I have been trying to use ontological bases in my chatbot to introduce interactivity which can take the conversation forward. What I have till now : Any user query is parsed by an NLP engine to classify if the intent is any one of the preset intents. Some of these preset intents are greetings, compliments, tasks assigned in the Talentify for Business app amongst a few. If none of the intents are matched then the user query is passed in sequence to various search engines and their web results are scraped to get a metadata response generated by the search engine, which usually is a representation of the internal knowledge graph of the search engine implementation. If none of the search engines can identify that query, then the query is passed to a knowledge engine called wolfram alpha which in most of the cases can give response to even very complex queries like "what is the distance between Chennai and Bangalore in kilometres" If even that fails then a default random...
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