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The Importance of Intents and Context in Chatbots

Humans are good in conversations, because they can understand the intent of any statement, also the context in which the statement is placed.

Today’s chatbots are equipped with intent recognition engine. Using machine learning, statements are mapped to intents, and the chabot can handle infinite variations of the same statement. Why is this technique useful? The following example cites this:

Consider you want to ask the contact details of a company. Now every person will ask it in a different way. Following are few of the variations that are possible:

  • Please share your contact details
  • Where do you reside
  • Where are you located
  • Can you share your location
  • Please provide your address
Now the intent of the above questions is “asking address”. So a answer can be mapped to the intent, rather than all the questions. This helps in managing the chatbot easy.

Before intent recognition came into existence, most popular being, recently acquired by Facebook, earlier chatbots were purely based on Artificial Intelligence Markup Language (AIML). AIML was purely a question-answering template. A lot of manual intervention was needed to make the chatbot sound intelligent. Based on pure pattern matching in the questions, it had a basic flaw - it was not able to handle the infinite variations in a question.

Context identification is still a difficult problem, and one of the core problems the AI community is working on. It is argued that, once this problem is solved, AI might have reached the Artificial General Intelligence level, which means the chatbot will be able to match up to human capabilities.

Intent recognition engines such as, Watson Conversation and Microsoft Bot Framework have changed the chatbot scene. Today it is very easy for anyone to develop a chatbot by training it on various intents. Context identification is handled by such engines using a manual process of creating stories or dialogues. A person who is training the chatbot has to write various dialogue flows to make the chatbot understand context.

We at Cere Labs, a Mumbai based startup in Artificial Intelligence, have developed successful chatbots that uses intent recognition. After training the chatbots on various intents, the chatbots have started sounding intelligent, and are able to answer most of the user’s questions. Look into this space as we elaborate on the process of intent recognition.

Let your users talk to your website by using chatbots. You can talk to our chatbot on Cere Lab’s facebook page -


  1. We can build your chatbot from scratch, instilling the best practices of a conversational user experience. From setting up a chatbot on your Facebook Page, to implementing analytics so you can understand how users are becoming customers. Malaysia chatbots


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