{"title":"基于Novel-CNN的顾客评论情感分析识别","authors":"N. Deepa, J. Priya, T. Devi","doi":"10.1109/ICCCI56745.2023.10128627","DOIUrl":null,"url":null,"abstract":"Sentimental Emotion Recognition is the recognition of emotion which is detected by many fields such as Artificial intelligence, Machine Learning and Deep Learning. The professionals need sentimental analysis for business like social media monitoring, brand monitoring and customer feedback which will help in business for improvising the product based on the emotion gathered from the customers. Sentimental analysis is used in business to mine the data of customers about how they are feeling about the product. Existing systems like Facebook, WhatsApp and twitter use sentimental emotions for sensing the user’s emotions. In our proposed system we are using the Novel Convolution Neural Network (N-CNN) system for sentimental recognition to make better understanding of customers which can be used to improve the product quality. To enhance the accuracy of the proposed model Amazon review for product sales is used which is available in kaggle. Using the proposed model the model in comparison with existing model the preprocessed feature which are extracted from multiple neural networks are recognized. Feature based on the selected customer feedback on constant steps of filtering, max pooling and necessary activation function results are implemented and shown 98.3% of accuracy which is more reliable results than the other Machine learning model.","PeriodicalId":205683,"journal":{"name":"2023 International Conference on Computer Communication and Informatics (ICCCI)","volume":"413 ","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Sentimental Analysis Recognition in Customer review using Novel-CNN\",\"authors\":\"N. Deepa, J. Priya, T. Devi\",\"doi\":\"10.1109/ICCCI56745.2023.10128627\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Sentimental Emotion Recognition is the recognition of emotion which is detected by many fields such as Artificial intelligence, Machine Learning and Deep Learning. The professionals need sentimental analysis for business like social media monitoring, brand monitoring and customer feedback which will help in business for improvising the product based on the emotion gathered from the customers. Sentimental analysis is used in business to mine the data of customers about how they are feeling about the product. Existing systems like Facebook, WhatsApp and twitter use sentimental emotions for sensing the user’s emotions. In our proposed system we are using the Novel Convolution Neural Network (N-CNN) system for sentimental recognition to make better understanding of customers which can be used to improve the product quality. To enhance the accuracy of the proposed model Amazon review for product sales is used which is available in kaggle. Using the proposed model the model in comparison with existing model the preprocessed feature which are extracted from multiple neural networks are recognized. Feature based on the selected customer feedback on constant steps of filtering, max pooling and necessary activation function results are implemented and shown 98.3% of accuracy which is more reliable results than the other Machine learning model.\",\"PeriodicalId\":205683,\"journal\":{\"name\":\"2023 International Conference on Computer Communication and Informatics (ICCCI)\",\"volume\":\"413 \",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-23\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2023 International Conference on Computer Communication and Informatics (ICCCI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCCI56745.2023.10128627\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2023 International Conference on Computer Communication and Informatics (ICCCI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCCI56745.2023.10128627","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Sentimental Analysis Recognition in Customer review using Novel-CNN
Sentimental Emotion Recognition is the recognition of emotion which is detected by many fields such as Artificial intelligence, Machine Learning and Deep Learning. The professionals need sentimental analysis for business like social media monitoring, brand monitoring and customer feedback which will help in business for improvising the product based on the emotion gathered from the customers. Sentimental analysis is used in business to mine the data of customers about how they are feeling about the product. Existing systems like Facebook, WhatsApp and twitter use sentimental emotions for sensing the user’s emotions. In our proposed system we are using the Novel Convolution Neural Network (N-CNN) system for sentimental recognition to make better understanding of customers which can be used to improve the product quality. To enhance the accuracy of the proposed model Amazon review for product sales is used which is available in kaggle. Using the proposed model the model in comparison with existing model the preprocessed feature which are extracted from multiple neural networks are recognized. Feature based on the selected customer feedback on constant steps of filtering, max pooling and necessary activation function results are implemented and shown 98.3% of accuracy which is more reliable results than the other Machine learning model.