Paper Info
Title
Benchmarking Applied to Semantic Conceptual Models of Linked Financial Data
Abstract
Semantic modeling plays a central role in knowledge-based systems where information sharing and integration is a primary objective. Ontology and metadata description languages such as OWL (Web Ontology Language) and RDF(S) (Resource Description Framework Schema) are commonly the most used for representing semantic models and data. The graph-like structure adopted for semantic metadata representation allows simple and expressive queries by using SPARQL-based subgraph matching. While performance of such knowledge-based systems depends on multiple factors, in this work we present a mechanism to properly choice a semantic modeling pattern in order to significantly reduce the data query execution time. Based on this understanding, this work proposes a comparative analysis of different conceptual modeling approaches on the basis of financial domain. In order to show the efficiency/accuracy of our approach, an evaluation of SPARQL-based queries was performed against different modeled datasets.
Year
DOI
Venue
2015
10.1007/978-3-319-26138-6_32
Lecture Notes in Computer Science
Keywords
Field
DocType
Conceptual modeling,Linked Data,Performance,Semantics,SPARQL
Metadata,Conceptual model,Computer science,Linked data,SPARQL,Finance,RDF Schema,RDF,Semantics,Web Ontology Language
Conference
Volume
ISSN
Citations 
9416
0302-9743
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
José Luis Sánchez-Cervantes1468.92
Cuauhtémoc Sánchez-Ramírez2213.63
Jorge Luis García-Alcaraz341.89
Emilio Jiménez Macías453.74