Fiction Gene : A Thai Genre Based Fiction Visualization Testimonial System

In today's digital era, fiction has become immensely popular and accessible through various channels, particularly online platforms where some content requires payment for access. Readers, therefore, seek fictions that align with their specific genre preferences to make informed reading choices. To assist in this process, we have developed a sophisticated genre-based fiction visualization testimonial system. This system leverages TF-IDF natural language processing algorithms for extracting key features and employs machine learning, specifically Naive Bayes algorithms, for accurate text classification. Implemented as a user-friendly sample website, the system visually represents fiction genres through pie charts and line charts. Our model achieved up to 91% accuracy in predicting the primary genre of fiction, thereby providing valuable support for readers in selecting fictions that best meet their preferences.