Introduction RecSysTEL workshop 2012

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Hendrik Drachsler

Recsystel2012 Introduction and Best Paper slides

Technologie Business

dataTEL challenge & dataTEL
cafe event

• a call for TEL datasets

• eight data sets submitted

http://bit.ly/ieqmWW

http://dev.mendeley.com/datachallenge/

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 - - - - + +

http://bit.ly/A4CwZU

http://bit.ly/acBKsp

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

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

Algorithms

Paper A:
Cristian
AVG: 2.6

Paper B:
Pythagoras
AVG: 3

Algorithms

Paper A:
Cristian
AVG: 3.3

Paper B:
Pythagoras
AVG: 2.9

Algorithms

Paper A:
Cristian
AVG: 3

Paper B:
Pythagoras
AVG: 3.7

Application

Paper A:
Cristian
AVG: 3.3

Paper B:
Pythagoras
AVG: 3.3

Application

Paper A:
Cristian
AVG: 3

Paper B:
Pythagoras
AVG: 3.7

Application

Paper A:
Cristian
AVG: 2.7

Paper B:
Pythagoras
AVG: 2.7

Application

Paper A:
Cristian
AVG: 3.5

Paper B:
Pythagoras
AVG: 3.6

Application

Paper A:
Cristian
AVG: 2.6

Paper B:
Pythagoras
AVG: 3

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

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Introduction RecSysTEL workshop 2012

1.

2.

3.

4. dataTEL challenge & dataTEL cafe event • a call for TEL datasets • eight data sets submitted http://bit.ly/ieqmWW

5. http://dev.mendeley.com/datachallenge/

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 - - - - + +

7.

8. http://bit.ly/A4CwZU

9. http://bit.ly/acBKsp

10.

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

Hinweis der Redaktion

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?