Enriching BERT with Knowledge Graph Embeddings for Document Classification

scientific article published on 18 September 2019

Enriching BERT with Knowledge Graph Embeddings for Document Classification is …
instance of (P31):
scholarly articleQ13442814

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P820arXiv classificationcs.CL
cs.IR
cs.LG
P818arXiv ID1909.08402
P953full work available at URLhttps://arxiv.org/pdf/1909.08402.pdf

P50authorBela GippQ50411920
Georg RehmQ67175680
Malte OstendorffQ67389868
P2093author name stringMaria Berger
Julian Moreno-Schneider
Peter Bourgonje
P2860cites workWikidata: A Free Collaborative KnowledgebaseQ18507561
Scikit-learn: Machine Learning in PythonQ28365500
Multi-task Learning of Pairwise Sequence Classification Tasks Over Disparate Label SpacesQ50281314
BERT: Pre-training of Deep Bidirectional Transformers for Language UnderstandingQ57267388
PyTorch-BigGraph: A Large-scale Graph Embedding SystemQ62657788
ERNIE: Enhanced Language Representation with Informative EntitiesQ64141042
ERNIE: Enhanced Representation through Knowledge IntegrationQ64141094
Using Wikipedia knowledge to improve text classificationQ66710742
P4510describes a project that usesWikidataQ2013
P407language of work or nameEnglishQ1860
P921main subjectdocument classificationQ302088
knowledge graphQ33002955
knowledge graph embeddingQ33003557
Bidirectional Encoder Representations from TransformerQ61726893
P1104number of pages8
P577publication date2019-09-18
P1433published inarXivQ118398
P859sponsorFederal Ministry of Education and ResearchQ492234
P1476titleEnriching BERT with Knowledge Graph Embeddings for Document Classification

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