SISTEM REKOMENDASI BERBASIS KOMBINASI SEMANTIC SIMILARITY DAN COLLABORATIVE FILTERING (STUDI KASUS PADA TOKO ACCESORIES HANDPHONE BESSELLING CELL) - , IMAM FAHRURROZI, Dr. Azhari SN, M.T. ([Yogyakarta] : Universitas Gadjah Mada, 2014)
Recommendation system is a component which has been developed for online commerce purposes. In this issue, one of the popular methods that has been widely used is collaborative filtering. However, this method has some drawbacks and needs to be improved. Therefore, in this research a combination of collaborative filtering and a semantic similarity with Leacock Chodorow method has been done, and it is expected reducing some deficiencies on the original collaborative filtering method. Based on the performance tests, the results conclude that the combination can reduce some weaknesses on the original collaborative filtering, especially on the cold-start item and sparsity issue. For this case, based on the results of some experiments, the best value of the semantic combination parameter is 0,30. Hence, this proposed method produces the smaller MAE value (error value) compared to the original method.