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- W4360994536 abstract "Over the past ten years, the number of internet users has increased tremendously. Due to the e- commerce industry's fast growth, practically all goods are now sold online. Before making a purchasing choice, the customer gets comprehensive information on the items they are interested in. Customer opinions and reviews assist businesses and other consumers in making wise decisions and enhancing the purchasing experience. It is getting harder to comprehend and keep track of every customer's wants since the number of individuals leaving evaluations is increasing quickly. Some evaluations, which make it more time-consuming and challenging to analyse for business, are purposefully overly lengthy, unclear, incomplete, and short. A customer Feedback Evaluation System is needed to address this issue since it will track every one of those evaluations and offer statistical data for improving the manufacturer's quality and functionality. The suggested approach uses machine learning to give each word a certain amount of weight." @default.
- W4360994536 created "2023-03-30" @default.
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- W4360994536 date "2023-02-02" @default.
- W4360994536 modified "2023-10-18" @default.
- W4360994536 title "Decoding and Analysing Consumer Feedback for Companies and Goods using Machine Learning" @default.
- W4360994536 doi "https://doi.org/10.1109/icais56108.2023.10073801" @default.
- W4360994536 hasPublicationYear "2023" @default.
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