CLASSIFICATION OF REVIEWS, ERROR REPORTS ANDPRODUCT FEATURE REQUESTS USING MACHINE LEARNINGMETHODS
Bakdaulet Tolbassy · Suleyman Demirel University Bulletin Natural and Technical Sciences · 2023
This article proposes a solution for filtering and categorizinguser feedback on software products, which can be overwhelming in quantity andoften includes uninformative or fake reviews. The proposed approach involvesusing machine learning methods for classifying reviews into categories such aserror reports, product feature requests, and other reviews. The article comparesthe performance of different classification ML algorithms and investigates theimpact of preprocessing options on classification accuracy. Additionally, thearticle addresses the task of identifying groups of similar reviews in eachcategory, which can be useful for detecting duplicates and identifying patterns.The proposed solution is tested on a dataset and compared with existingsolutions. The article concludes by highlighting the novelty and potentialbenefits of the proposed approach for improving the quality of user feedback andenhancing the reputation of software products.