Robustheit in Empfehlungssystemen

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Ein Vortrag von Maximilian Schmidbauer aus dem Hauptseminar "Personalisierung mit großen Daten".

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3 http://de.wikipedia.org/wiki/Robustheit, 1.12.2013

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8 Burke, Mahony, Hurley, Robust Collaborative Recommendation

11 Williams, Mobasher, Burke, Defending Recommender Systems: Detection of Profile Injection Attacks, 2007

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0,00

0,20

0,40

0,60

0,80

1,00

1,20

1,40

1,60

1,80

Random Attack Bandwagon Attack Average Attack

Burke, Mahony, Hurley, Robust Collaborative Recommendation

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0,00

0,10

0,20

0,30

0,40

0,50

0,60

0,70

0,80

0,90

All-Users Segment Attack

Burke, Mahony, Hurley, Robust Collaborative Recommendation

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-2,50

-2,00

-1,50

-1,00

-0,50

0,00

Reverse Bandwagon

Average Attack

Random Attack

Bandwagon Attack

Love/Hate Attack

Burke, Mahony, Hurley, Robust Collaborative Recommendation

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-0,80

-0,70

-0,60

-0,50

-0,40

-0,30

-0,20

-0,10

0,00

0,10

Reverse Bandwagon

Average Attack

Random Attack

Bandwagon Attack

Love/Hate Attack

Burke, Mahony, Hurley, Robust Collaborative Recommendation

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0%

10%

20%

30%

40%

50%

60%

70%

80%

Average Attack Probe Attack Popular Attack

Burke, Mahony, Hurley, Robust Collaborative Recommendation

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