Azman Busst
Papers
1
Total Citations
2
H-Index
1
About
Azman Busst is a researcher at the forefront of conversational AI and natural language processing, with a particular focus on enhancing human-computer interaction through intelligent error correction. His most cited work, "Typographic Error Identification and Correction in Chatbot Using N-gram Overlapping Approach" (2022), addresses a critical challenge in chatbot development: handling user input errors that disrupt seamless communication. By leveraging n-gram overlapping techniques, Busst’s research enables chatbots to more accurately detect and rectify typographical mistakes, thereby improving response reliability and user experience. This contribution is especially significant given the surging demand for AI-driven customer service solutions across the business sector. While his citation count is still growing, the practical implications of his work are substantial, offering a pathway toward more robust and user-friendly virtual agents. Busst’s research sits at the intersection of computational linguistics and applied AI, and his efforts are helping to refine the foundational technologies that power modern chatbots, making digital interactions feel more natural and error-free.
Research Focus
Key Achievements
Top Papers
- 1