The Real-time Updating Problem for Recommendation Systems with Implicit Feedback
碩士 === 國立交通大學 === 電信工程研究所 === 103 === With the prosperity of e-commerce, online vendors use the recommendation systems in different fields. Classic algorithms for data analysis, such as cosine-similarity, user-based collaborative filtering, are designed assuming that data are stationary and will not...
Main Authors: | Tsai, Kun-Hung, 蔡昆宏 |
---|---|
Other Authors: | Wang, Li-Chun |
Format: | Others |
Language: | en_US |
Published: |
2015
|
Online Access: | http://ndltd.ncl.edu.tw/handle/umq5rr |
Similar Items
-
Hybrid Real-Time Matrix Factorization for Implicit Feedback Recommendation Systems
by: Chia-Yu Lin, et al.
Published: (2018-01-01) -
A New Approach of Auto-recommendation using Implicit Feedback
by: Chih-Hung Wu, et al.
Published: (2004) -
Keyword-based Recommendation Service using Implicit Feedback on Hadoop
by: TSAI, JIA-HAN, et al.
Published: (2017) -
An interval-based Recommender System with Implicit Feedback
by: Szu-Chi Chao, et al.
Published: (2011) -
Alleviation of Data Overdispersion On Implicit Feedback for Recommender Systems
by: Li-Yen Kuo, et al.
Published: (2019)