4 papers
u-cf2vec: Representation Learning for Personalized Algorithm Selection in Recommender Systems
Tomas Sousa-Pereira, Tiago Cunha, Carlos Soares
Collaborative Filtering (CF) has become the standard approach to solve recommendation systems (RS) problems. Collaborative Filtering algorithms try to make predictions about intere…
cf2vec: Collaborative Filtering algorithm selection using graph distributed representations
Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho
Algorithm selection using Metalearning aims to find mappings between problem characteristics (i.e. metafeatures) with relative algorithm performance to predict the best algorithm(s…
Algorithm Selection for Collaborative Filtering: the influence of graph metafeatures and multicriteria metatargets
Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho
To select the best algorithm for a new problem is an expensive and difficult task. However, there are automatic solutions to address this problem: using Metalearning, which takes a…
CF4CF: Recommending Collaborative Filtering algorithms using Collaborative Filtering
Tiago Cunha, Carlos Soares, André C. P. L. F. de Carvalho
Automatic solutions which enable the selection of the best algorithms for a new problem are commonly found in the literature. One research area which has recently received consider…