{"title":"Analysis of Customer Review and Predicting Future Release of the Product using machine learning concepts","authors":"P. R. Sabapathi, K. Kaliyamurthie","doi":"10.1109/IC3IOT53935.2022.9767956","DOIUrl":null,"url":null,"abstract":"The customer reviews are in unstructured form and natural language. To make data structured, natural language processing algorithms like sentimental analysis are used. This method is to extract whether the reviews are positive, negative, or neutral in the state. Sentimental analysis is used to capture each product's opinions and feelings about the particular product. The main objective of the proposed work is to predict the future release of the product. For prediction, machine learning algorithms along with sentimental analysis are added that provide better performance. In the proposed work, firstly the data is collected, and then it is preprocessed. Secondly, Vader sentiment analysis is implemented for analyzing the customer reviews followed by extracting the features. Random forest classifiers were carried out for improving the performance pursued by predicting the future release of the product using a decision tree algorithm. The proposed work provides and improves performance results compared to the existing works.","PeriodicalId":430809,"journal":{"name":"2022 International Conference on Communication, Computing and Internet of Things (IC3IoT)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-03-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2022 International Conference on Communication, Computing and Internet of Things (IC3IoT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IC3IOT53935.2022.9767956","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The customer reviews are in unstructured form and natural language. To make data structured, natural language processing algorithms like sentimental analysis are used. This method is to extract whether the reviews are positive, negative, or neutral in the state. Sentimental analysis is used to capture each product's opinions and feelings about the particular product. The main objective of the proposed work is to predict the future release of the product. For prediction, machine learning algorithms along with sentimental analysis are added that provide better performance. In the proposed work, firstly the data is collected, and then it is preprocessed. Secondly, Vader sentiment analysis is implemented for analyzing the customer reviews followed by extracting the features. Random forest classifiers were carried out for improving the performance pursued by predicting the future release of the product using a decision tree algorithm. The proposed work provides and improves performance results compared to the existing works.