scholarly journals Twitter Fake Account Detection and Classification using Ontological Engineering and Semantic Web Rule Language

2020 ◽  
Vol 6 (4) ◽  
Author(s):  
MOHAMMED JABARDI ◽  
Asaad Sabah Hadi
Keyword(s):  
Semantic Web ◽  
Ontological Engineering ◽  
Semantic Web Rule Language

SWRLx

2018 ◽  
pp. 348-367
Author(s):  
Souad Bouaicha ◽  
Zizette Boufaida
Keyword(s):  
Semantic Web ◽  
Knowledge Base ◽  
Object Oriented ◽  
Web Ontology Language ◽  
Rule Engine ◽  
Ontology Language ◽  
New Knowledge ◽  
Semantic Web Rule Language

Although OWL (Web Ontology Language) and SWRL (Semantic Web Rule Language) add considerable expressiveness to the Semantic Web, they do have expressive limitations. For some reasoning problems, it is necessary to modify existing knowledge in an ontology. This kind of problem cannot be fully resolved by OWL and SWRL, as they only support monotonic inference. In this paper, the authors propose SWRLx (Extended Semantic Web Rule Language) as an extension to the SWRL rules. The set of rules obtained with SWRLx are posted to the Jess engine using rewrite meta-rules. The reason for this combination is that it allows the inference of new knowledge and storing it in the knowledge base. The authors propose a formalism for SWRLx along with its implementation through an adaptation of different object-oriented techniques. The Jess rule engine is used to transform these techniques to the Jess model. The authors include a demonstration that demonstrates the importance of this kind of reasoning. In order to verify their proposal, they use a case study inherent to interpretation of a preventive medical check-up.

scholarly journals Finding Knowledge from Indonesian Traditional Medicine using Semantic Web Rule Language

2017 ◽  
Vol 7 (6) ◽  
pp. 3674 ◽  
Author(s):  
Ridowati Gunawan ◽  
Khabib Mustofa
Keyword(s):  
Semantic Web ◽  
Natural Resources ◽  
Traditional Medicine ◽  
Content Knowledge ◽  
Semantic Web Rule Language

One of the natural resources in Indonesia is a lot of plants which can be used in healing diseases. Thosekinds of plants can be used in “Jamu”. Jamu is a name given to traditional medicine in Indonesia. Usually Jamu is composed from several plants as ingredients. Particularly, some parts of the plant like the leaves, roots, or branches have different purpose in Jamu. Nowadays the knowledge about Jamu can be known by building Ontology. Ontology can be built and developed to enrich the content. Knowledge in Ontology is built by several rules using Semantic Web Rule Language (SWRL).Knowledge gained from SWRL is easily searchable so that users can double check the results obtained.

A visual modeling approach for the Semantic Web Rule Language

Semantic Web ◽  
2020 ◽  
Vol 11 (2) ◽  
pp. 361-389 ◽  
Author(s):  
Benedikt Pittl ◽  
Hans-Georg Fill
Keyword(s):  
Semantic Web ◽  
Visual Modeling ◽  
Modeling Approach ◽  
Semantic Web Rule Language

Using the Semantic Web Rule Language in the Development of Ontology-Driven Applications

2010 ◽  
pp. 525-539 ◽  
Author(s):  
Martin O’Connor ◽  
Mark Musen ◽  
Amar Das
Keyword(s):  
Semantic Web ◽  
Description Logic ◽  
Deductive Reasoning ◽  
Description Logics ◽  
Open World ◽  
Closed World ◽  
Amount Of Knowledge ◽  
Open World Assumption ◽  
Formal Characteristic ◽  
Semantic Web Rule Language

The Semantic Web Rule Language (SWRL) is an expressive OWL-based rule language. SWRL allows users to write Horn-like rules that can be expressed in terms of OWL concepts to provide more powerful deductive reasoning capabilities than OWL alone. Semantically, SWRL is built on the same description logic foundation as OWL and provides similar strong formal guarantees when performing inference. Due to its description logics foundation, rule-based applications developed using SWRL have a number of relatively novel characteristics. For example, SWRL shares OWL’s open world assumption so certain types of rules that assume a closed world may be difficult or impossible to write in SWRL. In addition, all inference in SWRL is monotonic so deductions cannot be updated or retracted. These formal characteristic have a strong influence on the development and use of SWRL rules in ontology-driven applications. In this chapter, we describe the primary features of SWRL and outline how, despite some limitations, SWRL can be used to dramatically increase amount of knowledge that be represented in OWL ontologies.

scholarly journals The role of ontological engineering for AIED research

2005 ◽  
Vol 2 (1) ◽  
pp. 31-42 ◽  
Author(s):  
Riichiro Mizoguchi
Keyword(s):  
Artificial Intelligence ◽  
Semantic Web ◽  
Knowledge Sharing ◽  
Semantic Integration ◽  
Ontological Engineering ◽  
Artificial Intelligence In Education ◽  
Domain I ◽  
Made In

Ontology has been collecting a lot of attention recently. In fact, it has potential for resolving several key problems such as semantic tag design for semantic web, semantic integration, knowledge sharing/reuse, etc. However, it is also true that people have different understanding of ontology. This article is written to contribute to clarification of the understanding of ontology and ontological engineering and to promotion of its utility. Although the discussion is made in the context of Artificial Intelligence in Education domain, I believe the content is pretty general.

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