Research Article
Research on Personalized Recommendation Algorithm Based on Mobile Social Network Data
@INPROCEEDINGS{10.1007/978-3-030-94551-0_16, author={Xiang Yan and Wen-hua Deng}, title={Research on Personalized Recommendation Algorithm Based on Mobile Social Network Data}, proceedings={Advanced Hybrid Information Processing. 5th EAI International Conference, ADHIP 2021, Virtual Event, October 22-24, 2021, Proceedings, Part I}, proceedings_a={ADHIP}, year={2022}, month={1}, keywords={Mobile social network data Personalization Recommendation algorithm Association rules}, doi={10.1007/978-3-030-94551-0_16} }- Xiang Yan
Wen-hua Deng
Year: 2022
Research on Personalized Recommendation Algorithm Based on Mobile Social Network Data
ADHIP
Springer
DOI: 10.1007/978-3-030-94551-0_16
Abstract
Due to the lack of mining of hidden data in traditional personalized recommendation algorithms, the algorithm is interfered by the mobile social network environment, and it is difficult to accurately recommend targeted data for users. Therefore, research on personalized recommendation algorithms based on mobile social network data. By dividing mobile social network user categories, user information is obtained; based on mobile social network data, user demand characteristics are extracted; potential association rules between users and service needs are mined to build personalized recommendation algorithms. The experimental results show that compared with the traditional recommendation algorithm, the research algorithm has stronger perception and recognition ability, and it can recommend more matching information for users according to different user needs when facing different network environments.
