Comparison of a Deductive Database with a Semantic Web reasoning engine

2010 ◽  
Vol 23 (6) ◽  
pp. 634-642 ◽  
Author(s):  
Simone A. Ludwig
2019 ◽  
Vol 8 (4) ◽  
pp. 2531-2539

The major benefit of working on Ontology Web Language (OWL) is its ability to define semantics such that the information becomes more valuable. To realize the full power of semantics, it is essential to integrate a reasoning engine to it. The software codes that perform inferences are often referred to as reasoning engines or reasoners. The reasoners can be classified into categories: tableau based and rule based reasoners. The rule based reasoners combines the assertions with a set of logical rules to infer new knowledge chunks. The Jena framework offers several ways to integrate rule based reasoners programmatically. The operation is similar to creating a more advanced model from a simpler one. The objective of this paper is to list and classify the reasoners according to OWL 2 profiles thereafter the focus of this study is to develop a model which evaluate the performance of Semantic Web Reasoner based on few parameters.


2019 ◽  
pp. 016555151986549
Author(s):  
Enayat Rajabi ◽  
Salvador Sanchez-Alonso

The Semantic Web allows knowledge discovery on graph-based data sets and facilitates answering complex queries that are extremely difficult to achieve using traditional database approaches. Intuitively, the Semantic Web query language (SPARQL) has a ‘property path’ feature that enables knowledge discovery in a knowledgebase using its reasoning engine. In this article, we utilise the property path of SPARQL and the other Semantic Web technologies to answer sophisticated queries posed over a disease data set. To this aim, we transform data from a disease web portal to a graph-based data set by designing an ontology, present a template to define the queries and provide a set of conjunctive queries on the data set. We illustrate how the reasoning engine of ‘property path’ feature of SPARQL can retrieve the results from the designed knowledgebase. The results of this study were verified by two domain experts as well as authors’ manual exploration on the disease web portal.


Informatica ◽  
2015 ◽  
Vol 26 (2) ◽  
pp. 221-240 ◽  
Author(s):  
Valentina Dagienė ◽  
Daina Gudonienė ◽  
Renata Burbaitė

2018 ◽  
Vol 6 (1) ◽  
pp. 132-140
Author(s):  
Ranjna Jain ◽  
◽  
Neelam Duhan ◽  
A.K.Sharma . ◽  
◽  
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