About: Fast and Exact Rule Mining with AMIE 3

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	Fast and Exact Rule Mining with AMIE 3
Creator	Galárraga, Luis Lajus, Jonathan Suchanek, Fabian
Source	PMC
abstract	Given a knowledge base (KB), rule mining finds rules such as “If two people are married, then they live (most likely) in the same place”. Due to the exponential search space, rule mining approaches still have difficulties to scale to today’s large KBs. In this paper, we present AMIE 3, a system that employs a number of sophisticated pruning strategies and optimizations. This allows the system to mine rules on large KBs in a matter of minutes. Most importantly, we do not have to resort to approximations or sampling, but are able to compute the exact confidence and support of each rule. Our experiments on DBpedia, YAGO, and Wikidata show that AMIE 3 beats the state of the art by a factor of more than 15 in terms of runtime.
has issue date	2020-05-07(xsd:dateTime)
bibo:doi	10.1007/978-3-030-49461-2_3
has license	no-cc
sha1sum (hex)	6da67be013b92d64c78970a63e5ec2946b86d87a
schema:url	https://doi.org/10.1007/978-3-030-49461-2_3
resource representing a document's title	Fast and Exact Rule Mining with AMIE 3
has PubMed Central identifier	PMC7250613
schema:publication	The Semantic Web
resource representing a document's body	covid:6da67be013b92d64c78970a63e5ec2946b86d87a#body_text
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