Authors:
Antonio De Nicola
1
;
Anna Formica
2
;
Michele Missikoff
2
;
Elaheh Pourabbas
2
and
Francesco Taglino
2
Affiliations:
1
Italian National Agency for New Technologies, Energy and Sustainable Economic Development (ENEA), Casaccia Research Centre, Via Anguillarese 301, I-00123, Rome and Italy
;
2
Istituto di Analisi dei Sistemi ed Informatica (IASI) “Antonio Ruberti”, National Research Council, Via dei Taurini 19, I-00185, Rome and Italy
Keyword(s):
Weighted Reference Ontology, Semantic Similarity, Information Content, Probabilistic Approach.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
e-Business
;
Enterprise Engineering
;
Enterprise Information Systems
;
Enterprise Ontologies
;
Formal Methods
;
Knowledge Representation and Reasoning
;
Ontologies
;
Simulation and Modeling
;
Symbolic Systems
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.