PRBL:A Personalized Recommendation System Based on Bipartite Network Projection and Link Community Detection
In recent years complex network has become a research hot spot for the large-scale systems.The bipartite network,a particular format of the complex network,can be used to describe the personalized recommendation systems that rec-ommend the interesting items to users based on their own interests.In this paper,we propose a personalized recom-mendation systems based on the bipartite network projection and link community detection.The preference from users to items is abstracted as the edges in the bipartite user-item network.To get the relationship between the items,we make the one-mode projection to generate the item-item network.The link community detection is used to cluster the item-s to recommend to preferred users.Our systems could be used for any area with large-scale datasets.The experimental results show that our system could efficiently recommend commodities to the consumers based on the big data from the e-commerce.
Complex network recommendation system link community detection bipartite network projection
Xuemeng Zhai Hangyu Hu Guangmin Hu Youyang Qu
School of Information and Communication Engineering University of Electronic Science and Technology School of Info Technology Deakin University Burwood,Australia
国际会议
2019国图灵大会(ACM Turing Celebration conference-China 2019 )
成都
英文
933-939
2019-05-17（万方平台首次上网日期，不代表论文的发表时间）