The Hybrid Recommender System of the Indonesian Online Market Products using IMDb weight rating and TF-IDF
Today, consumers are faced with an abundance of information on the internet; accordingly, it is hard for them to reach the vital information they need. One of the reasonable solutions in modern society is implementing information filtering. Some researchers implemented a recommender system as filter...
Guardado en:
Autores principales: | Muhammad Johari, Arif Laksito |
---|---|
Formato: | article |
Lenguaje: | ID |
Publicado: |
Ikatan Ahli Indormatika Indonesia
2021
|
Materias: | |
Acceso en línea: | https://doaj.org/article/89a4fde4e174489c810f467f53591456 |
Etiquetas: |
Agregar Etiqueta
Sin Etiquetas, Sea el primero en etiquetar este registro!
|
Ejemplares similares
-
Perbandingan Metode TF-ABS dan TF-IDF Pada Klasifikasi Teks Helpdesk Menggunakan K-Nearest Neighbor
por: Riza Adrianti Supono, et al.
Publicado: (2021) -
Adapt Learning Path by Recommending Problems to Struggling Learners
por: Youssef Jdidou, et al.
Publicado: (2021) -
Pemeringkatan Pencarian pada Buku Pedoman Akademik Filkom UB Menuju Merdeka Belajar dan Free E-Book Pembelajaran Sebagai Prototype Local Smart Micro Search Engine Menggunakan Algoritma Pagerank dan TF-IDF
por: Imam Cholissodin, et al.
Publicado: (2021) -
Community Formation as a Byproduct of a Recommendation System: A Simulation Model for Bubble Formation in Social Media
por: Franco Bagnoli, et al.
Publicado: (2021) -
Addressing Cold Start New User in Recommender System Based on Hybrid Approach: A review and bibliometric analysis
por: Nasy`an Taufiq Al Ghifari, et al.
Publicado: (2021)