Back to Search
Start Over
Graph Planning Based Composition For Adaptable Semantic Web Services
- Source :
- KES
- Publication Year :
- 2017
- Publisher :
- Elsevier BV, 2017.
-
Abstract
- This paper proposes a context-aware semantic planning graph technique for Web services composition. We first use an ontology based context model for extending Web services descriptions with information about the most suitable context for its use. Then, we transform the composition problem into a semantic context aware graph planning problem to build a set of best composed Web services based on user’s context. The construction of the planning graph is based on semantic context-aware Web service discovery. This allow, for each step of the construction, to add most suitable Web services in terms of semantic compatibility between the services parameters, and their context similarity with the user’s context. In the backward search step, semantic and contextual similarity scores are used to find composed Web services list. Finally, in the ranking step, a score is calculated for each candidate solution and a set of ranked solutions is returned to the user.
- Subjects :
- Web standards
medicine.medical_specialty
Web development
Computer science
computer.internet_protocol
02 engineering and technology
computer.software_genre
OWL-S
Social Semantic Web
World Wide Web
Semantic similarity
020204 information systems
Semantic computing
0202 electrical engineering, electronic engineering, information engineering
medicine
Semantic analytics
Semantic Web Stack
Semantic Web
Data Web
General Environmental Science
WS-Addressing
Context model
business.industry
Semantic Web Rule Language
Semantic search
020207 software engineering
Semantic grid
Ontology
General Earth and Planetary Sciences
Web mapping
Web service
business
WS-Policy
Web intelligence
computer
Web modeling
Subjects
Details
- ISSN :
- 18770509
- Volume :
- 112
- Database :
- OpenAIRE
- Journal :
- Procedia Computer Science
- Accession number :
- edsair.doi...........a42f3682fa128570553856d94f0cd239
- Full Text :
- https://doi.org/10.1016/j.procs.2017.08.016