2008International Semantic Web ConferenceRequires access

Ranking semantic similarity association in semantic web

Shahdad Shariatmadari, Ali Mamat, Hamidah Ibrahim, Aida Mustapha

Open publisher page 3 citations

Abstract

Discovering and ranking complex relationships in the semantic web is an important building block of semantic search applications. Although semantic web technologies define relations between objects but there are some complex (hidden) relationships that are valuable in different applications. Currently, users need to discover the relations between objects and find the level of semantic similarity between them. (I.e. find two similar papers). This paper presents a new approach for ranking semantic similarity association in semantic web document, based on semantic association concept.

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What this paper is about

Discovering and ranking complex relationships in the semantic web is an important building block of semantic search applications. Although semantic web technologies define relations between objects but there are some complex (hidden) relationships that are valuable in different applications. Currently, users need to discover the relations between objects and find the level of semantic similarity between them. (I.e. find two similar papers). This paper presents a new approach for ranking semantic similarity association in semantic web document, based on semantic association concept.

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OpenAlex reports 3 citations for this work. Citation counts describe recorded attention and do not establish research quality.

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Available abstract

Discovering and ranking complex relationships in the semantic web is an important building block of semantic search applications. Although semantic web technologies define relations between objects but there are some complex (hidden) relationships that are valuable in different applications. Currently, users need to discover the relations between objects and find the level of semantic similarity between them. (I.e. find two similar papers). This paper presents a new approach for ranking semantic similarity association in semantic web document, based on semantic association concept.

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

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