novel, important research contributions, and deployed, innovative solutions. Three keynote talks, by Cynthia Dwork, Bin Yu, and Renee J. Miller touch on some of the hard, emerging issues before the field of data mining. With a growing industry around AI assistants, our KDD Panel brings together industry experts in this field to spawn discussions and an exchanges of ideas. We have an outstanding lineup of industry speakers sharing their experiences and expertise in deploying industrial data mining solutions. We continue a strong hands-on tutorial program, in which participants will learn how to use practical data science tools. In order to broaden the impact of KDD and to increase the participation of attendees who would greatly benefit from the conference but would have otherwise found it financially challenging to attend, we reserved a substantial budget for travel grants. KDD 2017 awarded a record USD 145k for student travel and also set aside USD 25k to enable smaller startups to attend. With the new "Meet the Experts" sessions, KDD 2017 also gives researchers and practitioners a unique opportunity to form professional networks and to share their perspectives with others interested in the various aspects of data science. We hope that the KDD 2017 conference will serve as a meeting ground for researchers, practitioners, funding agencies and investors to help create new algorithms and commercial products.
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第23届ACM SIGKDD知识发现与数据挖掘国际会议论文集
我们非常高兴地欢迎您参加2017年ACM知识发现与数据挖掘会议(KDD 2017)。我们希望KDD 2017的内容和专业交流机会将帮助您在专业上取得成功,使您能够:识别新技术趋势;从投稿的论文、演讲和海报中学习;发现新的工具、流程和实践;发现新的工作机会;并雇佣新的团队成员。在过去的几年里,“数据科学”、“数据挖掘”和“大数据”这些术语已经走出了研究实验室,出现在媒体和日常对话中。我们也会在社交媒体上以及各级政府和企业的决策者那里听到这些术语。几乎各行各业都能感受到这些技术的影响。重要的是,在研究人员和对工业部署感兴趣的人员之间及时共享新发现和开发的表示和算法,促进了当前数据科学的快速发展。过去的KDD会议的特点是,它们一直是理论与实践之间的桥梁,是这种交流的伟大促进者和催化剂。研究人员和实践者在几天内亲自会面并以有意义的方式进行互动。会议计划有三个平行的专题——研究专题、应用数据科学专题和应用特邀演讲人专题——将这两个小组聚集在一起。欢迎参与者自由参加任何赛道,以及所有赛道共同的活动。今年的会议延续了它的传统,在会议的前两天将有一个关于数据挖掘前沿问题的强有力的指导和研讨会计划。最后三天致力于发表技术论文,描述新颖的,重要的研究贡献,以及部署的,创新的解决方案。Cynthia Dwork, Bin Yu和Renee J. Miller的三个主题演讲触及了数据挖掘领域之前的一些困难和新兴问题。随着围绕人工智能助手的行业不断发展,我们的KDD小组汇集了该领域的行业专家,以产生讨论和交流思想。我们有一个杰出的行业演讲者阵容,分享他们在部署工业数据挖掘解决方案方面的经验和专业知识。我们继续一个强大的动手教程计划,参与者将学习如何使用实用的数据科学工具。为了扩大KDD的影响,并增加与会者的参与,这些与会者将从会议中受益匪浅,但否则会发现参加会议在经济上具有挑战性,我们为旅行补助金预留了大量预算。KDD 2017为学生旅行提供了创纪录的14.5万美元,并预留了2.5万美元用于支持小型初创企业参加。通过新的“与专家会面”会议,KDD 2017还为研究人员和从业者提供了一个独特的机会,可以建立专业网络,并与对数据科学各个方面感兴趣的其他人分享他们的观点。我们希望KDD 2017会议将成为研究人员、从业者、资助机构和投资者帮助创建新算法和商业产品的会议场所。
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