The Hotel Sentiment Analysis project was developed as a learning initiative to explore advanced data analytics and natural language processing. By parsing and interpreting customer reviews, I aimed to quantify sentiments and visualize trends, providing a dashboard that helps in strategic decision-making for hotel managers.
This tool streamlines the review analysis process, enabling efficient and effective management of customer feedback.
Addressing the need for automated analysis of voluminous hotel reviews to reduce the manual effort and increase responsiveness to guest feedback.
To enhance my understanding of AI and machine learning through a practical, impactful project that offers real-world utility in the hospitality industry.
Integrating complex AI models to interpret nuanced human emotions presented in guest reviews, and ensuring the system's adaptability to diverse feedback.
Successfully developing an application that not only enhances my skills but also serves as a prototype demonstrating how AI can be leveraged to improve service quality in hotels.