Predicting Knowledge in an Ontology Stream
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.
@inproceedings{ijcai2013p392,
title = {Predicting Knowledge in an Ontology Stream},
author = {Lecue, Freddy and Pan, Jeff Z.},
booktitle = {Proceedings of the Twenty-Third International Joint Conference on
Artificial Intelligence, {IJCAI-13}},
publisher = {AAAI Press / International Joint Conferences on Artificial Intelligence},
editor = {Francesca Rossi},
pages = {2662--2668},
year = {2013},
month = {8},
url = {https://ijcai.org/proceedings/2013/392},
}
TY - CPAPER TI - Predicting Knowledge in an Ontology Stream AU - Lecue, Freddy AU - Pan, Jeff Z. T2 - Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence, IJCAI-13 PB - AAAI Press / International Joint Conferences on Artificial Intelligence PY - 2013 SP - 2662 EP - 2668 UR - https://ijcai.org/proceedings/2013/392 ER -Copied
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