2010/03/12 by Francesca A. Lisi, Lisi, Francesca A. · 1 citation
Computer Science · #Artificial Intelligence (cs.AI) #Data Management and Algorithms #Databases (cs.DB) #FOS: Computer and information sciences #Logic in Computer Science (cs.LO) #Logic, Reasoning, and Knowledge #Machine Learning (cs.LG) #Semantic Web and Ontologies #cs.AI #cs.DB #cs.LG #cs.LO
paper · pdf · doi:10.48550/arxiv.1003.2586
30 pages, 3 figures, 2 tables.
arxiv created 2010/03/12 · openalex publication_date 2010/03/12 · arxiv updated 2010/03/15 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In this paper we address an issue that has been brought to the attention of the database community with the advent of the Semantic Web, i.e. the issue of how ontologies (and semantics conveyed by them) can help solving typical database problems, through a better understanding of KR aspects related to databases. In particular, we investigate this issue from the ILP perspective by considering two database problems, (i) the definition of views and (ii) the definition of constraints, for a database whose schema is represented also by means of an ontology. Both can be reformulated as ILP problems and can benefit from the expressive and deductive power of the KR framework DL+log. We illustrate the application scenarios by means of examples. Keywords: Inductive Logic Programming, Relational Databases, Ontologies, Description Logics, Hybrid Knowledge Representation and Reasoning Systems. Note: To appear in Theory and Practice of Logic Programming (TPLP).