A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf
.
Type Prediction in RDF Knowledge Bases Using Hierarchical Multilabel Classification
2016
Proceedings of the 6th International Conference on Web Intelligence, Mining and Semantics - WIMS '16
Large Semantic Web knowledge bases are often noisy, incorrect, and incomplete with respect to type information. Automatic type prediction can help reduce such incompleteness, and, as previous works show, statistical methods are well-suited for this kind of data. Since most Semantic Web knowledge bases come with an ontology defining a type hierarchy, in this paper, we rephrase the type prediction problem as a hierarchical multilabel classification problem. We propose SLCN, a modification of the
doi:10.1145/2912845.2912861
dblp:conf/wims/MeloPV16
fatcat:ann3y6krm5cfnhsm24fcetzjdq