Introduction RecSysTEL workshop 2012
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Recsystel2012 Introduction and Best Paper slides
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Introduction RecSysTEL workshop 2012
- 4. dataTEL challenge & dataTEL cafe event • a call for TEL datasets • eight data sets submitted http://bit.ly/ieqmWW
- 6. Mendeley APOSDL ReMashed Organic. Mace Melt E edunet Collection period 1 year 3 months 2 years 9 3 years 6 months months Users 200.000 6 140 1.000 1.148 98 Items 1.857.912 163 96.000 11.000 12.000 1.923 Activities 4.848.725 1.500 23.264 920 461.982 16.353 reads + + - - + - tags - (+) + + + + ratings (+) - + + + + downloads + + - - + + search - + - - + - collaborations - + - - - - tasks/goals - + + - - - sequence - + - - - - competence - + - - + - time - - - - + +
- 11. TalkExplorer - Conference Navigator Participate in a short user study: • bookmark papers that are relevant with this visualization • you can win an iPod Nano! http://bit.ly/cn3talkexplorer
- 12. RecSysTEL - Best paper award 2012 Paper A: Cristian Cechinel et al. (2012) Populating Learning Object Repositories with Hidden Internal Quality Information Paper B: Pythagoras Karampiperis et al. (2012) Sentiment Analysis: A tool for Rating Attribution to Content in Recommender Systems
- 13. Algorithms Paper A: Cristian AVG: 2.6 Paper B: Pythagoras AVG: 3
- 14. Algorithms Paper A: Cristian AVG: 3.3 Paper B: Pythagoras AVG: 2.9
- 15. Algorithms Paper A: Cristian AVG: 3 Paper B: Pythagoras AVG: 3.7
- 16. Application Paper A: Cristian AVG: 3.3 Paper B: Pythagoras AVG: 3.3
- 17. Application Paper A: Cristian AVG: 3 Paper B: Pythagoras AVG: 3.7
- 18. Application Paper A: Cristian AVG: 2.7 Paper B: Pythagoras AVG: 2.7
- 19. Application Paper A: Cristian AVG: 3.5 Paper B: Pythagoras AVG: 3.6
- 20. Application Paper A: Cristian AVG: 2.6 Paper B: Pythagoras AVG: 3
- 21. And the best paper goes to: Paper B: Pythagoras Karampiperis et al. (2012) Sentiment Analysis: A tool for Rating Attribution to Content in Recommender Systems
Editor's Notes
- How can data sets be shared according to privacy and legal protection rights? How to develop a respective policy to use and share data sets? How to pre-process data sets to make them suitable for other researchers? How to define common evaluation criteria for TEL recommender systems? How to develop overview methods to monitor the performance of TEL recommender systems on data sets?