E-commerce Personalized Recommendation System Design Based on Multi-agent

2012 ◽  
pp. 159-164 ◽  
Author(s):  
Ya Luo
Keyword(s):  
System Design ◽  
Recommendation System ◽  
Personalized Recommendation ◽  
Multi Agent

Research on the Model of Personalized Recommendation System Based on Multi Agent

2014 ◽  
Vol 644-650 ◽  
pp. 3016-3019
Author(s):  
Qian Wang ◽  
Jin Zhen Ping ◽  
Li Li Yu ◽  
Zhi Juan Wang
Keyword(s):  
Recommendation System ◽  
Personalized Recommendation ◽  
Agent Technology ◽  
Web Log Mining ◽  
Architecture Model ◽  
Web Log ◽  
Processing Power ◽  
Function Modules ◽  
Multi Agent ◽  
Log Mining

There are some lacks of intelligence, self-adaptability, initiative and processing power limitations in the traditional recommendation system. Using the multi-agent technology and the web log mining technology, this paper converts the function modules of traditional personalized recommendation system into an agent. This paper proposes an architecture model based on multi-agent e-commerce personalized recommendation system (MAPRS), and discusses the function of each component of the model and the system's running processes.

Study on Personalized Recommendation Technology of Digital TV Programs

2013 ◽  
Vol 347-350 ◽  
pp. 3035-3038
Author(s):  
Xiao Bin Wang ◽  
Qing Jun Wang
Keyword(s):  
Collaborative Filtering ◽  
Recommendation System ◽  
Digital Tv ◽  
Personalized Recommendation ◽  
Digital Television ◽  
Content Filtering ◽  
Recommendation Algorithm ◽  
Tv Program ◽  
Collaborative Filtering Algorithm ◽  
Multi Agent

This paper aims at one of key technologies in digital television development ---intelligent personalized recommendation technology of digital TV programs for study. This paper proposes to take advantage of ample TV-Anytime to describe metadata so as to perform specific plans of guide service for TV programs based on TV-Anytime metadata specification. It combines technology such as data mining and artificial intelligence etc with a view of building a personalized TV program recommendation system on the framework of the multi-agent. Besides, a hybrid algorithm with content filtering and collaborative filtering based on the systematical recommendation algorithm has been put forward. In order to overcome the deficiencies of traditional collaborative filtering algorithm which relies on users explicit evaluation, the paper represents an improved algorithm with the footing of content collaborative filtering.

Using Concept Lattice for Personalized Recommendation System Design

2017 ◽  
Vol 11 (1) ◽  
pp. 305-314 ◽  
Author(s):  
Caifeng Zou ◽  
Daqiang Zhang ◽  
Jiafu Wan ◽  
Mohammad Mehedi Hassan ◽  
Jaime Lloret
Keyword(s):  
System Design ◽  
Recommendation System ◽  
Concept Lattice ◽  
Personalized Recommendation
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