{"title":"基于用户评论的卷积推荐神经网络系统","authors":"P. Kirubanantham, A. Saranya, D. Kumar","doi":"10.1109/ICCCT53315.2021.9711772","DOIUrl":null,"url":null,"abstract":"Nowadays, every user purchases a ticket based on the movie's story ranking. Some users enjoy horror films, fight films, and other genres; similarly, users can choose a film and purchase a ticket. In our proposed model, we use a Neural Network with a recommended system to provide better movies to users based on movie ratings and feedback. We can get better accuracy and have better movies by using Neural Networks based on the user's previous movie experience. We improved the accuracy and prediction level of the movies in our proposed model based on user feedback and ratings. Compared to the existing movie system, our proposed model provides better accuracy and recommends that the user enjoy the tickets booking.","PeriodicalId":162171,"journal":{"name":"2021 4th International Conference on Computing and Communications Technologies (ICCCT)","volume":"154 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2021-12-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Convolutional Recommended Neural Network system based on user reviews for movies\",\"authors\":\"P. Kirubanantham, A. Saranya, D. Kumar\",\"doi\":\"10.1109/ICCCT53315.2021.9711772\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Nowadays, every user purchases a ticket based on the movie's story ranking. Some users enjoy horror films, fight films, and other genres; similarly, users can choose a film and purchase a ticket. In our proposed model, we use a Neural Network with a recommended system to provide better movies to users based on movie ratings and feedback. We can get better accuracy and have better movies by using Neural Networks based on the user's previous movie experience. We improved the accuracy and prediction level of the movies in our proposed model based on user feedback and ratings. Compared to the existing movie system, our proposed model provides better accuracy and recommends that the user enjoy the tickets booking.\",\"PeriodicalId\":162171,\"journal\":{\"name\":\"2021 4th International Conference on Computing and Communications Technologies (ICCCT)\",\"volume\":\"154 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2021-12-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2021 4th International Conference on Computing and Communications Technologies (ICCCT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCT53315.2021.9711772\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2021 4th International Conference on Computing and Communications Technologies (ICCCT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCT53315.2021.9711772","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Convolutional Recommended Neural Network system based on user reviews for movies
Nowadays, every user purchases a ticket based on the movie's story ranking. Some users enjoy horror films, fight films, and other genres; similarly, users can choose a film and purchase a ticket. In our proposed model, we use a Neural Network with a recommended system to provide better movies to users based on movie ratings and feedback. We can get better accuracy and have better movies by using Neural Networks based on the user's previous movie experience. We improved the accuracy and prediction level of the movies in our proposed model based on user feedback and ratings. Compared to the existing movie system, our proposed model provides better accuracy and recommends that the user enjoy the tickets booking.