scholarly journals Ontologies and Semantic Web Technologies to Support Knowledge-Based Transformation and Decision Support

2007 ◽  
Vol 22 ◽  
pp. 49-63
Author(s):  
Tobias Lehmann ◽  
Andreas Karcher
Keyword(s):  
Decision Support ◽  
Semantic Web ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowledge Based

Mini-ME Matchmaker and Reasoner for the Semantic Web of Things

2018 ◽  
pp. 262-294 ◽  
Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Decision Support ◽  
Semantic Web ◽  
Knowledge Bases ◽  
Semantic Web Technologies ◽  
Experimental Performance ◽  
Web Of Things ◽  
Web Technologies ◽  
Constrained Environments ◽  
And Performance

The Semantic Web of Things (SWoT) aims to support smart semantics-enabled applications and services in pervasive contexts. Due to architectural and performance issues, most Semantic Web reasoners are often impractical to be ported: they are resource consuming and are basically designed for standard inference tasks on large ontologies. On the contrary, SWoT use cases generally require quick decision support through semantic matchmaking in resource-constrained environments. This paper describes Mini-ME (the Mini Matchmaking Engine), a mobile inference engine designed from the ground up for the SWoT. It supports Semantic Web technologies and implements both standard (subsumption, satisfiability, classification) and non-standard (abduction, contraction, covering, bonus, difference) inference services for moderately expressive knowledge bases. In addition to an architectural and functional description, usage scenarios and experimental performance evaluation are presented on PC (against other popular Semantic Web reasoners), smartphone and embedded single-board computer testbeds.

scholarly journals A Mobile Matchmaker for the Ubiquitous Semantic Web

2016 ◽  
pp. 994-1017 ◽  
Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Decision Support ◽  
Internet Of Things ◽  
Semantic Web ◽  
Knowledge Bases ◽  
Semantic Web Technologies ◽  
Experimental Performance ◽  
Web Technologies ◽  
Constrained Environments ◽  
And Performance

The Semantic Web and Internet of Things visions are converging toward the so-called Semantic Web of Things (SWoT). It aims to enable smart semantic-enabled applications and services in ubiquitous contexts. Due to architectural and performance issues, it is currently impractical to use existing Semantic Web reasoners. They are resource consuming and are basically optimized for standard inference tasks on large ontologies. On the contrary, SWoT use cases generally require quick decision support through semantic matchmaking in resource-constrained environments. This paper presents Mini-ME, a novel mobile inference engine designed from the ground up for the SWoT. It supports Semantic Web technologies and implements both standard (subsumption, satisfiability, classification) and non-standard (abduction, contraction, covering) inference services for moderately expressive knowledge bases. In addition to an architectural and functional description, usage scenarios are presented and an experimental performance evaluation is provided both on a PC testbed (against other popular Semantic Web reasoners) and on a smartphone.

Data Integration in the Geospatial Semantic Web

2011 ◽  
pp. 272-293
Author(s):  
Patrick Maué ◽  
Sven Schade
Keyword(s):  
Decision Support ◽  
Semantic Web ◽  
Real World ◽  
Relevant Information ◽  
Decision Makers ◽  
Semantic Web Technologies ◽  
Domain Experts ◽  
Web Technologies ◽  
Opening Up ◽  
The Web

Geospatial decision makers have to be aware of the varying interests of all stakeholders. One crucial task in the process is to identify relevant information available from the Web. In this chapter the authors introduce an application in the quarrying domain which integrates Semantic Web technologies to provide new ways to discover and reason about relevant information. The authors discuss the daily struggle of the domain experts to create decision-support maps helping to find suitable locations for opening up new quarries. After explaining how semantics can help these experts, they introduce the various components and the architecture of the software which has been developed in the European funded SWING project. In the last section, the different use cases illustrate how the implemented tools have been applied to real world scenarios.

Applying Semantic Web in Competence Management

2011 ◽  
pp. 1084-1104
Author(s):  
Mikko Maukkanen ◽  
Heikki Helin
Keyword(s):  
Semantic Web ◽  
Dynamic Environments ◽  
Management Systems ◽  
Flexible Systems ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowledge Based ◽  
Building Systems ◽  
Competence Management ◽  
Employee Competencies

Efficient competence management is essential in knowledge-based companies. This chapter describes how the Semantic Web technologies can be used in managing employee competencies. Applying the Semantic Web technologies in the competence management enables building systems that support highly dynamic environments, are extensible as well as interoperable between different application domains, and benefit from the use of machine-accessible semantics. Competence management systems should be available not only for managers, but for all the employees of the company. As companies get larger, it becomes increasingly difficult to manage the knowledge and competencies that their employees have. Utilizing the Semantic Web opens many possibilities for building flexible systems for competence management.

Applying Semantic Web in Competence Management

2007 ◽  
pp. 333-257
Author(s):  
Mikko Maukkanen ◽  
Heikki Helin
Keyword(s):  
Semantic Web ◽  
Dynamic Environments ◽  
Management Systems ◽  
Flexible Systems ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowledge Based ◽  
Building Systems ◽  
Competence Management ◽  
Employee Competencies

Efficient competence management is essential in knowledge-based companies. This chapter describes how the Semantic Web technologies can be used in managing employee competencies. Applying the Semantic Web technologies in the competence management enables building systems that support highly dynamic environments, are extensible as well as interoperable between different application domains, and benefit from the use of machine-accessible semantics. Competence management systems should be available not only for managers, but for all the employees of the company. As companies get larger, it becomes increasingly difficult to manage the knowledge and competencies that their employees have. Utilizing the Semantic Web opens many possibilities for building flexible systems for competence management.

SPARSE: A symptom-based antipattern retrieval knowledge-based system using Semantic Web technologies

2011 ◽  
Vol 38 (6) ◽  
pp. 7633-7646 ◽  
Author(s):  
Dimitrios L. Settas ◽  
Georgios Meditskos ◽  
Ioannis G. Stamelos ◽  
Nick Bassiliades
Keyword(s):  
Semantic Web ◽  
Semantic Web Technologies ◽  
Web Technologies ◽  
Knowledge Based System ◽  
Knowledge Based

scholarly journals A Mobile Matchmaker for the Ubiquitous Semantic Web

2014 ◽  
Vol 10 (4) ◽  
pp. 77-100 ◽  
Author(s):  
Floriano Scioscia ◽  
Michele Ruta ◽  
Giuseppe Loseto ◽  
Filippo Gramegna ◽  
Saverio Ieva ◽  
...  
Keyword(s):  
Performance Evaluation ◽  
Decision Support ◽  
Internet Of Things ◽  
Semantic Web ◽  
Knowledge Bases ◽  
Semantic Web Technologies ◽  
Experimental Performance ◽  
Web Technologies ◽  
Constrained Environments ◽  
And Performance

The Semantic Web and Internet of Things visions are converging toward the so-called Semantic Web of Things (SWoT). It aims to enable smart semantic-enabled applications and services in ubiquitous contexts. Due to architectural and performance issues, it is currently impractical to use existing Semantic Web reasoners. They are resource consuming and are basically optimized for standard inference tasks on large ontologies. On the contrary, SWoT use cases generally require quick decision support through semantic matchmaking in resource-constrained environments. This paper presents Mini-ME, a novel mobile inference engine designed from the ground up for the SWoT. It supports Semantic Web technologies and implements both standard (subsumption, satisfiability, classification) and non-standard (abduction, contraction, covering) inference services for moderately expressive knowledge bases. In addition to an architectural and functional description, usage scenarios are presented and an experimental performance evaluation is provided both on a PC testbed (against other popular Semantic Web reasoners) and on a smartphone.

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