Tadhg Fitzgerald, Yuri Malitsky, et al.
IJCAI 2015
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.
Tadhg Fitzgerald, Yuri Malitsky, et al.
IJCAI 2015
Zhiwu Lu, Xin Gao, et al.
IJCAI 2015
Liwei Liu, Freddy Lecue, et al.
ACM Transactions on the Web
Chang Wang, Liangliang Cao, et al.
IJCAI 2015