Last updated : Sep 24, 2021
Machine Learning has become the powerhouse of the individual's day to day lives. It is recreating the human's life structure from a new end. It has made digital systems more arranged for our help. This research focuses on the chatbot and machine learning and how machine learning can make a chatbot more sophisticated and human like. Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experiences and historical data with the help of some applied algorithms such as Linear Regression, Logistic Regression etc. After being trained the machine learning software does not need to program repeatedly. This research paper also focuses on what day to day tasks can be automated through the use of machine learning in future. It also focuses on about how machine learning algorithms are helping in improving customer support anywhere, anytime through a good user interface in the form of chat bots, natural language processing systems and parsers. And finally a section in this paper also discusses the idea of implementing learning capability in chatbot.
Have you ever wondered, you got a product and found some fault in that in the midnight and you want to urgently complain about it? Many people have suffered from the same situation and luckily developers have found a solution to this problem - "Chatbot". A chatbot is a computer program which creates a conversation session with its users in such a way that users find it very interesting to chat with. In simpler terms, chatbot is software whether in your computer or in mobile which pretends to be a human being and the user feels like they are conversing with a real person. Chat bots are mainly of 2 types:
flow based and AI based. Machine learning is an application of artificial intelligence that provides systems the ability to automatically learn and improve from experiences and assist people in their tasks. Now why machine learning is in demand now a day? The answer is machine learning algorithms remember the pattern of how a user reacts to a situation, and also machine reacts according to user’s choices. Machine learning uses the previous data and then makes use of the given algorithm and then uses some kind of given probability formula to solve the problem. Further in this article you will read different sections which are as follows:
Machine learning in detail,
This article's approach
Why machine learning chatbot differ from traditional bots,
Why machine learning is getting necessary for customer support chatbot,
2. Machine learning in detail: Training your machine to be intelligent
The story starts way back in 1950 when Alan Turing, a British scientist researched on "can machines think?" and the result is today when some software clears the Turing Test, then only it is considered as pure AI based software. Currently, Machine learning is a concept or application which is included under the artificial intelligence stream. Some people think it is a single algorithm or a technology, in reality it incorporates many algorithms and technologies which then require a large chunk of structured or unstructured data for its learning process. Primarily, there are 3 types of machine learning: supervised, unsupervised and reinforcement learning. Machine learning is generally abbreviated as ML. But why machine learning is getting famous in AI? Currently machine learning is used in spam detection, stock trend prediction, improving voice recognition, robotics, medicine, finance, gaming, e-commerce, IOT etc. There are many computer languages which are used to implement machine learning algorithms such as C++, Java, Scala, R, Python, Matlab, Prolog etc.
3. Chatbot: getting a human being out of a machine
Chatbot is software which is either installed in computer or your cell phone which acts a human being and the users feel as if they are conversing with a real person. Chatbot are so much engaged in people lives that it is also becoming a loner’s friend in some cases. They are capable of doing many tasks such as interacting like a real person, understanding the context of chat and completing the task as per ordered. Now a day chatbots are more commonly used for tasks such as ordering food, booking a taxi, messaging, calling, scheduling your day etc. Chatbots are basically of 2 types: one is flow based and the other is AI based. Former chatbot is programmed and then trained against a general data set, on the other hand AI based chatbots understand the context and uses some ML algorithm to respond. There are many chatbots running amongst public like Microsoft's Cortana, Apple's Siri, and Google's Google Assistant.
4. This article's idea/approach
As it is known, to learn something and remember for a long time, we need a brain, so the master mind or brain for machine learning is artificial neural network. For instance; if you ask a child about Taj Mahal, so child will give you all the details about it. So why child is able to say all these details, it is because the neurons in the brain which interprets the question and filters out the data with highest value and then scans the entire neural network to search about that question and then returns the information through speech. Another instance but related to same situation; a child hears, understands about Taj Mahal so this data will go in the neuron and will be stored in there, now the context becomes Taj Mahal and the information which is stored in different neurons are attached to this keyword or context. Whenever asked about Taj Mahal, the child will give you all details which is stored in neurons and attached to the keyword 'Taj Mahal' and registered as an index item in the conscious brain. In this manner, all the search engines in world work. Now with the help of above instances, you can understand the need of neural network. The idea is generated keeping the performance of the brain. Very basic steps involved in this idea are: i. The user submits a query to chatbot. ii. The query goes to the algorithm, and then it manipulates and tries to find out what context is being talked about in this query. iii. If it gets success in finding context then that context is passed to the index network. iv. This network has all the neurons connected to it storing the related information gets activated and most relevant information is passed on to the return statement. v. Then the result is shown to the user. vi. If context is not found then that query is saved in the database for future query handing. vii. That's how this idea works.
5. Why machine learning chatbots differ from traditional bots
As told earlier, that machine learning learns from previous experiences and as time passes it also starts predicting user's likes and choices after analyzing its decisions. Machine learning enabled chatbots improve the performance and quality of the product. Without machine learning, the chatbots are programmed as a collection of questions and answers which makes it difficult for program to answer each and every query. The developers need to cover all the situations that may occur in conversation. This approach of creating chat bot is known as static approach which may answer many questions but it cannot manage to maintain the context of the conversation which makes it little bit toytic. Without machine learning the chat bot conversation covers a very steep part of topics. On the other hand while using machine learning, the entities and contexts are created so as to understand what user wants to say, by this approach it is easy to make program more dynamic and user friendly. This type of approach is known as creating a natural language processing system. After creating a program a developer needs to train it because not everyone talks in the same way. Machine learning becomes important for chat bots in order for maintaining the context of the conversation. So with the maximum use machine learning algorithms the chat bot becomes like a real person and works as directed. After applying ML, the program become implementable in professional world where there is a huge demand of chat bot.
6. Why machine learning is getting necessary for customer support chatbot
First of all due to these automated bots the user need not to worry about the timings for registering a complaint about the product or service. In older times users used to follow some timings to complain about anything for e.g. 9-5, 10-5 etc usually in India. ML provides some amazingly unbelievable enhancements to bots like maintaining the contexts in bots which make it life like and it removes the need of a physical customer support agent and also many other unnecessary factors are removed like bribery, bias etc. It is only possible in machine learning driven chat bot to adapt new conditions, grammar, conversations and new way of talking very easily. Now it is useful because the programmer need not to code it against some new datasets repeatedly.
As the paper focused earlier that machine learning has become the powerhouse of modern programming and is simplifying day to day tasks. It is also simplifying the organization's task of customer support. Many internet based surveys showed that after introducing chat bots in place of real agents made that work more efficient and economical. We as users can hope that upcoming days are going to be good and more comfortable because of machine learning and artificial intelligence, some people oppose this statement. The future will decide whether excessive use of artificial intelligence in our lives will be good or not so good.
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