ItemSelect: A set of Items id for recommending to an active user.

In GACFF: Genetic Similarity in User-Based Collaborative Filtering

Description

Selecting the best items to recommend.

Usage

ItemSelect(ratings, active_user, pre_x)

Arguments

ratings	A rating matrix whose rows are items and columns are users.
active_user	The id of an active user as an integer greater than zero (for example active_user<-6).
pre_x	A set of predicted ratings for all items not rated by the active user.

Details

Items selecting and their order depends on the method (Pearson, NewKNN, Genetic).

Value

item_x

A set of item identifiers recommended to the active user.

References

Nilashi, M., Ibrahim, O. and Bagherifard, K. (2018). A recommender system based on collaborative filtering using ontology and dimensionality reduction techniques. Expert Systems with Applications, vol. 92, pp. 507-520.

Examples

ratings <- matrix(c(  2,    5,  NaN,  NaN,  NaN,    4,
                    NaN,  NaN,  NaN,    1,  NaN,    5,
                    NaN,    4,    5,  NaN,    4,  NaN,
                      4,  NaN,  NaN,    5,  NaN,  NaN,
                      5,  NaN,    2,  NaN,  NaN,  NaN,
                    NaN,    1,  NaN,    4,    2,  NaN),nrow=6,byrow=TRUE)
                    
Pearson.out  <- Pearson (ratings, active_user=6, Threshold_KNN=4)

predict      <-Prediction (ratings, active_user=6, 
                      near_user=Pearson.out$near_user_Pearson, 
                      sim_x=Pearson.out$sim_Pearson, 
                      KNN=length(Pearson.out$sim_Pearson))
                      
ItemSelect (ratings, active_user=6, pre_x=predict)

GACFF documentation built on Dec. 20, 2019, 5:07 p.m.