Research of Multi-objective Personalized Recommendation Algorithm Based on Multi-thread Concurrency

2019 ◽  
pp. 79-91
Author(s):  
Xiaoyan Shi ◽  
Wei Fang ◽  
Guizhu Zhang ◽  
Shi Cheng ◽  
Quan Wang
Keyword(s):  
Personalized Recommendation ◽  
Recommendation Algorithm ◽  
Multi Objective

Optimized Collaborative Filtering Recommendation Based on User’s Social Relationships

2014 ◽  
Vol 1044-1045 ◽  
pp. 1484-1488
Author(s):  
Yue Kun Fan ◽  
Xin Ye Li ◽  
Meng Meng Cao
Keyword(s):  
Collaborative Filtering ◽  
Social Relationships ◽  
Digital Libraries ◽  
Social Relationship ◽  
Nearest Neighbor ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Personalized Recommendation ◽  
Recommendation Algorithm

Currently collaborative filtering is widely used in e-commerce, digital libraries and other areas of personalized recommendation service system. Nearest-neighbor algorithm is the earliest proposed and the main collaborative filtering recommendation algorithm, but the data sparsity and cold-start problems seriously affect the recommendation quality. To solve these problems, A collaborative filtering recommendation algorithm based on users' social relationships is proposed. 0n the basis of traditional filtering recommendation technology, it combines with the interested objects of user's social relationship and takes the advantage of the tags to projects marked by users and their interested objects to improve the methods of recommendation. The experimental results of MAE ((Mean Absolute Error)) verify that this method can get better quality of recommendation.

scholarly journals College Library Personalized Recommendation System Based on Hybrid Recommendation Algorithm

Procedia CIRP ◽  
2019 ◽  
Vol 83 ◽  
pp. 490-494 ◽  
Author(s):  
Yonghong Tian ◽  
Bing Zheng ◽  
Yanfang Wang ◽  
Yue Zhang ◽  
Qi Wu
Keyword(s):  
Recommendation System ◽  
Personalized Recommendation ◽  
Recommendation Algorithm ◽  
College Library ◽  
Hybrid Recommendation
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