This project aims to develop an automated system for extracting meaningful insights from mobile app user feedback. It addresses the challenges of analyzing unstructured and complex language in reviews. By integrating machine learning and natural language processing techniques, the project focuses on accurately performing sentiment analysis and categorizing feedback into relevant topics, providing actionable insights for app developers to enhance app quality and user satisfaction.
Security and cryptocurrency wallet use are still at the center of the issues with blockchain adoption. Seed phrase-based physical wallets…
The existing traditional e-commerce systems struggle to focus the user query to give a relevant product recommendation at the end…
“The wristGuard application employs a hybrid approach, combining deep learning models for feature extraction and stacking ensemble method for classification…
“The COVID-19 epidemic changed IT industry processes by hastening the introduction of remote work. In virtual workplaces, detecting employee engagement…
“VRoxel is an innovative procedural generation system that addresses critical challenges in creating large-scale 3D environments for VR applications. The…
Block-based programming (BBP) has proven effective in teaching programming concepts, offering a visual and more intuitive approach than traditional text-based…
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