the austrian education portal. semantic technologies for e-learning
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
based on an idea by MinRat Mag. Dr. R. HawleHead Section IT Systems for Learning
Austrian Ministry for Teaching, Art and Culture
Carlo A. TrugenbergerInfoCodex Semantic Technologies AG, CH-9470 Buchs
December 2008 1www.InfoCodex.com
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
Problems
• Difficulties in formulating and adopting standards for learning objects (common problem to all top-down approaches)
• Large quantities of heterogeneous learning object repositories
• Lack of appropriate and effective search tools for the identification and composition of learning objects
• Lack of visualization tools for large quantities of information no overview of the available learning material
December 2008 www.InfoCodex.com 2
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
Manually tagging and annotating in real life:
December 2008 www.InfoCodex.com 3
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
December 2008 www.InfoCodex.com 4
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
December 2008 www.InfoCodex.com 5
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
“Semantic” = “pertaining to meaning”
Semantic technologies machines access the meaning of content
• 1st approach: top-down manually tag all Web pages by invisible, computer-readable metadata RDF, OWL,…
• 2nd approach: bottom-up abandon dream of re-coding all Web sites and develop better computational intelligence to enable machines to understand enough content for practical applications
December 2008 www.InfoCodex.com 6
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
Concrete examples of semantic content modeling
• Automatic categorization: self-organized / tuned / pre-defined (85% precision / 91% recall on “noisy”, multi-lingual documents) cross-lingual content recognition • Synonym search, Semantic search Content similarity search
• Semantic links between documents
• Abstract generation
December 2008 www.InfoCodex.com 7
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
Virtual library visualization
December 2008 www.InfoCodex.com 8
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
Semantic search
December 2008 www.InfoCodex.com 9
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
Content similarity search
December 2008 www.InfoCodex.com 10
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
December 2008 www.InfoCodex.com 11
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The Austrian Education PortalSemantic Technologies for E-learning
The Austrian Education PortalSemantic Technologies for E-learning
December 2008 www.InfoCodex.com 12