Paper Info
Title
Investigating a Method for Automatic Construction and Population of Ontologies for Services: Performances and Limitations
Abstract
Ontological engineering is a complex process, involving multidisciplinary skills. The Semantic Web, and more specifically Semantic Web Services spreading suffer from the difficulty of producing an ontology sufficiently detailed to be able to correctly describe the data flows exchanged between services. These data are often described using sector-specific vocabulary. Linking these descriptions to external knowledge sources capable of unifying them is often a complex process, requiring adequate sources to be found and properly used. In this paper, we investigate a method combining existing string distance measurement, NLP-analysis and clustering algorithms for automatic construction and population of an ontology. This method takes services capacities descriptions as only input, without external sources of knowledge. It is tested on a set of more than 10,000 services for 106,000 different measures to classify in an ontology, performances and limitations are exposed.
Year
DOI
Venue
2018
10.1109/AICCSA.2018.8612844
2018 IEEE/ACS 15th International Conference on Computer Systems and Applications (AICCSA)
Keywords
Field
DocType
Ontology,ontology population,unsupervised learning,syntactic matching,semantic Web services
Ontology (information science),Population,Ontology,Information retrieval,Computer science,Semantic Web,Computer network,Unsupervised learning,Web service,Cluster analysis,Vocabulary
Conference
ISSN
ISBN
Citations 
2161-5322
978-1-5386-9121-2
0
PageRank 
References 
Authors
0.34
12
3
Name
Order
Citations
PageRank
Thierry Louge162.92
Mohamed Hedi Karray2248.55
B. Archimède3126.81