Machine Learning and Constraint Programming for Relational-to-Ontology schema mapping

Diego De Uña, Nataliia Rümmele, Graeme Gange, Peter Schachte, Peter J. Stuckey

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

3 Citations (Scopus)

Abstract

The problem of integrating heterogeneous data sources into an ontology is highly relevant in the database field. Several techniques exist to approach the problem, but side constraints on the data cannot be easily implemented and thus the results may be inconsistent. In this paper we improve previous work by Taheriyan et al. [2016a] using Machine Learning (ML) to take into account inconsistencies in the data (unmatchable attributes) and encode the problem as a variation of the Steiner Tree, for which we use work by De Uña et al. [2016] in Constraint Programming (CP). Combining ML and CP achieves state-of-the-art precision, recall and speed, and provides a more flexible framework for variations of the problem.

Original languageEnglish
Title of host publicationProceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018
EditorsJerome Lang
Place of PublicationMarina del Rey CA USA
PublisherAssociation for the Advancement of Artificial Intelligence (AAAI)
Pages1277-1283
Number of pages7
ISBN (Electronic)9780999241127
Publication statusPublished - 2018
Externally publishedYes
EventInternational Joint Conference on Artificial Intelligence 2018 - Stockholm, Sweden
Duration: 13 Jul 201819 Jul 2018
https://www.ijcai.org/proceedings/2018/

Conference

ConferenceInternational Joint Conference on Artificial Intelligence 2018
Abbreviated titleIJCAI 2018
CountrySweden
CityStockholm
Period13/07/1819/07/18
Internet address

Keywords

  • Constraints and SAT
  • Modeling
  • Formulation
  • Knowledge Representation and Reasoning
  • Information Fusion
  • Multidisciplinary Topics and Applications
  • Intelligent Database Systems
  • Constraints and Data Mining
  • Machine Learning

Cite this

De Uña, D., Rümmele, N., Gange, G., Schachte, P., & Stuckey, P. J. (2018). Machine Learning and Constraint Programming for Relational-to-Ontology schema mapping. In J. Lang (Ed.), Proceedings of the 27th International Joint Conference on Artificial Intelligence, IJCAI 2018 (pp. 1277-1283). Association for the Advancement of Artificial Intelligence (AAAI). https://doi.org/10.24963/ijcai.2018/178