Personalized Recommendation Algorithm in Network Resources Based on K-means

2013 ◽  
Vol 12 (17) ◽  
pp. 3931-3938
Author(s):  
Xin Wang
Keyword(s):  
Personalized Recommendation ◽  
Network Resources ◽  
Recommendation Algorithm

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.

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

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

A Network-Based Multi-Dimensional Recommendation Algorithm

2013 ◽  
Vol 765-767 ◽  
pp. 1218-1222
Author(s):  
Xiang Yun Xiong ◽  
Yu Chen Fu ◽  
Zhao Qing Liu
Keyword(s):  
Collaborative Filtering ◽  
Experimental Results ◽  
Personalized Recommendation ◽  
Bipartite Network ◽  
Recommendation Algorithm ◽  
Better Than

Personalized recommendation based on bipartite network has attracted more and more attention. Its obviously better than CF (Collaborative Filtering). In this paper, we propose a multi-dimensional recommendation algorithm called BNPM. It combines item-based, user-based and category-based recommendation model to improve recommendation quality. The experimental results show that the algorithm can improve the diversity and reduce the popularity on the base of holding the accuracy of the recommendation

Sign in / Sign up

Export Citation Format

Share Document