Modeling Incomplete Knowledge of Semantic Web Using Bayesian Networks
Interoperable ontologies already exist in the biomedical field, enabling scientists to communicate with minimum ambiguity. Unfortunately, ontology languages, in the semantic web, such as OWL and RDF(S), are based on crisp logic and thus they cannot handle uncertain knowledge about an application fie...
| Main Author: | |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2019-09-01
|
| Series: | Applied Artificial Intelligence |
| Online Access: | http://dx.doi.org/10.1080/08839514.2019.1661578 |
| _version_ | 1797684891663466496 |
|---|---|
| author | Messaouda Fareh |
| author_facet | Messaouda Fareh |
| author_sort | Messaouda Fareh |
| collection | DOAJ |
| description | Interoperable ontologies already exist in the biomedical field, enabling scientists to communicate with minimum ambiguity. Unfortunately, ontology languages, in the semantic web, such as OWL and RDF(S), are based on crisp logic and thus they cannot handle uncertain knowledge about an application field, which is unsuitable for the medical domain. In this paper, we focus on modeling incomplete knowledge in the classical OWL ontologies, using Bayesian networks, all keeping the semantic of the first ontology, and applying algorithms dedicated to learn parameters of Bayesian networks in order to generate the Bayesian networks. We use EM algorithm for learning conditional probability tables of different nodes of Bayesian network automatically, contrary to different tools of Bayesian networks where probabilities are inserted manually. To validate our work, we have applied our model on the diagnosis of liver cancer using classical ontology containing incomplete instances, in order to handle medical uncertain knowledge, for predicting a liver cancer. |
| first_indexed | 2024-03-12T00:36:18Z |
| format | Article |
| id | doaj.art-8fb7594faa9e43f98fc2a60fd9688fca |
| institution | Directory Open Access Journal |
| issn | 0883-9514 1087-6545 |
| language | English |
| last_indexed | 2024-03-12T00:36:18Z |
| publishDate | 2019-09-01 |
| publisher | Taylor & Francis Group |
| record_format | Article |
| series | Applied Artificial Intelligence |
| spelling | doaj.art-8fb7594faa9e43f98fc2a60fd9688fca2023-09-15T09:33:57ZengTaylor & Francis GroupApplied Artificial Intelligence0883-95141087-65452019-09-0133111022103410.1080/08839514.2019.16615781661578Modeling Incomplete Knowledge of Semantic Web Using Bayesian NetworksMessaouda Fareh0Department of Computer Science, Faculty of SciencesInteroperable ontologies already exist in the biomedical field, enabling scientists to communicate with minimum ambiguity. Unfortunately, ontology languages, in the semantic web, such as OWL and RDF(S), are based on crisp logic and thus they cannot handle uncertain knowledge about an application field, which is unsuitable for the medical domain. In this paper, we focus on modeling incomplete knowledge in the classical OWL ontologies, using Bayesian networks, all keeping the semantic of the first ontology, and applying algorithms dedicated to learn parameters of Bayesian networks in order to generate the Bayesian networks. We use EM algorithm for learning conditional probability tables of different nodes of Bayesian network automatically, contrary to different tools of Bayesian networks where probabilities are inserted manually. To validate our work, we have applied our model on the diagnosis of liver cancer using classical ontology containing incomplete instances, in order to handle medical uncertain knowledge, for predicting a liver cancer.http://dx.doi.org/10.1080/08839514.2019.1661578 |
| spellingShingle | Messaouda Fareh Modeling Incomplete Knowledge of Semantic Web Using Bayesian Networks Applied Artificial Intelligence |
| title | Modeling Incomplete Knowledge of Semantic Web Using Bayesian Networks |
| title_full | Modeling Incomplete Knowledge of Semantic Web Using Bayesian Networks |
| title_fullStr | Modeling Incomplete Knowledge of Semantic Web Using Bayesian Networks |
| title_full_unstemmed | Modeling Incomplete Knowledge of Semantic Web Using Bayesian Networks |
| title_short | Modeling Incomplete Knowledge of Semantic Web Using Bayesian Networks |
| title_sort | modeling incomplete knowledge of semantic web using bayesian networks |
| url | http://dx.doi.org/10.1080/08839514.2019.1661578 |
| work_keys_str_mv | AT messaoudafareh modelingincompleteknowledgeofsemanticwebusingbayesiannetworks |