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http://dx.doi.org/10.3745/KTSDE.2016.5.11.569

MRSPAKE : A Web-Scale Spatial Knowledge Extractor Using Hadoop MapReduce  

Lee, Seok-Jun (경기대학교 컴퓨터과학과)
Kim, In-Cheol (경기대학교 컴퓨터과학과)
Publication Information
KIPS Transactions on Software and Data Engineering / v.5, no.11, 2016 , pp. 569-584 More about this Journal
Abstract
In this paper, we present a spatial knowledge extractor implemented in Hadoop MapReduce parallel, distributed computing environment. From a large spatial dataset, this knowledge extractor automatically derives a qualitative spatial knowledge base, which consists of both topological and directional relations on pairs of two spatial objects. By using R-tree index and range queries over a distributed spatial data file on HDFS, the MapReduce-enabled spatial knowledge extractor, MRSPAKE, can produce a web-scale spatial knowledge base in highly efficient way. In experiments with the well-known open spatial dataset, Open Street Map (OSM), the proposed web-scale spatial knowledge extractor, MRSPAKE, showed high performance and scalability.
Keywords
Spatial Knowledge Extraction; Topological Relation; Directional Relation; Hadoop MapReduce;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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