학술논문

MG-DAN-SNR: Research on Improved POI Recommendation Algorithm Based on Gating and Mixture of Experts Model
Document Type
Conference
Source
2022 IEEE 10th International Conference on Computer Science and Network Technology (ICCSNT) Computer Science and Network Technology (ICCSNT), 2022 IEEE 10th International Conference on. :49-52 Oct, 2022
Subject
Communication, Networking and Broadcast Technologies
Computing and Processing
Robotics and Control Systems
Signal Processing and Analysis
Filtering
Stability criteria
Neural networks
Prediction algorithms
Systems engineering and theory
Data models
Reliability
Gating
Mixture of Experts
POI recommendation algorithm
Language
ISSN
2690-5892
Abstract
With the development of LBSN, more and more attention has been paid to constructing interest point recommendation based on historical data of interest points, and there are many algorithms to predict and analyze interest points. However, in the traditional POI recommendation system, the user's information selection is not focused, which leads to the poor utilization of user data. To solve this problem, this paper improves the existing POI recommendation algorithm DAN-SNR, and constructs a new POI recommendation algorithm model MG-DAN-SNR based on deep neural network. The simulation experiment on Foursquare data set shows that the improved model has a significant improvement in the evaluation index, and can better recommend for users.