61 citations · 114 across the 23 of their papers we have counts for
Showing 2018Show all
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cs.IR2018★ 1 cited
Can we leverage rating patterns from traditional users to enhance recommendations for children?
Ion Madrazo Azpiazu, Michael Green, Oghenemaro Anuyah +1
Recommender algorithms performance is often associated with the availability of sufficient historical rating data. Unfortunately, when it comes to children, this data is seldom ava…
cs.IR2018★ 1 cited
Who is Really Affected by Fraudulent Reviews? An analysis of shilling attacks on recommender systems in real-world scenarios
Anu Shrestha, Francesca Spezzano, Maria Soledad Pera
We present the results of an initial analysis conducted on a real-life setting to quantify the effect of shilling attacks on recommender systems. We focus on both algorithm perform…