Scalable Maintenance of Knowledge Discovery in an Ontology Stream
Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence. Main Track. Pages 1457-1462.
Abstract
In dynamic settings where data is exposed by streams, knowledge discovery aims at learning associations of data across streams. In the semantic Web, streams expose their meaning through evolutive versions of ontologies. Such settings pose challenges of scalability for discovering (a posteriori) knowledge. In our work, the semantics, identifying knowledge similarity and rarity in streams, together with incremental, approximate maintenance, control scalability while preserving accuracy of streams associations (as semantic rules) discovery.
@inproceedings{ijcai2015p209,
title = {Scalable Maintenance of Knowledge Discovery in an Ontology Stream},
author = {Lecue, Freddy},
booktitle = {Proceedings of the Twenty-Fourth International Joint Conference on
Artificial Intelligence, {IJCAI-15}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Qiang Yang and Michael Wooldridge},
pages = {1457--1462},
year = {2015},
month = {7},
note = {Main Track},
url = {https://ijcai.org/proceedings/2015/209},
}
TY - CPAPER TI - Scalable Maintenance of Knowledge Discovery in an Ontology Stream AU - Lecue, Freddy T2 - Proceedings of the Twenty-Fourth International Joint Conference on Artificial Intelligence, IJCAI-15 PB - International Joint Conferences on Artificial Intelligence PY - 2015 SP - 1457 EP - 1462 UR - https://ijcai.org/proceedings/2015/209 ER -Copied
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