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Synthesizing Knowledge Graphs for Link and Type Prediction BenchmarkingSupervised Typing of Big Graphs using Semantic EmbeddingsN-ary relation extraction for simultaneous T-Box and A-Box knowledge base augmentationUnsupervised learning of an extensive and usable taxonomy for DBpediaKnowledge graph refinement: A survey of approaches and evaluation methodsLarge-scale taxonomy induction using entity and word embeddingsType Prediction in Noisy RDF Knowledge Bases Using Hierarchical Multilabel Classification with Graph and Latent FeaturesServing DBpedia with DOLCE – More than Just Adding a Cherry on Top
P2860
Q30092804-160512ED-A0D8-43CD-99F0-01D51F1BCEFFQ30276709-DD25B203-9A21-4CC8-8075-0CC9760267C5Q55864308-D04884A6-F3CF-4413-8AD2-462853537996Q55864309-B3F3B407-50C2-431D-9A38-432EB09AF82DQ55935883-F93A7E21-40E0-4AB1-908B-C9B05849F3B5Q55935885-5DCE1E68-F0A5-473C-A952-3088DBAAA977Q55935889-29E20903-9BDE-4FD7-B313-68AF7B779008Q57774172-1C61DE8B-1B39-45CE-B7FB-D7302C010980
P2860
description
wetenschappelijk artikel
@nl
наукова стаття, опублікована у 2013
@uk
name
Type Inference on Noisy RDF Data
@en
Type Inference on Noisy RDF Data
@nl
type
label
Type Inference on Noisy RDF Data
@en
Type Inference on Noisy RDF Data
@nl
prefLabel
Type Inference on Noisy RDF Data
@en
Type Inference on Noisy RDF Data
@nl
P1476
Type Inference on Noisy RDF Data
@en
P304
P356
10.1007/978-3-642-41335-3_32
P407
P577
2013-01-01T00:00:00Z