Chatbots are making a major wave in today’s dig- itally empowered business and technology world. Furthermore, chatbot development has become in demand due to its ability to make conversations more contextual while delivering better information and enhanced user encounters. The fundamental algorithms of natural language understanding (NLU) components of chatbot have already been subjected to a significant amount of research. In the present paper, we are focusing on developing a retrieval based conversational bot. The developed chatbot supports users in finding answers to their questions on a specific domain. To comprehend user intents, we have used machine learning methods for intent classification and natural language understanding. The system will look for a similarity between the tokens of the query and respond to the user accordingly. We have proposed a placeholder concept that can handle linked data and will contribute to the NLU component’s robustness

Natural Language Understanding, Intent clas- sification, Retrieval Based Chatbot, Domain classification, Place- holder Concept, Python.