Summarizing Vocabularies in the Global Semantic Web  

作　　者：张祥 程龚 葛唯益 瞿裕忠 

机构地区：[1]School of Computer Science and Engineering,Southeast University

出　　处：《Journal of Computer Science & Technology》2009年第1期165-174,共10页计算机科学技术学报（英文版）

基　　金：supported in part by the National Basic Research 973 Program of China under Grant No.2003CB317004;the National Natural Science Foundation of China under Grant No.60773106.

摘　　要：In the Semantic Web, vocabularies are defined and shared among knowledge workers to describe linked data for scientific, industrial or daily life usage. With the rapid growth of online vocabularies, there is an emergent need for approaches helping users understand vocabularies quickly. In this paper, we study the summarization of vocabularies to help users understand vocabularies. Vocabulary summarization is based on the structural analysis and pragmatics statistics in the global Semantic Web. Local Bipartite Model and Expanded Bipartite Model of a vocabulary are proposed to characterize the structure in a vocabulary and links between vocabularies. A structural importance for each RDF sentence in the vocabulary is assessed using link analysis. Meanwhile, pragmatics importance of each RDF sentence is assessed using the statistics of instantiation of its terms in the Semantic Web. Summaries are produced by extracting important RDF sentences in vocabularies under a re-ranking strategy. Preliminary experiments show that it is feasible to help users understand a vocabulary through its summary.In the Semantic Web, vocabularies are defined and shared among knowledge workers to describe linked data for scientific, industrial or daily life usage. With the rapid growth of online vocabularies, there is an emergent need for approaches helping users understand vocabularies quickly. In this paper, we study the summarization of vocabularies to help users understand vocabularies. Vocabulary summarization is based on the structural analysis and pragmatics statistics in the global Semantic Web. Local Bipartite Model and Expanded Bipartite Model of a vocabulary are proposed to characterize the structure in a vocabulary and links between vocabularies. A structural importance for each RDF sentence in the vocabulary is assessed using link analysis. Meanwhile, pragmatics importance of each RDF sentence is assessed using the statistics of instantiation of its terms in the Semantic Web. Summaries are produced by extracting important RDF sentences in vocabularies under a re-ranking strategy. Preliminary experiments show that it is feasible to help users understand a vocabulary through its summary.

关 键 词：Semantic Web vocabulary summarization RDF PRAGMATICS 

分 类 号：TP393.092[自动化与计算机技术—计算机应用技术]