The DEBS 2018 Grand Challenge

Vincenzo Gulisano, Zbigniew Jerzak, Pavel Smirnov, M. Strohbach, H. Ziekow, D. Zissis
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引用次数: 22

Abstract

The ACM DEBS 2018 Grand Challenge is the eighth in a series of challenges which seek to provide a common ground and evaluation criteria for a competition aimed at both research and industrial event-based systems. The focus of the 2018 Grand Challenge is on the application of machine learning to spatio-temporal streaming data. The goal of the challenge is to make the naval transportation industry more reliable by providing predictions for vessels' destinations and arrival times. This paper describes the specifics of the data streams and queries that define the DEBS 2018 Grand Challenge. It also describes the benchmarking platform that supports testing of corresponding solutions.
DEBS 2018大挑战
ACM DEBS 2018大挑战赛是一系列挑战中的第八次,旨在为研究和基于工业事件的系统的竞赛提供共同的基础和评估标准。2018年大挑战的重点是将机器学习应用于时空流数据。这项挑战的目标是通过提供船舶目的地和到达时间的预测,使海军运输业更加可靠。本文描述了定义DEBS 2018大挑战的数据流和查询的细节。它还描述了支持测试相应解决方案的基准测试平台。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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