Predicting knowledge in an ontology stream

Freddy Lécué, Jeff Z. Pan

Research output: Chapter in Book/Report/Conference proceedingPublished conference contribution

28 Citations (Scopus)


Recently, ontology stream reasoning has been introduced as a multidisciplinary approach, merging synergies from Artificial Intelligence, Database, World-Wide-Web to reason on semantic augmented data streams. Although knowledge evolution and real-time reasoning have been largely addressed in ontology streams, the challenge of predicting its future (or missing) knowledge remains open and yet unexplored. We tackle predictive reasoning as a correlation and interpretation of past semanticsaugmented data over exogenous ontology streams. Consistent predictions are constructed as Description Logics entailments by selecting and applying relevant cross-streams association rules. The experiments have shown accurate prediction with real and live stream data from Dublin City in Ireland.

Original languageEnglish
Title of host publicationProceedings of the 23rd International Joint Conference on Artificial Intelligence (IJCAI 2013)
EditorsFrancesca Rossi
PublisherAAAI Press
Number of pages8
ISBN (Print)9781577356332
Publication statusPublished - 2013
Event23rd International Joint Conference on Artificial Intelligence, IJCAI 2013 - Beijing, China
Duration: 3 Aug 20139 Aug 2013


Conference23rd International Joint Conference on Artificial Intelligence, IJCAI 2013

Bibliographical note

The research leading to these results has received funding from the European Unions Seventh Framework Programme (FP7/2007-2013) under grant agreement IDs 318201 (SIMPLI-CITY) and 286348 (K-Drive).


  • semantic web
  • ontology
  • stream
  • description logics
  • predictive reasoning
  • prediction


Dive into the research topics of 'Predicting knowledge in an ontology stream'. Together they form a unique fingerprint.

Cite this