6533b825fe1ef96bd1281e5c
RESEARCH PRODUCT
An Ontology Design Methodology for Knowledge-Based Systems with Application to Bioinformatics
A. FiannacaM. La RosaRiccardo RizzoAlfonso UrsoSalvatore Gagliosubject
Settore ING-INF/05 - Sistemi Di Elaborazione Delle InformazioniKnowledge representation and reasoningComputer sciencebusiness.industryKnowledge organizationOpen Knowledge Base ConnectivityOntology (information science)BioinformaticsArtificial intelligence; Expert systems; Knowledge representation; Ontology; ProteinsKnowledge-based systemsKnowledge extractionKnowledge baseArtificial IntelligenceDomain knowledgebusinessdescription
Ontologies are formal knowledge representation models. Knowledge organization is a fundamental requirement in order to develop Knowledge-Based systems. In this paper we present Data-Problem-Solver (DPS) approach, a new ontological paradigm that allows the knowledge designer to model and represent a Knowledge Base (KB) for expert systems. Our approach clearly distinguishes among the knowledge about a problem to resolve (answering the what to do question), the solver method to resolve it (answering the how to do question) and the type of input data required (answering the what I need question). The main purpose of the proposed paradigm is to facilitate the generalization of the application domain and the modularity and the expandability of the represented knowledge. The proposed DPS ontological approach is applied to the modelling of the knowledge about a bioinformatics application scenario: the protein complex extraction from a protein-protein interaction network. © 2012 IEEE.
| year | journal | country | edition | language |
|---|---|---|---|---|
| 2012-05-01 |