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Parallel Search Through Statistical Semantic Spaces for Querying Big RDF Data

Authors:
Alexey Cheptsov
Axel Tenschert

Keywords: Statistical Semantics; Random Indexing; Parallelization; High Performance Computing; Message-Passing Interface;JUNIPER

Abstract:
With billions of triples in the Linked Open Data cloud, which continues to grow exponentially, challenging tasks start to emerge related to the exploitation and reasoning of Web data. A considerable amount of work has been done in the area of using Information Retrieval (IR) methods to address these problems. However, although applied models work on the Web scale, they downgrade the semantics contained in an RDF graph by observing each physical resource as a ’bag of words (URIs/literals)’. Distributional statistic methods can address this problem by capturing the structure of the graph more efficiently. However, these methods are computationally expensive. In this paper, we describe the parallelization algorithm of one such method (Random Indexing) based on the Message-Passing Interface technology. Our evaluation results show super linear improvement.

Pages: 1 to 6

Copyright: Copyright (c) IARIA, 2013

Publication date: September 29, 2013

Published in: conference

ISSN: 2308-4510

ISBN: 978-1-61208-293-6

Location: Porto, Portugal

Dates: from September 29, 2013 to October 3, 2013