Research on cross‐hierarchical graph network recommendation algorithm based on random walk and convolutional neural network

2021 ◽  
Author(s):  
Meng Huang ◽  
Guohui Sun
Keyword(s):  
Neural Network ◽  
Random Walk ◽  
Convolutional Neural Network ◽  
Recommendation Algorithm ◽  
Hierarchical Graph

scholarly journals Design of the Piano Score Recommendation Image Analysis System Based on the Big Data and Convolutional Neural Network

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Yuanyuan Zhang
Keyword(s):  
Neural Network ◽  
Image Analysis ◽  
Big Data ◽  
Convolutional Neural Network ◽  
Recommendation System ◽  
Piano Music ◽  
Music Recommendation ◽  
Recommendation Algorithm ◽  
Data Environment ◽  
Music Recommendation System

In the era of big data, the problem of information overload is becoming more and more obvious. A piano music image analysis and recommendation system based on the CNN classifier and user preference is designed by using the convolutional neural network (CNN), which can realize accurate piano music recommendation for users in the big data environment. The piano music recommendation system based on the CNN is mainly composed of user modeling, music feature extraction, recommendation algorithm, and so on. In the recommendation algorithm module, the potential characteristics of music are predicted by the regression model, and the matching degree between users and music is calculated according to user preferences. Then, music that users may be interested in is generated and sorted in order to recommend new piano music to relevant users. The image analysis model contains four “convolution + pooling” layers. The classification accuracy and gradient change law of the CNN under RMSProp and Adam optimal controllers are compared. The image analysis results show that the Adam optimal controller can quickly find the direction, and the gradient decreases greatly. In addition, the accuracy of the recommendation system is 55.84%. Compared with the traditional CNN algorithm, this paper uses the convolutional neural network (CNN) to analyze and recommend piano music images according to users’ preferences, which can realize more accurate piano music recommendation for users in the big data environment. Therefore, the piano music recommendation system based on the CNN has strong feature learning ability and good prediction and recommendation ability.

scholarly journals Esophagus segmentation in CT via 3D fully convolutional neural network and random walk

2017 ◽  
Vol 44 (12) ◽  
pp. 6341-6352 ◽  
Author(s):  
Tobias Fechter ◽  
Sonja Adebahr ◽  
Dimos Baltas ◽  
Ismail Ben Ayed ◽  
Christian Desrosiers ◽  
...  
Keyword(s):  
Neural Network ◽  
Random Walk ◽  
Convolutional Neural Network
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