Genetic Algorithm Based Recommender System -IGC Plus: A Novel Clustering Dependant Recommender System
DOI:
https://doi.org/10.18486/ijcsnt/2.1.018Keywords:
Expected Utility (EU), Mean Absolute Error (MAE), Clustering Dependant Recommendation System (CDRS), Collaborative Filtering (CF), Popularity, Entropy, Bisecting K-mean Algorithm, Genetic Algorithm (GA), Elitist Genetic Algorithm (EGA), Rank Based Genetic Algorithm (RGA), Clustering PlusAbstract
Information Gain through Clustering Plus (IGC+) is a novel clustering dependant recommender system applied in both cold start and non-cold start problems. For comparison purposes, a number of Clustering Dependant Recommender Systems (CD RSs) have been consider and explored in this paper including IGCRGA (Information Gain Clustering through Rank Based Genetic Algorithm), IGCEGA (Information Gain Through Clustering Elitist Genetic Algorithm), among others. The two evaluation metric, Mean Absolute error (MAE) and Expected Unity (EU) used in this work show that, IGC+ emerged vector in terms of providing quality recommendation to the end user amongst the CD RSs considered.
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