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Robustheit in Empfehlungssystemen
 

Robustheit in Empfehlungssystemen

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

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

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    Robustheit in Empfehlungssystemen Robustheit in Empfehlungssystemen Presentation Transcript

    •    2
    •  3 http://de.wikipedia.org/wiki/Robustheit, 1.12.2013
    •      4
    • 5
    •   6
    •   7
    •    8 Burke, Mahony, Hurley, Robust Collaborative Recommendation
    •    9 http://www.enzyklopaedie-der-wirtschaftsinformatik.de, 1.12.2013
    •    10 http://www.enzyklopaedie-der-wirtschaftsinformatik.de, 1.12.2013
    •    ∅  11 Williams, Mobasher, Burke, Defending Recommender Systems: Detection of Profile Injection Attacks, 2007
    •     12
    •  ∅     13
    •  ∅      14
    •         15
    •      16
    •     ∅   17
    •       18
    •     19
    •      20
    •      21
    •    22
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    •         24
    • 1,80 1,60 1,40 1,20 1,00 0,80 0,60 0,40 0,20 0,00 Random Attack Bandwagon Attack Average Attack 25 Burke, Mahony, Hurley, Robust Collaborative Recommendation
    • 0,90 0,80 0,70 0,60 0,50 0,40 0,30 0,20 0,10 0,00 All-Users Segment Attack 26 Burke, Mahony, Hurley, Robust Collaborative Recommendation
    • 0,00 -0,50 Reverse Bandwagon Average Attack Random Attack Bandwagon Love/Hate Attack Attack -1,00 -1,50 -2,00 -2,50 27 Burke, Mahony, Hurley, Robust Collaborative Recommendation
    • 0,10 0,00 -0,10 -0,20 -0,30 -0,40 -0,50 -0,60 -0,70 -0,80 Reverse Bandwagon Average Attack Random Attack Bandwagon Love/Hate Attack Attack 28 Burke, Mahony, Hurley, Robust Collaborative Recommendation
    • 80% 70% 60% 50% 40% 30% 20% 10% 0% Average Attack Probe Attack Popular Attack 29 Burke, Mahony, Hurley, Robust Collaborative Recommendation
    •       30
    •     31
    •     32
    •       33
    •   34 Williams, Mobasher, Burke, Defending Recommender Systems: Detection of Profile Injection Attacks, 2007
    •    35
    •    36
    •      37
    •     38
    •     39
    •       40
    •     41
    •     42
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    • 44