Predicting Knowledge in an Ontology Stream

Freddy Lécué, Jeff Z. Pan

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 languageEnglish
Title of host publicationProceedings of the Twenty-Third International Joint Conference on Artificial Intelligence
EditorsFrancesca Rossi
PublisherAAAI Press
Pages2662–2669
Number of pages8
ISBN (Print)9781577356332
Publication statusPublished - 3 Aug 2013
EventTwenty-Third International Joint Conference on Artificial Intelligence - Beijing, China
Duration: 3 Aug 20139 Aug 2013
Conference number: 23
https://ijcai13.org/

Publication series

NameIJCAI '13
PublisherAAAI Press

Conference

ConferenceTwenty-Third International Joint Conference on Artificial Intelligence
Abbreviated titleIJCAI 2013
Country/TerritoryChina
CityBeijing
Period3/08/139/08/13
Internet address

Fingerprint

Dive into the research topics of 'Predicting Knowledge in an Ontology Stream'. Together they form a unique fingerprint.

Cite this