Advanced SearchSearch Tips
MRQUTER : A Parallel Qualitative Temporal Reasoner Using MapReduce Framework
facebook(new window)  Pirnt(new window) E-mail(new window) Excel Download
 Title & Authors
MRQUTER : A Parallel Qualitative Temporal Reasoner Using MapReduce Framework
Kim, Jonghoon; Kim, Incheol;
  PDF(new window)
In order to meet rapid changes of Web information, it is necessary to extend the current Web technologies to represent both the valid time and location of each fact and knowledge, and reason their relationships. Until recently, many researches on qualitative temporal reasoning have been conducted in laboratory-scale, dealing with small knowledge bases. However, in this paper, we propose the design and implementation of a parallel qualitative temporal reasoner, MRQUTER, which can make reasoning over Web-scale large knowledge bases. This parallel temporal reasoner was built on a Hadoop cluster system using the MapReduce parallel programming framework. It decomposes the entire qualitative temporal reasoning process into several MapReduce jobs such as the encoding and decoding job, the inverse and equal reasoning job, the transitive reasoning job, the refining job, and applies some optimization techniques into each component reasoning job implemented with a pair of Map and Reduce functions. Through experiments using large benchmarking temporal knowledge bases, MRQUTER shows high reasoning performance and scalability.
Qualitative Temporal Reasoning;Disjunctive Relations;Composition Table;MapReduce;Parallel Temporal Reasoner;
 Cited by
W3C Recommendation, "OWL Web Ontology Language Semantics and Abstract Syntax," http://www.w3org/TR/owl-ref/, 2004.

C. Gutierrez, C. Hurtado, and A. Vaisman, "Temporal RDF," Proceedings of European Semantic Web Conference, 2005.

V. Milea, F. Frasincar, and U. Kaymak, "tOWL: A Temporal Web Ontology Language," IEEE Transactions on Systems, Man, Cybernetics, Vol.42, No.1, pp.268-281, 2011.

K. Kyzirakos, "The Data Model stRDF and the Query language stSPARQL," Proceedings of OGC/W3C Spatial Data on the Web WG, Barcelona, March 11, 2015.

A. Salguero, C. Delgado, and F. Araque, "STOWL: An OWL Extension for Facilitating the Definition of Taxonomies in Spatio-temporal Ontologies," Lecture Notes in Computer Science, Vol.5736, pp.336-345, 2009.

F. Grandi, "T-SPARQL: A TSQL2-like Teporal Query Language for RDF," Proceedings of the International Workshop on Querying Graph Structured Data, pp.21-30, 2010.

M. Vilain, H. Kautz, and P. Van Beek, "Constraint Propagation Algorithm for Temporal Reasoning," Proceedings of the 5th. National Conference on Artificial Intelligence, 1986.

J. F. Allen, "Maintaining Knowledge about Temporal Intervals," Communications of the ACM, Vol.26, pp.832-843, 1983. crossref(new window)

Z. Gantner, M. Westphal, and S. Wolfl, "GQR-A Fast Reasoner for Binary Qualitative Constraint Calculi," Proceedings of AAAI. Vol.8, 2008.

S. Batsakis, and E. G. M. Petrakis, "SOWL: A Framework for Handling Spatio-Temporal Information in Owl 2.0," Proceedings of International Symposium on RuleMl, Vol. 6826, pp.242-249, 2011.

E. Anagnostopoulos, E. G. M. Petrakis, and S. Bastsakis "CHRONOS: Improving the Performance of Qualitative Temporal Reasoning in OWL," Proceedings of IEEE International Conference on Tools with Artificial intelligence, pp.309-345, 2014.

S. Batsakis, K. Stravoskoufos, and E.G.M. Petrakis, "Temporal Reasoning for Supporting Temporal Queries in OWL 2.0," Proceedings of International Conference on KES, pp.558-567, 2011.

T. Gunarathne, "Hadoop MapReduce v2 Cookbook," Packt Publishing, 2015.

I. Horrocks, P. F. Patel-Schneider, H. Boley, S. Tabet, B. Grosof, and M. Dean, "SWRL: A Semantic Web Rule Language Combining OWL and RuleML," W3C Member submission, 2004.

M. Stocker and E. Sirin, "PelletSpatial: A Hybrid RCC-8 and RDF/OWL Reasoning and Query Engine," OWLED, Vol. 529, 2009.

H. Karau, A. Konwinski, P. Wendell, and M. Zaharia, "Learning Spark: Lightning-Fast Big Data Analysis," O'Reilly Media, 2015.