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data.input.path=filmtrust/rating
data.column.format=UIR
rec.recommender.class=itemknn
rec.recommender.isranking=false
rec.recommender.ranking.topn=10
rec.recommender.similarities=item
rec.similarity.class=pcc
rec.neighbors.knn.number=50
rec.similarity.shrinkage=10
#default weight
rec.ensemble.weight = 1.0
rec.recommender.fullClassName = net.librec.recommender.cf.ranking.ItemKNNRecommender