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RDF2Vec: RDF Graph Embeddings for Data Mining
Published on Nov 10, 20163213 Views
Linked Open Data has been recognized as a valuable source for background information in data mining. However, most data mining tools require features in propositional form, i.e., a vector of nominal o
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Chapter list
RDF2Vec: RDF Graph Embeddings for Data Mining00:00
Introduction - 100:13
Introduction - 200:39
Motivation - 101:25
Motivation - 201:47
Motivation - 301:57
Motivation - 402:02
Vision02:42
RDF2VEC APPROACH03:11
RDF2Vec - 103:16
Word2vec – Neural Language Model04:11
CBOW04:44
Word Embedding - 105:21
Word Embedding - 205:29
Word Embedding - 305:44
Word Embedding - 405:45
Word Embedding - 505:57
Word Embedding - 606:04
Word2vec – Neural Language Model06:14
Skip-gram06:26
RDF2vec - 206:30
Graph Walks RDF2vec - 106:47
Graph Walks RDF2vec - 206:59
Graph Walks RDF2vec - 307:13
Entity Embedding07:23
Weisfeiler-Lehman Kernel - 107:37
Weisfeiler-Lehman Kernel - 208:04
Weisfeiler-Lehman Kernel - 308:11
Weisfeiler-Lehman Kernel - 408:19
WL Kernel RDF2vec - 108:26
WL Kernel RDF2vec - 209:03
EVALUATION09:12
Evaluation Setup09:17
Domain Specific RDF Datasets10:12
Large Cross-Domain RDF Datasets11:05
Results: classification12:02
Results: regression12:09
Results Summary12:38
Other Use-Cases13:58
Conclusion14:33