In this evolving world, electronic devices make our daily life easier by understanding what we require. But have you ever wondered how computer systems understand human language so efficiently? The answer is today's topic of the blog - NLP. NLP stands for natural language processing, a subset of artificial intelligence that involves making the devices understand human commands and mimic human actions. And in this blog, we'll be seeing what is natural language processing, applications of NLP, and much more. Let's start the introduction to natural language processing.
What Is NLP?
The amount of speech and text data that organizations now have comes from various communication channels, including messages, emails, social media newsfeeds, audio, video recordings, and more. Using NLP software, businesses instantly scan this data, examine the content's intent or emotions, and react with human dialogue in real time. NLP offers both organizations and customers a range of advantages, from being used to swiftly translate an article from one language to another to creating company knowledge by running sentiment analysis on numerous reviews. Therefore, it should come as no surprise that we will see more of it in the upcoming years. Let's see some of the benefits of NLP.
- The NLP model can analyze any type of data, be it structured or unstructured.
- NLP can efficiently help in improving customer satisfaction by analyzing the available data.
- NLP helps businesses to provide better customer experience by introducing the services of chatbots.
Apart from these, there are multiple other benefits and applications of NLP, which we'll see further in the blog. Now that we know what NLP is let's see how to perform NLP.
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How To Perform NLP?
To perform the concept of NLP, there's a set of pre-determined steps that have to be followed. Let's see what those steps are:
Step1: Sentence Segmentation
The first step in the process of NLP is sentences segmentation. This involves breaking the whole paragraphs into different sentences for a better process. The idea behind this is very simple: to cut the large paragraphs into sentences for a better understanding of the emotion of the text.
Step2: Word Tokenization
Similar to the first step, in word tokenization, the divided sentences are broken further into words. The process is also known as word segmentation. The model is ordered to do so with the help of identifying space between them.
Step3: Stemming
Stemming involves pre-processing of the data. This is done to understand the context of the data and finding the root words for the text used. For example, all the words like celebrated, celebrating, and celebrates are derived from one root word, which is "celebrate." This is done in this step of the NLP process.
Step4: Stop Word
In this process, the model eliminates all the frequently appearing words that are of no importance. In the English language, multiple words appear frequently but are of no importance, like a, an, the, is, of, etc. This step in the process is important because it'll help focus on important words by eliminating the unimportant ones. Depending upon the text, various other steps are involved in the process, like lemmatization, part-of-speech tagging, chunking, etc. You might have already guessed that there are multiple applications of NLP. Let's see some of them.
Applications Of NLP
Sentiment Analysis
The first one in the line of applications of NLP has to be this one. So, if not all, then the majority of people use social media. The audience even conversates with the brand's content. Businesses and brands can make use of social media to understand more about consumer behavior.
Companies can utilize sentiment analysis in various ways, including evaluating customer reviews, determining the feelings of their intended consumers, and assessing the sentiment surrounding their brands. In addition to commercial businesses, governments also use sentiment analysis to identify public opinion and potential dangers to the country's security.
Smart Assistants
When was the last time you asked a virtual assistant to complete a task? Not a long time back, right? The usage of smart devices has increased, and so has Siri and Alexa's involvement in our lives. Natural Language Processing makes all of this feasible. By decomposing our language into its constituent elements, such as vocabulary, and other verbal qualities, it aids the computer system in comprehending it. It not only aids in language comprehension but also in understanding meaning and emotions and responding in a human-like manner.
Predictive Text
The majority of us people have the autocorrect feature enabled on our devices, be it mobile phones or computers. The feature of autocorrect is so common and useful that we don't even have to type the full words and sentences. Not only this, the feature is capable of taking inputs and correcting itself to perform better the next time. All this is done by the concept of NLP. The concept is already making our lives so much easier.
Email Filtering
Whether you're a student, employee, or business entity, emails are part of your everyday life. We send and receive so many promotional emails from the brands. Among the work, emails are also present the mails which are nothing but scams. This problem can also be solved easily by the concept of NLP. NLP is capable of bifurcating mail under different factors like work, promotional, social, spam, etc. This feature saves up lots of time for students and professionals.
Grammar Correction
Nowadays, not only a professional writer but a regular employee or a regular student is expected to write compelling drafts, emails, invites, etc. But, after all, humans tend to make mistakes. These grammatical mistakes or spelling mistakes don't make a very good impression, and therefore, there are multiple tools available that help with the easy identification of errors. These tools use the concept of NLP to identify the error and even suggest the best possible solution.
Search Result Page
Have you ever noticed how the search engine understands your misspelled query, which is also grammatically incorrect? This is because NLP depicts what a user might be looking for. To help the typical person get what they're looking for without being a search-term whiz, search engines utilize NLP to display relevant results based on comparable search behaviors or user intent. As you type, Google, for instance, not only anticipates what common searches might be relevant to your inquiry but also looks at the big picture and understands what you're trying to convey rather than the precise search terms. As NLP in search connects the unclear question to an associated entity and produces helpful results, these are some variants you could notice while searching.
Conclusion
You must have been amused by seeing NLP's applications in your daily lives. In this blog on natural language processing, we've seen the basics of the concept, how NLP works, and, most importantly, all the applications of NLP. As mentioned earlier, NLP is a subset of artificial intelligence. If you want to learn more about the concept, browse our AI course. This was it for today's guide. See you in the next one.
