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Extracting dependency relations from digital learning content

Conference Paper
Publication Date:
2018
abstract:
Digital Libraries present tremendous potential for developing e-learning applications, such as text comprehension and question-answering tools. A way to build this kind of tools is structuring the digital content into relevant concepts and dependency relations among them. While the literature offers several approaches for the former, the identification of dependencies, and specifically of prerequisite relations, is still an open issue. We present an approach to manage this task.
Iris type:
04.01 Contributo in Atti di convegno
Keywords:
Prerequisite relationship; Concept extraction; Graph mining
List of contributors:
Venturi, Giulia; Dell'Orletta, Felice
Authors of the University:
DELL'ORLETTA FELICE
VENTURI GIULIA
Handle:
https://iris.cnr.it/handle/20.500.14243/374898
Published in:
COMMUNICATIONS IN COMPUTER AND INFORMATION SCIENCE (PRINT)
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URL

http://www.scopus.com/record/display.url?eid=2-s2.0-85041860435&origin=inward
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