SE@M 2010: Automatic Keywords Extraction - a Basis for Content Recommendation
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Presented at SE@M 2010 - Fourth International Workshop on Search and Exchange of e-le@rning Materials (SE@M’10). 27-28 September 2010, Barcelona, Spain
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SE@M 2010: Automatic Keywords Extraction - a Basis for Content Recommendation
- 1. Automatic Keywords Extraction – A Basis for Content Recommendation Ivana Bosnić Katrien Verbert Erik Duval University of Zagreb, Croatia Katholieke Universiteit Leuven, Belgium
- 3. General idea and use case 1
- 5. Use case Content available Broader c ontext Content Reuse Metadata LORs Wikipedia Blogs LMS Course context Author Current content Tools Integration Referencing
- 12. Automatically extracted keywords: user grading I Average of keyword relevancy grading, per presentation
- 13. Automatically extracted keywords: user grading II Average of keyword relevancy grading, per topic
- 14. Automatically extracted keywords: user grading III Average user grading per particular Zemanta rank
- 16. User-generated keywords Matches between user- and automatically generated keywords
- 18. Evaluation in the environment 3
- 23. Evaluation I The relation between user and internat ranking The average of user rankings
- 27. Evaluation II The relation between user and internat ranking The average of user rankings