论文信息 - Ranking Semantic Similarity Association in Semantic Web

Ranking Semantic Similarity Association in Semantic Web

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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