人在循环数据分析研讨会论文集

Carsten Binnig, A. Fekete, Arnab Nandi
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引用次数: 3

摘要

我们很高兴地介绍2016年6月26日在美国加利福尼亚州旧金山举行的ACM SIGMOD会议的第一届HILDA人机循环数据分析研讨会的论文。在设计数据管理系统时,一个经常被忽视的组件是与之交互的一组用户(人在循环中)。当今数据分析的一个主要瓶颈是有效地利用人类的能力来制定问题并理解数据分析系统的答案。在数据库社区中,朝着这个方向的第一批远景论文讨论了诸如交互式数据探索或具有更直观用户界面的查询数据管理系统等主题。最近的技术趋势(如触摸屏、运动检测和语音识别)正在扩大用户与数据交互的可能性,数据驱动的行业正在转向个性化处理,以更好地针对用户的需求提供服务。我们创建HILDA是为了扩大数据分析的范围,让人们意识到这一点。HILDA的一个主要目标是将数据库社区的研究人员和实践者与各种其他社区(如HCI社区或信息可视化社区)聚集在一起。我们寻找提出创新方案以改进人们使用数据管理系统的方式的论文,以及研究人类如何使用现有系统的论文。我们明确要求提交的文件必须呈现出最初的想法和愿景,就像早期结果的报告一样,或者是对完成项目的反思。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Proceedings of the Workshop on Human-In-the-Loop Data Analytics
We are delighted to present the papers from the first HILDA Workshop on Human-in-the-Loop Data Analytics, which took place on 26 June, 2016 co-located with the ACM SIGMOD conference in San Francisco, California, USA. An often overlooked component when designing a data management system is the set of users interacting with it { the human-in-the-loop. A major bottleneck in data analytics today is to efficiently leverage the human capabilities to formulate questions and understand answers of data analytics systems. In the database community the first vision papers towards that direction discussed topics such as interactive data exploration or querying data management systems with more intuitive user interfaces. Recent technology trends (such as touch screens, motion detection, and voice recognition) are widening the possibilities for users to interact with data, and data-driven industries are shifting to personalized processing to better target their services to the users' needs. We created HILDA to broaden the scope of how data analytics can be done with the awareness of people. A major goal of HILDA was to bring together researchers and practitioners from the database community with various other communities such as the HCI community or the Information Visualization community. We sought papers that propose innovations to improve the way people can work with data management systems, and also work that studies how humans work with existing systems. We explicitly asked for submissions that present initial ideas and visions, just as much as reports on early results, or reflections on completed projects.
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