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Ever found yourself frustrated with a chatbot’s inability to comprehend your messages? Ever wondered about the underlying cause? Well, the answer is quite straightforward—it boils down to the absence or deficiency of Natural Language Processing, commonly referred to as NLP. So, what exactly is Natural Language Processing? Why is it essential, and where does it […]
Updated 30 September 2024
VP - Delivery at Appventurez
Ever found yourself frustrated with a chatbot’s inability to comprehend your messages? Ever wondered about the underlying cause? Well, the answer is quite straightforward—it boils down to the absence or deficiency of Natural Language Processing, commonly referred to as NLP.
So, what exactly is Natural Language Processing? Why is it essential, and where does it find application?
Let’s break down NLP in simple terms and elucidate the entire process through a natural language processing tutorial. Every expression, whether written or spoken, contains information. This information encompasses words, tone, and topics, representing a form of data from which value can be extracted. This wealth of information provides insights into human behavior, enabling us to understand others.
However, a challenge arises due to the overwhelming volume of information, making it impractical for humans to track everything. Let’s clarify this.
An individual can generate a multitude of sentences and declarative statements, each laden with its complexities. Manually managing and analyzing this data is beyond human capacity, given the sheer number of declarations.
This data, collected from conversations, declarations, social media activities, etc., is unstructured and challenging to fit into relational databases representing the world. The result is a labyrinth of information that is intricate and cumbersome to comprehend. Enter the game-changing solution—Natural Language Processing.
This revolutionary technology alleviates the burden on humans to manually interpret speech or text data. Cognitive methods have streamlined the process, making it easier to discern the meaning of data and detect speech patterns.
Crucially, the efficacy of NLP hinges on Artificial Intelligence, Machine Learning, and Deep Learning, which collectively facilitate the entire NLP process. In essence, NLP has evolved into a comprehensive natural language processing solution, sparing individuals the manual efforts and ushering in a new era of understanding and interpreting vast datasets.
This is just an introduction to natural language processing, there is so much more that we must be aware of. Now, let us understand it in a technical way in the natural language processing tutorial.
NLP is a sub-category of artificial intelligence, information engineering, computer science, and linguistics that helps machines understand human language. It helps in analyzing the data that humans refrain from doing but can be of great potential.In simple terms, NLP helps to understand plenty of data and analyze it to make it easy for computers to communicate with humans using NLP machine learning, deep learning, and AI technologies.Let us give you a brief about the history of NLP. In the 1950s, the first theory about NLP came up in the article “Computing Machinery and Intelligence” by Alan Turing which showcases the criterion of intelligence around the Turing test.However, in 1954, the automatic translation was done as a Georgetown experiment that translated sentences from Russian to English. With this, NLP gained popularity, and slowly new researches were added to it including statistical machine transactions in the 1980s, and so on.
In the present time, NLP is growing at a rapid rate with the increase in computation power and enhancement in data access. This allows practitioners to achieve desirable results in sectors including human resources, finance, media, healthcare, and so on.
We are living in a time where companies’ motive is to improve the user experience at every step. They are not leaving a single stone unturned to evolve the experience of customers ensuring to be a step ahead of their competitors.Brands are well-advanced to work around AI-assistant channels, computational linguistics, retrieving data from websites or documents, and so on. Customers and businesses are now embracing NLP and cloud computing to be more accurate, automate services, search through FAQs, and even have conversations with customers using Chatbot.Customers can have instant answers to their queries whereas companies can focus on higher-value data without manual help. The agent side for the companies is easily covered with NLP that work as virtual assistants (mostly) that use the data to interact efficiently with users.The data analysis with NLP has a lot of potential to grow that was earlier hidden in the text troves that use NLP machine learning algorithms for analysis. With a brief explanation of the working, let us get to the pros and cons of NLP as per its approaches – machine learning and grammar engineering (we will briefly talk about them later in the blog).
With this said, let us dive into the deep of the NLP world with its working and other major aspects that one must be aware of.
Just like other platforms, NLP has its own sets of challenges that are explained below:
If we talk about the present time, NLP is becoming an integral part of the technology, especially with machine learning, deep learning, and artificial intelligence solutions as its core factor. By learning from them, the companies are now able to interact with the customers easily and make a difference in the market.Natural language processing (NLP) techniques are majorly used by companies to enhance their customer interactions, and interaction with data, and reach the desired outcome. The processes are becoming better and faster with the help of natural language processing (NLP) techniques.This is bringing in a new phase of communication with the machines, companies are now easily making decisions and becoming more flexible. It is a paradigm shift in technology in the market while maintaining customer sentiments in mind.Organizations are going to become smarter with the NLP and mainstreaming the intelligence in a manner that can be beneficial for them. The integration of the NLP with other technologies is going to change the way users work with machines including computers and smartphones.When it comes to the NLP then the sky’s the limit and the future is going to shine brighter with advancements.
With this said, if you have any queries about the NLP then drop a comment below, or if you want to develop the app using this technology then feel free to contact us.
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Expert in the Communications and Enterprise Software Development domain, Omji Mehrotra co-founded Appventurez and took the role of VP of Delivery. He specializes in React Native mobile app development and has worked on end-to-end development platforms for various industry sectors.
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