Artificial intelligence and machine learning algorithms to transform chatbots

Artificial intelligence and machine learning algorithms to transform chatbots

The increasing technology has always been a saviour for us. Technology still provides us with solutions for existing problems. One of the answers offered by technology to a current issue is the chatbot. A chatbot is an artificial intelligence software. It helps to communicate with a user in natural language. It uses websites, message applications, mobile apps, or telephone to provide interaction.

Chatbots have influenced many marketers and many organizations. Everyone who needs interaction with a client prefers chatbots nowadays. Many brands are using these chatbots. Bots can interact with their clients very quickly. Trending technologies algorithms help to create chatbots with Machine learning algorithms. 

Machine learning algorithms

These chatbots are helping marketers to increase their sales. An increase in sales is because they provide perfect interaction with the customer. Chatbots can also help to increase profits, improve branding, and grow our business. Before, our customers used to wait for a long time to contact our customer service executive. But by using chatbots, we no more face this issue. Besides, these chatbots can also provide clients with solutions. One more advantage of the chatbot is that it works all day in a year. This advantage can help clients to use it any time in a day.

Along with Machine learning algorithms, artificial intelligence(AI) also plays a significant role in designing a chatbot. Artificial Intelligence plays an essential role in increasing chatbots efficiency. There are many advantages to using artificial intelligence. One of them is it makes the user feel that they interact with humans. The bot understands the client’s request and gives a solution. In the same way as a human being would respond to that request. Using artificial intelligence also helps us to provide our clients with answers for complex queries as well.


Besides that, chatbots usually learn from their past experiences. They analyze client queries and improve their performance. This feature of the bot helps it increase its overall interaction with the client making it more user-friendly. Further, it can also understand customer’s preferences and choices. The  Machine learning algorithms used in chatbots helps bots to gain the knowledge required during bot training. During bot training, the organizations provide all the necessary information to the bot. Exercise will increase the bot’s working efficiency.

Machine learning algorithms used in chatbots

Since chatbot use machine learning algorithms, they follow a highly complicated process whenever they ask a question. It first checks the previous chat history with the customer and then answers the present problem. Since chatbot offers solutions in this way, it became more user friendly. 

Machine learning algorithms and artificial intelligence algorithms make chatbot more user friendly. But along with them, NLP chatbot is also very important.

Suppose we use Machine learning algorithms and artificial intelligence algorithm. In that case, it only gives a good response once it understands the question or request. The first task of a bot is to understand the offer correctly. Many customers or clients use natural language to place a bid or raise a query. So the chatbot must understand the crude language. Natural Language Process(NLP) chatbots came into the picture to overcome this problem.

NLP chatbot can interact with a human more sympathetically, helping its customers stay loyal to them. These NLP systems usually use Machine learning algorithms to take the client’s input and understand what a client needs. The way to make NLP bots give better results to clients is by training the bot. We need to provide chatbots with many examples. It requires training in many scenarios. Providing this kind of activity to bots will provide more adequate results to the client. 

While providing bots training, the bot designers should make sure of some things. They should ensure that they can respond formally, making our clients stay with us. Every individual has a different style of asking questions. We ask questions in a specific manner. We also expect answers in the same way. If we get the response in the way, we ask it makes us happier. By using NLP, chatbots can understand the human mindset and reply to them in their manner. Other conversational tones like sarcasm, humor, etc. can be understood well by using NLP. NLP chatbots have their personality.

We have seen that natural language processing plays a significant role in making chatbot a better one. Let us now see how a chatbot to build a bot with natural language processing.

What are the fields of natural language processing(NLP)?

What are the fields of natural language processing(NLP)?

As seen earlier, NLP is a branch of Machine learning algorithms, artificial intelligence, mathematical linguistics, and informatics. It helps us to make our chatbot more user friendly. NLP has three core fields. They are:

  1. Natural language understanding(NLU):

The language we use to communicate in our daily lives is highly flexible. We need to perform logical operations so that it will ensure that the computer’s standard algorithms understand our day to day language.  

2. Natural language generation:

Like generating financial reports and analyzing them, the process is fully automated using natural language understanding and natural language generation.

3. Natural language interaction:

We do training of bot after completing the natural language understanding and natural language generation. Based on our requirements, we should provide training for bots.

Types of chatbots based on NLP

Although there are many types of chatbots based on different technologies, the NLP chatbots are of two kinds. They are:

  1. Scripted chatbots:
    If the customer requests something that is not pre-programmed, then these chatbots cannot respond.
  2. Artificial intelligence chatbots:
    We develop these chatbots using NLP. As mentioned before, these chatbots can learn from previous interactions and give effective responses. These chatbots communicate with customers by voice or by texting. These chatbots are being used in all places and all businesses nowadays.

What are the challenges that your chatbot is facing?

The way each and everyone speaks is different. Since chatbot is also a pre-programmed software, it gives output for the present question. If we depend on pre-programmed software, then we cannot reach our requirements. To overcome this problem, we are using NLP. In our ordinary language, the way every individual speaks is different from one another. We face many challenges like synonyms, slang, spelling, antonyms, abbreviations, accents, vomiting punctuation. 

What are the challenges that your chatbot is facing?

If a human being needs to give a response, then he or she can do it. Since we want a system to do the work, we use NLP. In NLP, we teach the system these all factors and face all the challenges while responding to the query.

