期刊名称：International Journal of Computer Science and Security (IJCSS)
电子版ISSN：1985-1553
出版年度：2019
卷号：13
期号：2
页码：36-52
出版社：Computer Science Journals
摘要：In spite of the rapid growth of cloud services, a wide spectrum of enterprises and users do not buy such services as a result of insufficient knowledge about cloud technology. On the other hand, the majority of cloud service discovery and repository frameworks depend on cloud ontologies as one of the main building blocks. Accordingly, constructing a suitable cloud service discovery mechanism will exclude an immense obstacle especially for non-expert users due to the difficulty to select suitable concepts from referenced cloud ontology. Users always prefer to compose queries using their natural languages. But, it is difficult to truly match such queries because of natural language ambiguities. In this paper, we propose a new mechanism bridging the gap between English natural language terms and concepts of the referenced cloud ontology using BabelNet knowledge base and FP-Growth mining algorithm. The contribution of this paper is two folded: firstly, classifying cloud services into their corresponding cloud ontology concepts; secondly, anticipating a system that enables non-specialized users to flexibly compose their cloud service searching queries using English natural language. We have applied the proposed mechanism on two sets of cloud services related to concepts in the referenced cloud ontology; Streaming and Multimedia (S&M), and Human Resource (HR). According to our experimental results, the proposed mechanism has achieved 90%, and 86% in the F-Score measure for classifying S&M, and HR cloud services, respectively. For matching users' queries, the results have shown that 80% of S&M and 82% of HR relevant queries have been assigned correctly.
关键词：Cloud Ontology; Query Composition; Semantic Search; Word Sense Disambiguation; Cloud Service Discover.
