ALEX: Automatic link exploration in linked data

Ahmed El-Roby, Ashraf Aboulnaga

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

There has recently been an increase in the number of RDF knowledge bases published on the Internet. These rich RDF data sets can be useful in answering many queries, but much more interesting queries can be answered by integrating information from different data sets. This has given rise to research on automatically linking different RDF data sets representing different knowledge bases. This is challenging due to their scale and semantic heterogeneity. Various approaches have been proposed, but there is room for improving the quality of the generated links. In this paper, we present ALEX, a system that aims at improving the quality of links between RDF data sets by using feedback provided by users on the answers to linked data queries. ALEX starts with a set of candidate links obtained using any automatic linking algorithm. ALEX utilizes user feedback to discover new links that did not exist in the set of candidate links while preserving link precision. ALEX discovers these new links by finding links that are similar to a link approved by the user through feedback on queries. ALEX uses a Monte-Carlo reinforcement learning method to learn how to explore in the space of possible links around a given link. Our experiments on real-world data sets show that ALEX is efficient and significantly improves the quality of links.

Original languageEnglish
Title of host publicationProceedings of the ACM SIGMOD International Conference on Management of Data
PublisherAssociation for Computing Machinery
Pages1839-1853
Number of pages15
Volume2015-May
ISBN (Print)9781450327589
DOIs
Publication statusPublished - 27 May 2015
EventACM SIGMOD International Conference on Management of Data, SIGMOD 2015 - Melbourne, Australia
Duration: 31 May 20154 Jun 2015

Other

OtherACM SIGMOD International Conference on Management of Data, SIGMOD 2015
CountryAustralia
CityMelbourne
Period31/5/154/6/15

Fingerprint

Feedback
Reinforcement learning
Semantics
Internet
Experiments

Keywords

  • Automatic linking
  • Federated query processing
  • Knoweldge bases
  • Linked data
  • RDF
  • Reinforcement learning

ASJC Scopus subject areas

  • Software
  • Information Systems

Cite this

El-Roby, A., & Aboulnaga, A. (2015). ALEX: Automatic link exploration in linked data. In Proceedings of the ACM SIGMOD International Conference on Management of Data (Vol. 2015-May, pp. 1839-1853). Association for Computing Machinery. https://doi.org/10.1145/2723372.2749428

ALEX : Automatic link exploration in linked data. / El-Roby, Ahmed; Aboulnaga, Ashraf.

Proceedings of the ACM SIGMOD International Conference on Management of Data. Vol. 2015-May Association for Computing Machinery, 2015. p. 1839-1853.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

El-Roby, A & Aboulnaga, A 2015, ALEX: Automatic link exploration in linked data. in Proceedings of the ACM SIGMOD International Conference on Management of Data. vol. 2015-May, Association for Computing Machinery, pp. 1839-1853, ACM SIGMOD International Conference on Management of Data, SIGMOD 2015, Melbourne, Australia, 31/5/15. https://doi.org/10.1145/2723372.2749428
El-Roby A, Aboulnaga A. ALEX: Automatic link exploration in linked data. In Proceedings of the ACM SIGMOD International Conference on Management of Data. Vol. 2015-May. Association for Computing Machinery. 2015. p. 1839-1853 https://doi.org/10.1145/2723372.2749428
El-Roby, Ahmed ; Aboulnaga, Ashraf. / ALEX : Automatic link exploration in linked data. Proceedings of the ACM SIGMOD International Conference on Management of Data. Vol. 2015-May Association for Computing Machinery, 2015. pp. 1839-1853
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