Abstract / Description of output
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.
Original language | English |
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Title of host publication | Proceedings of the Twenty-Third International Joint Conference on Artificial Intelligence |
Editors | Francesca Rossi |
Publisher | AAAI Press |
Pages | 2662–2669 |
Number of pages | 8 |
ISBN (Print) | 9781577356332 |
Publication status | Published - 3 Aug 2013 |
Event | Twenty-Third International Joint Conference on Artificial Intelligence - Beijing, China Duration: 3 Aug 2013 → 9 Aug 2013 Conference number: 23 https://ijcai13.org/ |
Publication series
Name | IJCAI '13 |
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Publisher | AAAI Press |
Conference
Conference | Twenty-Third International Joint Conference on Artificial Intelligence |
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Abbreviated title | IJCAI 2013 |
Country/Territory | China |
City | Beijing |
Period | 3/08/13 → 9/08/13 |
Internet address |