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.

A comparative assessment of ontology weighting methods in semantic similarity search

De Nicola, A.;
2019

Abstract

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.
978-989758350-6
Information Content, Probabilistic Approach, Semantic Similarity, Weighted Reference Ontology
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12079/54857
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