Title :
An adaptive framework for personalized recommendation algorithms
Author :
Jianchang Tang ; Xinhuai Tang
Author_Institution :
Sch. of Software Eng., Shanghai Jiao Tong Univ., Shanghai, China
Abstract :
Different personalized recommendation algorithms are suitable for different scenarios. In this paper, we use artificial neural networks to implement an adaptive framework. When we add different recommendation algorithms into it and train it with the data from a given scenario, it can calculate the weight of each algorithm, choose suitable algorithms and give a more accurate prediction rating.
Keywords :
neural nets; recommender systems; adaptive framework; artificial neural network; personalized recommendation algorithm; prediction rating; Prediction algorithms; adaptive framework; artificial neural networks; personalized recommendation algorithm;
Conference_Titel :
Cloud Computing and Internet of Things (CCIOT), 2014 International Conference on
Print_ISBN :
978-1-4799-4765-2
DOI :
10.1109/CCIOT.2014.7062515
