Diversity

Diversity means balancing recommendation lists to cover the user's whole set of interests. One way to compute the diversity is using: div(Ru)=∑i∈Ru∑j∈Ru,i!=jd(i,j)div(R_u)= \sum_{i \in R_u} \sum_{j \in R_u, i!=j}d(i,j), where d(i,j)d(i,j) measures the distance between two items (cosine distance can be used). Another approach is given by this paper, in which a relative rank discount function of each pair of items is used (disc(k) and disc(l|k)); moreover the metric uses a distance function between the items (cosine), the formula is: div(Ru)=∑k=1∣Ru∣∑l=1∣Ru∣disc(k)disc(l∣k)d(ik,il)∀ik≠ildiv(R_u)= \sum_{k=1}^{|R_u|} \sum_{l=1}^{|R_u|} disc(k)disc(l|k)d(i_k,i_l) \forall i_k \neq i_l.

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#recsys