How NLP & ML Works in Paraphrasing Tools for Better Results

Table of Contents

1. What is NLP?
2. What is ML?
3. Wrapping Up

Paraphrasing tools work to quickly and efficiently restate the given text in an improved way while keeping the original meaning intact. Since this is the era of Artificial Intelligence, modern paraphrasers now using advanced AI technologies such as NLP and ML to produce better results.

But the question that arises here is how both these AI technologies work in rephrasing tools to generate better results. To get a detailed answer, you will have to continue reading this blog till the end.

What is NLP?

NLP is also known as Natural Language Processing. It is a branch of Artificial Intelligence that allows computers, robotic machines, or online tools to efficiently comprehend and interpret the human language.

In simple words, it works to understand the given text, so that the required computer or program can then generate a response accordingly. But how does it do this? Let us explain. To efficiently understand a text, NLP divides it into small pieces such as words, punctuation marks, or sometimes even syllables. This is called tokenization.

Now, let’s understand the role of Natural Language Processing in improving the working of paraphrasing tools.

How Does it Improve Paraphrasing Tools Working Mechanism for Better Results?

NLP helps AI paraphrasers to work better in multiple ways that are discussed below.

1. Determine the Language:

When a text is provided to a modern paraphrasing tool, its NLP technology becomes active to understand its language. For this, this AI technology carefully skims through the syntax of the given text.

It does not stop here, instead, NLP also scans the input text’s grammar structure. After going through both these, it will then signal the tool about the exact language.

So, when the paraphrasing tool has a strong idea about source content language, it will be mostly likely to generate accurate yet better output results.

2. Understanding Context

There is no doubt that, when it comes to paraphrasing a text, context matters a lot. Fortunately, Natural Language Processing also helps tools quickly and efficiently understand this as well. Let us explain how.

NLP carefully analyzes each word, phrase, and sentence in the given content. The main intention is to determine the relationship between them, ultimately leading to contextual understanding.

Moreover, it also tries to understand grammatical items such as nouns, verbs, adverbs, etc. to grasp a strong idea about the original meaning of the source text.

Obviously, a good version of the input text will make it a lot easier for the paraphrasing tool to generate better output results.

What is ML?

ML is the abbreviation of “Machine Learning.” Just like NLP, it is also a sub-brand of Artificial Intelligence in which machines or computer programs continuously learn from data so that they can improve their overall performance with time. In general terms, this AI technology allows online tools to perform or work like humans.

Due to this capability, ML is being used in several fields such as automation, healthcare, education, and many more.

There are two common types of machine learning:

• Supervised learning
• Unsupervised learning

Since we are talking about paraphrasing tools, most of them usually operate on Supervised learning.

How Does ML Allow Paraphrasing Tools to Produce Good Results?

There is one way through which machine learning assists paraphrasing tools in producing better output results. The way is to learn from their generated paraphrased version so that they can come up with better results next time.

Due to this reason, whenever you paraphrase the same text multiple times with an AI-powered paraphrasing tool, you will be most likely to get a better output result as compared to the previous one, all thanks to ML.

To demonstrate this, we paraphrased a paragraph with an AI tool named Editpad. The results are in the attachment below.

Now, we are going to rephrase the same text again to see how the tool produces a better result as compared to the previous one.

So, there is a clear difference in both the output results. The second version is far better than the first one. Now, we believe you will have an efficient idea of how ML helps rephrasing tools to generate good results.

Wrapping Up

Natural Language Processing and Machine Learning are two popular branches of Artificial Intelligence that are being used in modern paraphrasing tools. These are playing key roles to make the tool work better. In this blog post, we have discussed those roles in complete detail, hope you will find the given information valuable.