A Rule-Based Language for Complex Event Processing and Reasoning

Anicic, Darko; Fodor, Paul; Rudolph, Sebastian; Stühmer, Roland; Stojanović, Nenad; Studer, Rudi

doi:10.1007/978-3-642-15918-3_5

Cited by 82 publications

(79 citation statements)

References 8 publications

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“…Languages have been proposed for expressing the patterns that applications need to observe within streams: ESPER [18], FTL, and Streams Processing Language (SPL) [19]. For example, SPL is the programming language for IBM InfoSphere Streams [20], a platform for analysing Big Data in motion meaning continuous event streams at high data-transfer rates.…”

Section: Querying Event Historiesmentioning

confidence: 99%

Big Continuous Data: Dealing with Velocity by Composing Event Streams

Vargas-Solar¹,

Espinosa-Oviedo²,

Zechinelli-Martini

2016

Big Data Concepts, Theories, and Applications

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Section: Querying Event Historiesmentioning

confidence: 99%

Big Continuous Data: Dealing with Velocity by Composing Event Streams

Vargas-Solar¹,

Espinosa-Oviedo²,

Zechinelli-Martini

2016

Big Data Concepts, Theories, and Applications

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“…Complex Event Processing (CEP) is rather important for event aggregation (Anicic et al, 2010) and may be used for event compositions. CEP focuses on predefined relations and temporal patterns, typically on different streams of data or events.…”

Section: Evolutionary Event Aggregationmentioning

confidence: 99%

Facilitating the Reactive Web - A Condition Action System using Node.js

Groflin

Bosch²,

Guggisberg

et al. 2015

Proceedings of the 11th International Conference on Web Information Systems and Technologies

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Abstract:The orchestration of the Web is a big issue for Web users all around the world. Web users have a high interest in services, which are able to personalise and customise the Web. However, for Web reactivity there exists only a few limited solutions that allow the aggregation of Web resources. This paper takes a look at existing eventbased methods that build upon Event-Condition-Action (ECA) Rules and Complex Event Processing (CEP). Moreover, this paper illustrates the architecture of a fully functioning Condition Action System prototype for the creation of reactivity in between Web resources. In a proof of concept, we could detect and determine the change interval of electronic newspaper headlines. With the proposed system, we are able to orchestrate Web resources e.g. Detecting Web Changes.

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“…Indeed, rule-based processing is the underlying mechanism adopted in many reasoning tools. Moreover, a few languages based on derivation rules have been proposed in the domain of CEP [56,57].…”

Section: Related Workmentioning

confidence: 99%

Streaming the Web: Reasoning Over Dynamic Data

Margara¹,

Urbani²,

Harmelen³

et al. 2014

SSRN Journal

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a b s t r a c tIn the last few years a new research area, called stream reasoning, emerged to bridge the gap between reasoning and stream processing. While current reasoning approaches are designed to work on mainly static data, the Web is, on the other hand, extremely dynamic: information is frequently changed and updated, and new data is continuously generated from a huge number of sources, often at high rate. In other words, fresh information is constantly made available in the form of streams of new data and updates.Despite some promising investigations in the area, stream reasoning is still in its infancy, both from the perspective of models and theories development, and from the perspective of systems and tools design and implementation.The aim of this paper is threefold: (i) we identify the requirements coming from different application scenarios, and we isolate the problems they pose; (ii) we survey existing approaches and proposals in the area of stream reasoning, highlighting their strengths and limitations; (iii) we draw a research agenda to guide the future research and development of stream reasoning. In doing so, we also analyze related research fields to extract algorithms, models, techniques, and solutions that could be useful in the area of stream reasoning.

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A Rule-Based Language for Complex Event Processing and Reasoning

Cited by 82 publications

References 8 publications

Big Continuous Data: Dealing with Velocity by Composing Event Streams

Big Continuous Data: Dealing with Velocity by Composing Event Streams

Facilitating the Reactive Web - A Condition Action System using Node.js

Streaming the Web: Reasoning Over Dynamic Data

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