A QUERY BASED GRAPH-ORIENTED LOAD-SHEDDING FOR RDF STREAM PROCESSING

被引：0
作者：
Belghaouti, Fethi [1 ]
Bouzeghoub, Amel [1 ]
Aoul, Zakia Kazi [2 ]
Chiky, Raja [2 ]
机构：
[1] Univ Paris Saclay, CNRS, Telecom SudParis, SAMOVAR, 9 Rue Charles Fourier, F-91011 Evry, France
[2] Inst Super Elect Paris, 28 Rue Notre Dame Champs, F-75006 Paris, France
来源：
2016 INTERNATIONAL WORKSHOP ON COMPUTATIONAL INTELLIGENCE FOR MULTIMEDIA UNDERSTANDING (IWCIM) | 2016年
关键词：
Big Data; Semantic Web; Semantic Data Stream; Sampling; Load-Shedding;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
To cope with heterogeneity of data in streams, Semantic Web technologies (RDF1/SPARQL(2)) have recently been used for annotation, publication and reasoning on these data. To deal with this new kind of streams, researchers have proposed new systems named RDF Stream Processing (RSP). Unfortunately, in limited system resources environment, these systems are fallible as soon as their maximum supported speed is reached. To overcome these problems, some efforts have been done in this area. Most of them, based on a triple-oriented approach and according to a probabilistic method, decrease the volume of RDF data stream using load-shedding techniques. In this paper we propose an enhancement of a Graph-Oriented approach for load-shedding semantic data streams, by considering the continuous query as input. Conducted experiments show that we can keep the RSP's recall at 100% even if we drop more than half of data.
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页数：5
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