Efficient Finding Relationship between Individuals in a Mass Ontology Database

Seo, Dongmin; Koo, Hee Kwan; Lee, Seungwoo; Kim, Pyung; Jung, Hanmin; Sung, Wing-Kin

doi:10.1007/978-3-642-27210-3_37

Cited by 8 publications

(6 citation statements)

References 1 publication

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“…However, these approaches have the generality drawbacks, because materializing all possible path expressions is not a viable approach [16]. OntoRelfinder [9] also precalculates and materializes path expressions, but the scope is within the triples of the RDF schema classes. Excluding instance triples from precomputing scope enables the OntoRelfinder system to precalculate and store all possible RDF schema class path expressions, which they called class path, into a distinct relational table.…”

Section: Related Workmentioning

confidence: 99%

“…if V is not visited then (8) for each path ins ∈ INS | lastNode ( ins ) = do (9) ins ← append ( ins , )…”

Section: Distributed and Parallel Path Query Using Class Pathmentioning

confidence: 99%

“…In the field of generic Semantic Web technology, several relationship finding services have been proposed. Microsoft coauthor path (http://academic.research.microsoft .com/VisualExplorer), Relfinder [8], and OntoRelfinder [9] are the examples of relationship finding services which retrieve relationships between two given objects of interest from Resource Description Framework (RDF) graph. RDF is a language for representing information about resources in the World Wide Web.…”

Section: Introductionmentioning

confidence: 99%

“…Despite the advantage of the path query, the path query processing requires computationally expensive graph search operations which involve multiple self-joins. In this study we adopt the way OntoRelfinder [9] precalculates and materializes class paths, but we propose a different path querying scheme that utilizes the precalculated class paths. In this paper we propose a novel RDF path querying scheme which utilizes bidirectional BFS algorithm combined with class path lookup scheme to reduce search space in path query processing.…”

Section: Introductionmentioning

confidence: 99%

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Distributed and Parallel Path Query Processing for Semantic Sensor Networks

Jung

Seo

Lee

et al. 2014

International Journal of Distributed Sensor Networks

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As the sensor networks are broadly used in diverse range of applications, Semantic Web technologies have been adopted as a means to manage the huge amount of heterogeneous sensor nodes and their observation data. Large amount of sensor data are annotated with spatial, temporal, and thematic semantic metadata. As a consequence, efficient query processing over large RDF graph is becoming more important in retrieving contextual information from semantic sensor data. In this paper we propose a novel path querying scheme which uses RDF schema information. By utilizing the class path expressions precalculated from RDF schema, the graph search space is significantly reduced. Compared with the conventional BFS algorithm, the proposed algorithm (bidirectional BFS combined with class path lookup approach) achieves performance improvement by 3 orders of magnitude. Additionally, we show that the proposed algorithm is efficiently parallelizable, and thus, the proposed algorithm returns graph search results within a reasonable response time on even much larger RDF graph.

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Section: Related Workmentioning

confidence: 99%

“…if V is not visited then (8) for each path ins ∈ INS | lastNode ( ins ) = do (9) ins ← append ( ins , )…”

Section: Distributed and Parallel Path Query Using Class Pathmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Distributed and Parallel Path Query Processing for Semantic Sensor Networks

Jung

Seo

Lee

et al. 2014

International Journal of Distributed Sensor Networks

Self Cite

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“…Contrasting with RelFinder, Seo et al [25] proposed the OntoRelFinder that uses a RDF Schema for finding semantic associations between two entities through its class links. Scarlet [23,24] is another approach that relies on different schemas to identify relationships between entities.…”

Section: Related Workmentioning

confidence: 99%

Combining a Co-occurrence-Based and a Semantic Measure for Entity Linking

Nunes

Dietze

Casanova

et al. 2013

The Semantic Web: Semantics and Big Data

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Abstract. One key feature of the Semantic Web lies in the ability to link related Web resources. However, while relations within particular datasets are often well-defined, links between disparate datasets and corpora of Web resources are rare. The increasingly widespread use of cross-domain reference datasets, such as Freebase and DBpedia for annotating and enriching datasets as well as documents, opens up opportunities to exploit their inherent semantic relationships to align disparate Web resources. In this paper, we present a combined approach to uncover relationships between disparate entities which exploits (a) graph analysis of reference datasets together with (b) entity co-occurrence on the Web with the help of search engines. In (a), we introduce a novel approach adopted and applied from social network theory to measure the connectivity between given entities in reference datasets. The connectivity measures are used to identify connected Web resources. Finally, we present a thorough evaluation of our approach using a publicly available dataset and introduce a comparison with established measures in the field.

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