Mobile services discovery framework using DBpedia and non-monotonic rules. (May 2016)

• Record Type: Journal Article
• Authors: Cheniki, Nasredine; Belkhir, Abdelkader; Atif, Yacine
• Is Part Of: Computers & electrical engineering. Volume 52(2016)
• Page Start: 49
• Page End: 64
• Publication Date: 2016-05
• Subjects: Mobile services discovery -- Context information -- QoS information -- Semantic search -- Non-monotonic rules -- DBpedia -- Multi-domain ontologies; Computer engineering -- Periodicals; Electrical engineering -- Periodicals; Electrical engineering -- Data processing -- Periodicals; Ordinateurs -- Conception et construction -- Périodiques; Électrotechnique -- Périodiques; Électrotechnique -- Informatique -- Périodiques; Computer engineering; Electrical engineering; Electrical engineering -- Data processing; Periodicals; Electronic journals; 621.302854
• DOI: 10.1016/j.compeleceng.2016.02.016
• Languages: English
• ISSNs: 0045-7906

Abstract

Abstract: Mobile services are constantly evolving, thanks to improvements in performance of mobile devices and wireless networks. As a result, there is a need for and efficient supply of discovery processes that will even allow non-technical users and developers to publish, discover and access services in a mobile environment where non-functional properties (context and quality of service information) play an important role in the discovery process in conjunction to functional properties. In this paper, we propose a user-centric mobile services discovery framework that enriches functional descriptions of mobile services with semantic annotations from DBpedia knowledge (the semantically-structured version of Wikipedia) which covers multiple domains and provides lightweight ontologies. In addition, it offers open tools that can be used to simplify the provisioning and discovery of mobile services. The framework allows users to rank services using non-monotonic rules, which define their desired choices based on the context and quality of service information. Experimental results show that our framework provides efficient discovery results of efficient mobile services.