Paper Info
Title
Autonomous Semantic Structuring Of Lecture Topics Synthesis Of Knowledge Models
Abstract
Students attending lectures in universities suffer from a weak structural awareness on lecture content. According to learning theories, structural awareness is a relevant factor to association and comprehension of new learning inputs. We synthesize semantic structures from non annotated lecture slides using Topic Modeling algorithms to identify relevant terms and relate them in force-directed graphs. The synthesized graphs provide a structural overview on the topic distribution and relations of non annotated sequential lecture slides.
Year
DOI
Venue
2017
10.5220/0006367903490355
PROCEEDINGS OF THE 9TH INTERNATIONAL CONFERENCE ON COMPUTER SUPPORTED EDUCATION (CSEDU), VOL 2
Keywords
Field
DocType
Latent Dirichlet Allocation, Topic Models, Mental Models, Knowlege Management, Force-directed Algorithms
Computer science,Knowledge management,Structuring,Multimedia
Conference
Citations 
PageRank 
References 
0
0.34
0
Authors
4
Name
Order
Citations
PageRank
Robin Nicolay101.35
Nikolaj Troels Graf von Malotky200.34
Tanja Auge302.70
Alke Martens47323.00