Correcting Typographical Error and Understanding User Intention in Chatbot by Combining N-Gram and Machine Learning Using Schema Matching Technique
Mikael L. Tedjopranoto, Andreas Wijaya, Levi Hanny Santoso, Derwin Suhartono · International Journal of Machine Learning and Computing · 2019
Purpose of this research is to make chatbot based system to help Small and Medium Enterprise business.Initially, we build this application only to help Small and Medium Enterprise owner to monitor their business and report.Yet, we realize that we can make our chatbot to be more effective and efficient using machine learning technique.N-gram and machine learning using schema matching are embedded to the chatbot to understand user intention and correct typographical error inside the sentences.Finally, the chatbot has been successfully achieved those objectives.It can be concluded that the chatbot can drive the users' feeling to be more convenient and help Small and Medium Enterprise owner to monitor their business.