---
title: "Predicting Knowledge in an Ontology Stream"
authors:
  - "Freddy Lécué"
  - "Jeff Z. Pan"
doi: ""
url: "https://ijcai.org/proceedings/2013/392"
pdf: "https://ijcai.org/proceedings/2013/0392.pdf"
venue: "Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence"
year: 2013
pages: "2662-2668"
track: ""
keywords:
---

# Predicting Knowledge in an Ontology Stream

Freddy Lécué, Jeff Z. Pan

*Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence*, pages 2662-2668.

## Abstract

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 semantics-augmented 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.