Chatbots in Business: Advantage & Benefits

Chatbots in Business: Advantage & Benefits

We know that chatbot is helping us to grow our business. A bot can answer some queries. But some questions need interaction with a person to be solved. So now, let us see various examples of using a chatbot.

  • Customer service chatbot:

It helps us to tell the customers regarding the various services provided by the company. Suppose there is an accompanying website using a chatbot. In that case, we can assist people by telling them how to navigate the website. Customer service chatbot also helps to order goods and ask for services.

Chatbot in medicine can help us to fix an appointment with the doctor. It also helps to order prescriptions or to view the prices of drugs.

In tourism, it helps to find information on the price of the ticket. It also helps to find places of interest, shops, and travel packages.

  • Tickets booking:

When we are planning to book a movie ticket, sometimes we get confused. The chatbot provides suggestions for us based on our interests. If we answer some questions that the bot asks, it can give us the best recommendations.

  • In-app support:

These kinds of chatbots are more customer-friendly. They provide support to the customer 24*7. These chatbots can send notifications to the customer while they are searching for something else. 

Using chatbots helps us to get the news information which we need or look for inside our messenger. So this way, chatbot reduces our efforts to surf over the internet. It also helps us from switching over the channels to watch important news. We will again miss any information this way.

Ways to build a chatbot:

Ways to build a chatbot:

There are two methods to design a chatbot. One is a ready-made solution, and the other is custom developed.

1. Ready-made solutions:

There are some platforms available that will help you to design your chatbot. These solutions are of great help for people who do not need sophisticated chatbots. When we need an NLP chatbot, we do not have programmers to write the code.

Advantages of ready-made solutions:

  1. Fast and simple:
    It is effortless to design a chatbot using these platforms.
  2. Availability of built-in features:
    These ready-made solutions provide our chatbot with built-in messaging platforms like a telegram, messenger, etc.
  3. Economical:
    We can design bots at reasonable prices. We can create bots based on our budget.

Disadvantages of ready-made solutions:

  1. Less availability of features:
    Although there are built-in features, the ready-made solutions provide the bot with essential features and simple logic.
  2. Difficult to add new features:
    After taking the ready-made solutions chatbot, it is a complicated process to add any additional features yourself.

2. Custom chatbot development:

If one wants to create their chatbot, then that chatbot is called a custom chatbot. Using this, one can develop a sophisticated chatbot, with all the features they need for their business.

Advantages of custom chatbot development:

  1. Customization:
    By using a custom chatbot, you can create all the features you need. You can make a unique chatbot and implement complex NLP. There will be no restrictions for developing.
  2. Expertise:
    We choose a new team to develop the technology. We can select the unit based on the technology the individual knows well. Establishing a group like this will help us create or design a chatbot that we need.
  3. Testing and maintenance:
    Since we are picking our experts’ team, we can be sure that they will also test and maintain our chatbot. Suppose there are any technical issues in the future. In that case, the team will immediately solve it, helping us maintain a loyal relationship with the clients.

Disadvantages of custom chatbot development:

  1. Time:
    Since we will design it with our team of experts, it will take more time than ready-made solutions. Usually, a chatbot to develop a chatbot is a few hours to a few weeks.
  2. Cost:
    In ready-made solutions, we only pay the charges for the tool. But, we also need to pay for them in custom chatbot development since employing people to develop. So this custom chatbot is more complicated compared to ready-made solutions.
  3. Development:
    Suppose you think of developing a chatbot and do not have enough experience, that could be a problem. So we need to hire offshore people who have enough experience to create a bot.
Conclusion: This article saw a chatbot, machine learning algorithms in chatbots, NLP chatbots, and how to build NLP chatbots. An individual should keep in mind some essential points while creating a bot. You should know your customer and competitors. It will be best if you also have chatbot tested and maintained from time to time.

Published at Wed, 21 Oct 2020 06:11:15 +0000

Artificial Intelligence (AI) in Education Industry 2020 Market Growth, Size, Share, Demand, Trends …

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• Metacog
• Microsoft
• Cognizant
• Pearson
• Querium
• Nuance
• Quantum Adaptive Learning
• Carnegie Learning
• DreamBox Learning
• Third Space Learning
• Fishtree
• Century
• BridgeU
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• Elemental Path
• Cognii
• Blackboard
• Jellynote
• Luilishuo
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• Knewton

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By Type, Artificial Intelligence (AI) in Education market has been segmented into:
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• Natural Language Processing

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TOC of Artificial Intelligence (AI) in Education Market Report Includes:
Chapter 1: Market Definition and Segment by Type, End-Use & Major Regions Market Size
Chapter 2: Global Production & Consumption Market by Type and End-Use
Chapter 3: Europe Production & Consumption Market by Type and End-Use
Chapter 4: America Production & Consumption Market by Type and End-Use
Chapter 5: Asia Production & Consumption Market by Type and End-Use
Chapter 6: Oceania Production & Consumption Market by Type and End-Use
Chapter 7: Africa Production & Consumption Market by Type and End-Use
Chapter 8: Global Market Forecast by Type, End-Use and Region
Chapter 9: Company information, Sales, Cost, Margin, news etc.
Chapter 10: Market Competition by Companies and Market Concentration Ratio
Chapter 11: Market Impact by Coronavirus.
Chapter 12: Industry Summary

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Published at Wed, 21 Oct 2020 06:00:00 +0000