GACFF (version 1.0)

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

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.

Value

item_x

A set of item identifiers recommended to the active user.

Details

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

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

# NOT RUN {
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)
# }