2012Unpublished venueRequires access

Semantic Web Service Similarity Ranking Proposal Based on Semantic Space Vector Model

Zhihao Zeng, Jiping Hu, Ting Dong, Yu Wang

Open publisher page 5 citations

Abstract

With the Semantic Web services technology research work continued to deepen, the number of semantic Web services on the Internet has dramatically increased how to locate available semantic Web services quickly and easily has become an urgent and key issue. Among semantic Web service matchmaking technology study, one of the important research themes is the semantic Web service matchmaking result ranking mechanism. In this paper, a novel semantic Web service ranking mechanism based on semantic space vector model is proposed. The calculation of semantic similarity measure can be realized by using this three dimensional semantic space vector model, therefore, the semantic Web Service matchmaking results can be ranked in accordance with the semantic similarity measure. The approach based on semantic space vector model will significantly improve search accuracy of semantic Web service matchmaking, and achieve high performance of the user experience of semantic Web services search.

About this research paper

What this paper is about

With the Semantic Web services technology research work continued to deepen, the number of semantic Web services on the Internet has dramatically increased how to locate available semantic Web services quickly and easily has become an urgent and key issue. Among semantic Web service matchmaking technology study, one of the important research themes is the semantic Web service matchmaking result ranking mechanism. In this paper, a novel semantic Web service ranking mechanism based on semantic space vector model is proposed. The calculation of semantic similarity measure can be realized by using this three dimensional semantic space vector model, therefore, the semantic Web Service matchmaking results can be ranked in accordance with the semantic similarity measure. The approach based on semantic space vector model will significantly improve search accuracy of semantic Web service matchmaking, and achieve high performance of the user experience of semantic Web services search.

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OpenAlex reports 5 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

With the Semantic Web services technology research work continued to deepen, the number of semantic Web services on the Internet has dramatically increased how to locate available semantic Web services quickly and easily has become an urgent and key issue. Among semantic Web service matchmaking technology study, one of the important research themes is the semantic Web service matchmaking result ranking mechanism. In this paper, a novel semantic Web service ranking mechanism based on semantic space vector model is proposed. The calculation of semantic similarity measure can be realized by using this three dimensional semantic space vector model, therefore, the semantic Web Service matchmaking results can be ranked in accordance with the semantic similarity measure. The approach based on semantic space vector model will significantly improve search accuracy of semantic Web service matchmaking, and achieve high performance of the user experience of semantic Web services search.

Key concepts: Social Semantic Web, Semantic Web Stack, Computer science, Semantic grid, Semantic similarity, Information retrieval, Semantic computing, Semantic analytics

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