Real time event monitoring with trident

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Title: Real time event monitoring with trident
Authors: Brigadir, Igor
Greene, Derek
Cunningham, Pádraig
Sheridan, Gavin
Permanent link: http://hdl.handle.net/10197/5247
Date: 23-Sep-2013
Abstract: Building a scalable, fault-tolerant stream mining system that deals with realistic data volumes presents unique challenges. Considerable work is being done to make the development of such systems simpler, creating high level abstractions on top of existing systems. Many of the technical barriers can be eliminated by adopting a state-of-the-art interface, such as the Trident API for Storm. We describe a stream mining tool, based on Trident, for monitoring breaking news events on Twitter, which can be extended quickly and scaled easily.
Funding Details: Science Foundation Ireland
Type of material: Conference Publication
Keywords: Stream processing;Trident;Storm;Event monitoring
Language: en
Status of Item: Not peer reviewed
Is part of: Georg Krempl et al. (eds.) Real-World Challenges for Data Stream Mining: Proceedings of the 1st International Workshop on Real-World Challenges for Data Stream Mining, RealStream 2013, Prague, Czech Republic, September 27, 2013
Conference Details: RealStream: Real-World Challenges for Data Stream Mining workshop at European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECMLPKDD 2013), Prague, September 23th to 27th, 2013
Appears in Collections:Computer Science Research Collection

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