Automated tourism knowledge graph and intent generation from audio content extracted from videos, by utilizing NLP

Abstract

Generating a knowledge graph for a chatbot is a time-consuming exercise which needs the help of an expert relevant to the field. This thesis presents our approach to synthesizes the creation of a knowledge graph and intents for a chatbot. Currently, the creation of a knowledge graph and intents for a chatbot is a tedious process and this process does not extract data from videos. Developing a chatbot also requires the support of experienced software engineers.

This platform allows a user to build a customized chatbot according to a specific requirement in any field, without the intervention of experts. It also allows for the seamless development of a comprehensive knowledge graph from the video content through a simple and less tedious approach. The platform uses Natural Language Processing (NLP) machine learning models such as Naive Bayes and Logistic Regression and grammar correction techniques to supplement the experience of the users.

The working process of this proposed system is Knowledge Extraction and generating the Knowledge Base. The user inserts keywords related to the chatbot’s domain as the first step of the process. The system retrieves the search results from YouTube. Finally, NLP will be used to retrieve data contained in videos to create a preliminary knowledge graph and intents for a chatbot. A scheduler is then activated automatically from time to time to update the knowledge graph and intents. The knowledge graph and intents generated have been tested on a chatbot created using the Rasa framework, with the chatbot giving the correct answers when questioned by a user.