EnviroStream: A Stream Reasoning Benchmark for Environmental and Climate Monitoring

IF 3.7 Q2 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE Big Data and Cognitive Computing Pub Date : 2023-07-31 DOI:10.3390/bdcc7030135
Elena Mastria, Francesco Pacenza, J. Zangari, Francesco Calimeri, S. Perri, G. Terracina
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引用次数: 0

Abstract

Stream Reasoning (SR) focuses on developing advanced approaches for applying inference to dynamic data streams; it has become increasingly relevant in various application scenarios such as IoT, Smart Cities, Emergency Management, and Healthcare, despite being a relatively new field of research. The current lack of standardized formalisms and benchmarks has been hindering the comparison between different SR approaches. We proposed a new benchmark, called EnviroStream, for evaluating SR systems on weather and environmental data. The benchmark includes queries and datasets of different sizes. We adopted I-DLV-sr, a recently released SR system based on Answer Set Programming, as a baseline for query modelling and experimentation. We also showcased continuous online reasoning via a web application.
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环境和气候监测的流推理基准
流推理(SR)专注于开发将推理应用于动态数据流的高级方法;尽管它是一个相对较新的研究领域,但它在物联网、智慧城市、应急管理和医疗保健等各种应用场景中越来越重要。目前缺乏标准化的形式和基准已经阻碍了不同SR方法之间的比较。我们提出了一个新的基准,称为EnviroStream,用于评估SR系统的天气和环境数据。基准测试包括不同大小的查询和数据集。我们采用了I-DLV-sr,一个最近发布的基于答案集编程的SR系统,作为查询建模和实验的基线。我们还通过一个web应用程序展示了连续的在线推理。
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来源期刊
Big Data and Cognitive Computing
Big Data and Cognitive Computing Business, Management and Accounting-Management Information Systems
CiteScore
7.10
自引率
8.10%
发文量
128
审稿时长
11 weeks
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