Artificial Intelligence has taken the tech world by storm. Tech developers are trying their best to incorporate Artificial Intelligence (AI) in software systems for intelligent and automated execution of various processes. AI, coupled with Machine Learning, can do wonders, and it has certainly opened a whole new horizon of endless possibilities. The AI is getting so much involved in our daily lifestyle that we are now unable to recognize its applications in our lifestyle. From health to finance and space systems to tech solutions, AI is everywhere.
Natural Language Processing or Simply, NLP is also made possible because of AI. Machine Learning algorithms possess the capability of understanding the processing of information through the human brain in various situations, and then machine learning algorithms implement the technique in multiple processes. NLP is also a great application of a combination of machine learning and Artificial Intelligence, which is capable of predicting the next phrases after analyzing the words or phrases used in the context.
This ability empowers NLP algorithms to leave old-school article spinning algorithms far behind in the competition. Because these algorithms don’t incorporate AI and ML in the analysis and prediction of words. In this article, we will discuss various components and technologies used in NLP, why it is superior to outdated word spinning algorithms, companies who have implemented NLP in their products, the companies who are working to implement AI, and ML-powered NLP technology in their various word processing tools. Further discussion on the topic is written below:
Technologies Used In NLP:
As we discussed earlier, the main components used in NLP are AI and ML. Let’s take a closer look at some other technologies, frameworks, and tools used in developing NLP solutions. Some of the significant tools are listed and briefly described below:
AI:
Artificial intelligence is the capability of computer systems in various forms to analyze the situation intelligently and then reacting autonomously in a similar way as humans do according to the requirements of a particular scenario. AI is the main building block of NLP.
Machine Learning:
Machine learning is, although a sub-branch of AI, still, it is worth mentioning because NLP makes a lot of use of machine learning. Machine learning enables a computer system to learn from previous records and historical data. This enables a computer system to act accordingly by analyzing the situation and comparing it to prior happenings to understand a trend or pattern and then predict the solution.
NLTK:
The full form of NLTK is the Natural language tool kit. It is basically an open-source database consisting of Python modules with data sets and tutorials.
Genism:
It is a Python library for topic modeling and document indexing.
Intel NLP:
Intel NLP architect is another Python programming language library used for the implementation of deep learning algorithms and techniques.
Python Programming Language:
This language is an essential part of AI and, subsequently, NLP. It is used because of the availability of a wide range of libraries and its closeness to the English language.
The superiority of the NLP technique to Outdated Word Spinning Algorithms:
Old conventional word spinning algorithms treat the written content as trees of data and try to follow the word by word approach and list the words to replace them with synonyms or words with relevant meanings. This approach is good but not perfect, and almost every time, a content rephrased by such tools needs to be reviewed, and the user has to make some modifications; otherwise, it doesn’t look clinical.
Another downside of using these tools is that the end product of rephrasing tools or article re-writers doesn’t look like it is written by a human. As the algorithms used in these tools treat the content as a list or tree of words and replace each word with synonyms one by one, the writing doesn’t look in harmony with the context, and sentences don’t feel connected. Experienced language professionals would easily identify the raw paraphrased content and the original one because of the lack of connectivity between sentences and a misdirected concept of whole paraphrased content. There is a high probability that you’d get strange content with unstructured sentences and awkward words.
Whereas Natural Language Processing is far advanced, then these conventional algorithms because of AI and ML incorporation. NLP considers the whole content to be paraphrased as interconnected data. The emulated Natural Language Processing algorithms possess the capability of understanding and rewriting content automatically. It can even restructure the sentences to enhance the readability of content and make it look more connected.
NLP algorithms not only understand what every single word written in an article means but also how words written in an article, relate with each other. NLP analyzes the content fully and then looks for multiple ways to rewrite the articles on the basis of the actual meaning of the whole article. NLP algorithms are capable of rewriting whole sentence in a different voice or structure so that the sentence share nothing in common with the actual specimen or sentence. The end product is a unique content that is totally relevant to the meaning of actual content and can’t be detected as a spun article because of human-like writing.
This makes NLP far superior to the old-school conventional rewriting or word spinning algorithms.
Companies Working with NLP:
NLP is being used by Google in its multiple products. A significant example of the use of NLP in Google products is Gmail word suggestions. When a user is trying to compose an email, the user writes some words, and then Gmail starts predicting the next words or phrases, which are mostly accurate. This is a minimal example of the use of NLP, and it is being used for long in our daily work routine. This is how NLP is incorporated into our lifestyle, and most of us don’t know.
Some other companies have also used NLP for their customer services. Chatbots are being used for long to serve the purpose of customer services, but to make the user experience more comfortable, a lot of companies have used NLP to analyze the behavior of individual customers to make their bots act accordingly to keep the consumers satisfied. MasterCard has implemented NLP with AI chatbots since 2016 to serve its customers in a better way.
Many other companies are working towards implementation of NLP in various tools, Prepostseo is known for its beneficial tools related to writing, SEO, and many other things. It is also working towards the implementation of NLP in its paraphrasing tool to provide the best rewriting service autonomously.
Conclusion:
NLP is getting popular due to its amazing word processing and rewriting capabilities. This machine learning technique has seen a huge rise in its use, and a lot of users are already getting benefits from NLP without even noticing it.
The understanding and analyzing capabilities of NLP have left conventional word spinning algorithms far behind, and people also look to get the better of NLP for their paraphrasing tasks.
We have discussed the essential components of NLP, compared it with the old-school spinning techniques, and referred to some companies who are already using it or planning use it in their products. Hopefully, this information would be useful for you in getting know-how about NLP and NLP powered rephrasing. Intelligence is Life!

Author's Bio: 

Shane has been a writer for three years. He writes SEO articles for business and eLearning articles.