2010Unpublished venueRequires access

Research on similarity of Semantic Web

Hongsheng Wang, Xiaoguang Han

Open publisher page 7 citations

Abstract

With the rapid increasing of information on Internet and the emergence of the Semantic Web technology, information retrieval based on the Semantic Web has become a researching focus. In the semantic retrieval, the calculating method of semantic similarity is very important to information recall and precision ratio, this paper presents a new calculating method of semantic similarity by improving the flaw of traditional calculating method. The method adopts a directed graph to establish the Semantic Web and calculating the similarity of semantic nodes and semantic relations, then combine them to form the unified semantic similarity values. The analysis of the semantic retrieval and the statistics of the results indicate that this method can get higher recall and precision ratio than traditional method.

About this research paper

What this paper is about

With the rapid increasing of information on Internet and the emergence of the Semantic Web technology, information retrieval based on the Semantic Web has become a researching focus. In the semantic retrieval, the calculating method of semantic similarity is very important to information recall and precision ratio, this paper presents a new calculating method of semantic similarity by improving the flaw of traditional calculating method. The method adopts a directed graph to establish the Semantic Web and calculating the similarity of semantic nodes and semantic relations, then combine them to form the unified semantic similarity values. The analysis of the semantic retrieval and the statistics of the results indicate that this method can get higher recall and precision ratio than traditional method.

Why it matters

OpenAlex reports 7 citations for this work. Citation counts describe recorded attention and do not establish research quality.

Key contribution

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Method / approach

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Available abstract

With the rapid increasing of information on Internet and the emergence of the Semantic Web technology, information retrieval based on the Semantic Web has become a researching focus. In the semantic retrieval, the calculating method of semantic similarity is very important to information recall and precision ratio, this paper presents a new calculating method of semantic similarity by improving the flaw of traditional calculating method. The method adopts a directed graph to establish the Semantic Web and calculating the similarity of semantic nodes and semantic relations, then combine them to form the unified semantic similarity values. The analysis of the semantic retrieval and the statistics of the results indicate that this method can get higher recall and precision ratio than traditional method.

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

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