Natural Language Processing (NLP) based Chatbots
Natural Language Processing (NLP)
Natural Language Processing, also known as NLP, is an area of computer science and artificial intelligence concerned with the interactions between computers and human (natural) languages, in particular how to program computers to fruitfully process large amounts of natural language data.
NLP enables the computer to acquire meaning from inputs given by users. It is a branch of informatics, mathematical linguistics, machine learning, and artificial intelligence.
An NLP based chatbot is a computer program or artificial intelligence that communicates with a customer via textual or sound methods.
Various NLP engines available in the market are Google’s Dialogflow, Wit.ai (Facebook), Watson Conversation Service (IBM), Lex (Amazon), and more.
Chatbots
Chatbots are applications that imitate human conversations for solving various tasks.
According to Oxford Dictionaries, a chatbot is
“A computer program designed to simulate conversation with human users, especially over the Internet.”
Type of Chatbots
Ready-made Solutions Chatbot
This chatbot allows user to make chatbot by themself. This is a popular solution for those who do not require complex and sophisticated technical solutions.
Pros of Ready-made Solutions
· Fast and Simple: Provide ready-made tools to the user to build a chatbot, who does not have resources to write the code.
· Build-in Integrations: Most ready-made platforms provide built-in integrations for the chatbot such messaging platforms like Messenger, Telegram, Skype, as well as third-party services like payment getaways.
· Budget-friendly Prices: Many chatbot-building platforms are budget-friendly or are of free charge for usage.
Cons of Ready-made Solutions
· Poor Functionality: Ready-made tools can only provide the chatbot with a few basic features and simple logic.
· Hard to Customize: If the user wants to add new features or extend the functionality of the chatbot, this may be difficult due to the restrictions in the functionality of ready-made tools.
Custom SolutionsChatbot
The user can create sophisticated chatbots with different API integrations. They can create a solution with custom logic and a set of features that ideally meet their business needs.
Pros of Custom Development
· Customizable: With custom development, the user can make a complex and unique chatbot using NLP. There will be no restrictions on the number of functionalities they want to add.
· Expertise: The user can choose a team that has expertise in particular technologies. The developers with expertise in chatbots will be able to tailor the chatbot software according to needs.
· Easy Testing & Maintenance: When the user chooses custom development for their chatbot, they have to be sure that the team will not only develop but test and maintain the chatbot in the future. This approach helps to ensure that the chatbot will be bug-free and will work properly even after further technical upgrades.
Cons of Custom Development
· Time Consuming: The development of a customized chatbot may take a long time. It can vary from a few hours to several weeks.
· Costly: Different features are used in the custom development of the chatbot. These features can be of different costs. Thus, the overall cost of the chatbot increases.
Best Approach for NLP based Chatbots
The best approach towards NLP is using Machine Learning and Fundamental Meaning for maximizing the outcomes. They together help to make efficient NLP based chatbots.
· Machine Language is used to train the bots, which leads it to continuous learning for Natural Language Understanding (NLU) and Natural Language Generation (NLG).
· Fundamental Meaning is an approach to NLP that’s helps understanding words themselves.
Working of an NLP Chatbot
- For example, you want to purchase something, and you decide to use a chatbot. You type in your request.
- When you send a message to the chatbot, asking to purchase something, the chatbot sends the plain text to the NLP engine.
- At the NLP engine, the unstructured human language is converted to structured data that the computer can interpret. Thus, it uses algorithms to get meaning and context from every sentence to collect data from them. This process is called Natural Language Understanding (NLU).
- The chatbot moves the data that was collected (the intents and entities) to the decision-making engine.
- The decision-making model derives a solid decision based on previous actions and results taken.
- Then at the Natural language generator, the chatbot converts the decision data to text. This process is called Natural Language Generation (NLG). Using NLG, the message generator outputs the message. This message is displayed to the user in the form of a text or voice message.
Use of NLP Chatbot in Real-World
Royal Bank of Scotland uses NLP in their chatbots to enhance customer experience through text analysis to interpret the trends from the customer feedback in multiple forms like surveys, call center discussions, complaints, or emails. It helps them identify the root cause of the customer’s dissatisfaction and help them improve their services according to that.
Technologies required in Chatbot Development
The most popular and commonly used technologies in chatbot development are:
Python — A programming language used to build the architecture of the chatbot
Pandas — A software library is written for the Python programming language for data manipulation and analysis.
TensorFlow — A library often used for machine learning and neural network tasks.
SpaCy — An open-source software library for advanced natural language processing
Twilio — Allows software developers to programmatically make and receive phone calls, send and receive text messages, and perform other communication functions using web service APIs.
Telegram, Viber, or Hangouts APIs — Used to connect chatbot to messengers or websites
Conclusion
In recent times we have seen exponential growth in the Chatbot market and over 85% of the business companies have automated their customer support.
Chatbot helps in enhancing the business processes and elevates customer’s experience to the next level while also increasing the overall growth and profitability of the business. It provides technological advantages to stay competitive in the market, saving time, effort, and costs that further leads to increased customer satisfaction and increased engagement in your business.
