Predicate clustering-based entity-centered graph pattern recognition for query extension on the LOD

1Citations
Citations of this article
4Readers
Mendeley users who have this article in their library.
Get full text

Abstract

In this paper, we propose a method to reduce the difficulties of query caused by lack of information about graph patterns even though the graph pattern is one of the important characteristics of the LOD. To do so, we apply the clustering methodology to find the RDF predicates that have similar patterns. In addition, we identify representative graph patterns that imply its characteristics each cluster. The representative graph patterns are used to extend the users’ query graphs. To show the difficulties of the query on the LOD, we developed an illustrative example. We propose the novel framework to support query extension using predicate clustering-based entity-centered graph patterns. Through the implementation of this framework, the user can easily query the LOD and at the same time collect appropriate query results.

Cite

CITATION STYLE

APA

Kim, J., Kong, J., Park, D., & Sohn, M. (2019). Predicate clustering-based entity-centered graph pattern recognition for query extension on the LOD. In Advances in Intelligent Systems and Computing (Vol. 773, pp. 159–170). Springer Verlag. https://doi.org/10.1007/978-3-319-93554-6_14

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free