DETERMINING MOVIE RANKINGS USING NON-PERSONALIZED AND PERSONALIZED APPROACHES FOR RECOMMENDER SYSTEM
Providing a useful suggestion of products to online users to increase their consumption on websites is the goal of many companies nowadays. People usually select or purchase a new product based on some friend’s recommendations, comparison of similar products, or feedback from other users. In order t...
Saved in:
Main Author: | Izzah, NUrul |
---|---|
Format: | Final Project |
Language: | Indonesia |
Online Access: | https://digilib.itb.ac.id/gdl/view/54924 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Institut Teknologi Bandung |
Language: | Indonesia |
Similar Items
-
Adversarial Personalized Ranking for Recommendation
by: Xiangnan He, et al.
Published: (2020) -
Stochastically robust personalized ranking for LSH recommendation retrieval
by: LE, Dung D., et al.
Published: (2020) -
Indexable Bayesian personalized ranking for efficient top-k recommendation
by: LE, Dung D., et al.
Published: (2017) -
SGD-Rec: A Matrix Decomposition Based Model for Personalized Movie Recommendation
by: Siripen Pongpaichet, et al.
Published: (2020) -
WebAPIRec: Recommending web APIs to software projects via personalized ranking
by: THUNG, Ferdian, et al.
Published: (2017)