Intelligent bots use artificial intelligence to accomplish specific tasks by identifying user intent from text or voice conversations. They use a process called entity extraction, leveraging natural language understanding to extract key pieces of information. Most of the intelligent chatbots today are powered by natural language processing and machine learning. This enables them to get smarter and identify the key elements of a conversation to provide smart replies. Some of the most common places these chatbots are used are answering questions, playing music or making reservations.
Regardless of whether a chatbot is transactional or conversational, it needs to have the ability to recognize what the user wants – essentially it needs to understand user intent. Bots need to be able to detect bits of information from the user input and convert it into machine readable format. This process is known as entity extraction. For example, when you call a chatbot to make a reservation, the bot follows a number of steps to complete the process. Firstly, it uses intent recognition process to determine what the user wants and what it needs to ask you for getting the details it wants. It uses entity extraction to provide the time and seating preferences to the reservation management system.
To accomplish this there are two methods a chatbot uses. First is the rules based system that uses a set of rules (typically Boolean) to talk to users and detect the intent and extract entities. Second is the natural language understanding that uses machine learning techniques to determine a user intent.
Rule based systems
These systems use regular expressions or other pattern recognition techniques. Certain advanced systems might measure the frequency of the words and their position in a sentence or perform sentiment analysis so that user intent can be better determined.
Rules based systems are simplistic in nature, and users are required to restrict their responses to a limited set of phrases or keywords.
Natural Language Understanding
NLU – Natural Language Understanding is a branch of Natural Language Processing (NLP). It helps machines to understand and interpret human language. The bot is trained to understand certain phrases. The bot then learns to associate certain inputs with the appropriate intent. The deep learning algorithm breaks down the phrase into smaller parts and applies statistical techniques to guess the intent. It them comes up with an estimated intent and that’s why the human feedback during the training phase is important
Machine learning techniques are improving by the day and chatbots are becoming more intelligent. It’s only a matter of time when these chatbots will gain enough accuracy to create human like conversations!
So, does your business need an intelligent chatbot?
The answer is – eventually yes. It will be able to handle your first line of communication with customers either in customer service or in customer support. It will also be able to handle simple online sales, reservations and such simple business processes.
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