[Objective] As the number of available cloud services increases exponentially, the problem of cloud service discovery and selection arises. [Methods] Semantic retrieval technology in use of information retrieval, semantic analysis and information fusion can improve retrieval efficiency. Combined with Ontology technology can ensure search processes accuracy and consistency, and realize cloud service discovery and selection. [Results] This paper can semantically represent and semantically annotate cloud services. According to extracting semantically annotate terms, it applies vector value to create semantic indexing. Using semantic search engine calculate vector space value between query sentence and index data, and obtain documents similarity. [Limitations] Relevant algorithms involved in some semantic retrieval system are still in development. This paper researches semantic retrieval system as a whole, every module just applies these basic algorithms, algorithm improvement is not involved. [Conclusions] Empirical research proves Ontology technology applied in semantic retrieval system achieves good effects. Especially it is suitable for retrieval of unstructured information, when changes between Ontology and semantic need to keep consistency.
唐守利, 徐宝祥. 基于本体的云服务语义检索系统研究[J]. 现代图书情报技术, 2014, 30(12): 27-35.
Tang Shouli, Xu Baoxiang. Research on Ontology-based Cloud Services Semantic Retrieval System. New Technology of Library and Information Service, 2014, 30(12): 27-35.
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