loading
Papers Papers/2022 Papers Papers/2022

Research.Publish.Connect.

Paper

Paper Unlock

Authors: Anna Formica 1 ; Michele Missikoff 2 ; Elaheh Pourabbas 1 and Francesco Taglino 1

Affiliations: 1 National Research Council and Istituto di Analisi dei Sistemi ed Informatica ”Antonio Ruberti”, Italy ; 2 National Research Council and Istituto di Scienze e Tecnologie della Cognizione, Italy

Keyword(s): Semantic Search, Similarity Reasoning, Weighted Reference Ontology, Bayesian Network.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Knowledge Engineering and Ontology Development ; Knowledge Representation ; Knowledge-Based Systems ; Symbolic Systems

Abstract: Semantic similarity search is one of the most promising methods for improving the performance of retrieval systems. This paper presents a new probabilistic method for ontology weighting based on a Bayesian approach. In particular, this work addresses the semantic search method SemSim for evaluating the similarity among a user request and semantically annotated sources. Each resource is annotated with a vector of features (annotation vector), i.e., a set of concepts defined in a reference ontology. Analogously, a user request is represented by a collection of desired features. The paper shows, on the bases of a comparative study, that the adoption of the Bayesian weighting method improves the performance of the SemSim method.

CC BY-NC-ND 4.0

Sign In Guest: Register as new SciTePress user now for free.

Sign In SciTePress user: please login.

PDF ImageMy Papers

You are not signed in, therefore limits apply to your IP address 44.220.255.141

In the current month:
Recent papers: 100 available of 100 total
2+ years older papers: 200 available of 200 total

Paper citation in several formats:
Formica, A.; Missikoff, M.; Pourabbas, E. and Taglino, F. (2016). A Bayesian Approach for Weighted Ontologies and Semantic Search. In Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KEOD; ISBN 978-989-758-203-5; ISSN 2184-3228, SciTePress, pages 171-178. DOI: 10.5220/0006073301710178

@conference{keod16,
author={Anna Formica. and Michele Missikoff. and Elaheh Pourabbas. and Francesco Taglino.},
title={A Bayesian Approach for Weighted Ontologies and Semantic Search},
booktitle={Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KEOD},
year={2016},
pages={171-178},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006073301710178},
isbn={978-989-758-203-5},
issn={2184-3228},
}

TY - CONF

JO - Proceedings of the 8th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management (IC3K 2016) - KEOD
TI - A Bayesian Approach for Weighted Ontologies and Semantic Search
SN - 978-989-758-203-5
IS - 2184-3228
AU - Formica, A.
AU - Missikoff, M.
AU - Pourabbas, E.
AU - Taglino, F.
PY - 2016
SP - 171
EP - 178
DO - 10.5220/0006073301710178
PB - SciTePress