Chatbots have become the go-to platform for users to receive answers to their queries. They are now being used by many businesses too to provide their customers with a virtual assistant to answer their queries. But when it comes to engaging with a user in a dialogue, existing chatbots have several shortcomings, with issues such as failing to provide a meaningful response to the user, offering semantically incorrect information etc. This paper studies the working styles of existing chatbots in generating a response and then identifies their shortcomings from the viewpoint of engaging in a dialogue with a user. It then proposes a domain-specific chatbot named IntelliBot, which is a response-generating dialogue-based chatbot that uses multiple strategies to generate a response. IntelliBot was trained on two datasets, namely the Cornell movie dialogue and a custom-built insurance dataset so it has domain-specific knowledge. The performance of IntelliBot was then validated and compared with three other chatbots from the literature, namely RootyAI, ChatterBot and DeepQA. The results demonstrate IntelliBot’s superiority in engaging with the user and providing a complete answer in the insurance domain.

聊天机器人已成为用户接收其查询答案的首选平台。现在，许多企业也使用它们为客户提供虚拟助手来回答他们的查询。但是，在与用户进行对话时，现有的聊天机器人存在一些缺点，例如无法向用户提供有意义的响应，提供语义上不正确的信息等。本文研究了现有聊天机器人在生成时的工作方式响应，然后从与用户对话的角度识别其缺点。然后，它提出了一个名为IntelliBot的特定于域的聊天机器人，这是一个基于响应的，基于对话的聊天机器人，它使用多种策略来生成响应。IntelliBot接受了两个数据集的培训，即康奈尔电影对话和定制的保险数据集，因此它具有特定领域的知识。然后验证了IntelliBot的性能，并与文献中的其他三个聊天机器人RootyAI，ChatterBot和DeepQA进行了比较。结果证明了IntelliBot在与用户互动和提供保险领域完整答案方面的优势。