Workings of a Chatbot: Machine Learning and NLP
“The theory and development of computer systems able to perform tasks normally requiring human intelligence, such as visual perception, speech recognition, decision-making, and translation between languages.”
Oxford Dictionary’s definition of AI
Chatbots are fascinating. Through the power of Artificial Intelligence, they have taken the world by storm with their human-like behaviour and problem-solving capabilities. Intelligence by definition is the ability to acquire and apply knowledge and skills. But, you might be wondering how does a chatbot actually recognise and learn from what it is being told? This is done through a combination of Natural Language Processing (NLP) and Machine Learning.
Natural Language Processing (NLP)
NLP is the component which helps chatbots understand the language, sentiment and context that we as people use almost instinctively when conversing. Through NLP, computers can interpret the vast and complicated human language and process it effectively in order to provide the appropriate response. Unlike a search engine, NLP focuses on more than just one targeted keyword, but rather it uses sentence structure, patterns and context to identify intent.
Once that intent is established, the bot can then provide the relevant action or response. Bots are usually pre-programmed with a number of specific intents related to the purpose and goals that the chatbot was created for. Given that there are various ways to ask the same question, it is through interacting and facing numerous conversations that a chatbot will eventually learn how to recognise these questions and reply with human-like consistency. This is where machine learning comes into play.
Where NLP helps the chatbot interpret and recognise what is being said, machine learning gives it the ability to record and learn from conversations. The machine “learns” through the analysis and recordings of patterns and use of algorithms. The chatbot uses these algorithms to assess multiple conversations and their impact over time. While this is happening the bot is constantly learning and growing with the results. This is how a chatbot becomes exponentially efficient in meeting user expectations.
Though chatbots still have to be monitored and maintained from time to time, machine learning gives the chatbot the ability to independently grow and improve without constant programming and supervision. This, in turn, makes a chatbot an asset to have that will provide better and better results as it develops with time.
From the early invention of the clock to modern autonomous cars, humanity has always aspired and sought to create machines that work independently and make our lives easier. Chatbots are doing just that for a number of industries. If you’d like to find out more how ebo can be an indispensable asset to have for your business, contact us today to schedule a demo.
Published September 2017
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