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Event-enhanced learning for KG completion

Abstract:

Statistical learning of relations between entities is a popular approach to address the problem of missing data in Knowledge Graphs. In this work we study how relational learning can be enhanced with background of a special kind: event logs, that are sequences of entities that may occur in the graph. Events naturally appear in many important applications as background. We propose various embedding models that combine entities of a Knowledge Graph and event logs. Our evaluation shows that our ...

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Publication status:
Published
Peer review status:
Peer reviewed

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Publisher copy:
10.1007/978-3-319-93417-4_35

Authors


Publisher:
Springer Verlag
Host title:
Lecture Notes in Computer Science
Journal:
Lecture Notes in Computer Science More from this journal
Pages:
541-559
Publication date:
2018-06-03
Acceptance date:
2018-03-02
DOI:
ISSN:
0302-9743 and 1611-3349
ISBN:
9783319934167
Pubs id:
pubs:858950
UUID:
uuid:a9193a56-f41f-4ea2-aa37-2cda743c854b
Local pid:
pubs:858950
Source identifiers:
858950
Deposit date:
2019-02-22

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