AMIE: Association Rule Mining under Incomplete Evidence in Ontological Knowledge Bases

First Page		Document Content
Date: 2014-07-21 08:47:06 Computing Software engineering Data Semantic Web Association rule learning Data management Data mining Prolog Datalog Resource Description Framework Inference		AMIE: Association Rule Mining under Incomplete Evidence in Ontological Knowledge Bases Add to Reading List Source URL: www2013.wwwconference.org Download Document from Source Website File Size: 769,48 KB Share Document on Facebook

	RDF as Graph-Based, Diagrammatic Logic Frithjof Dau Dept. of Mathematics, Dresden Technical University, Germany Abstract. The Resource Description Framework (RDF) is the basic standard for representing information in the DocID: 1sFfn - View Document
	Human Associations and DBpedia Don’t Discard Wikilinks Jörn Hees, Rouven Bauer, Joachim Folz, Damian Borth, and Andreas Dengel 1 2 DocID: 1rua8 - View Document
	Microsoft Word - ProdLight-BIS2007-lncs.doc DocID: 1rt9m - View Document
	Visualizing the Evolution of Ontologies: A Dynamic Graph Perspective Michael Burch1 and Steffen Lohmann2 1 VISUS, University of Stuttgart, Germany DocID: 1rt8K - View Document
	A Natural Language Interface for Querying General and Individual Knowledge (Full Version) Yael Amsterdamer, Anna Kukliansky, and Tova Milo Tel Aviv University DocID: 1rt8u - View Document