A Comparative Assessment Of Ontologyweighting Methods In Semantic Similarity Search

PROCEEDINGS OF THE 11TH INTERNATIONAL CONFERENCE ON AGENTS AND ARTIFICIAL INTELLIGENCE (ICAART), VOL 2(2019)

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摘要
Semantic search is the new frontier for the search engines of the last generation. Advanced semantic search methods are exploring the use of weighted ontologies, i.e., domain ontologies where concepts are associated with weights, inversely related to their selective power. In this paper, we present and assess four different ontology weighting methods, organized according to two groups: intensional methods, based on the sole ontology structure, and extensional methods, where also the content of the search space is considered. The comparative assessment is carried out by embedding the different methods within the semantic search engine SemSim, based on weighted ontologies, and then by running four retrieval tests over a search space we have previously proposed in the literature. In order to reach a broad audience of readers, the key concepts of this paper have been presented by using a simple taxonomy, and the already experimented dataset.
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关键词
Weighted Reference Ontology, Semantic Similarity, Information Content, Probabilistic Approach
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