Natural Language Processing Usecases And Services

Natural language processing is a form of AI that’s focused on identifying, understanding, and using human languages. Written or spoken language is analyzed by computers to achieve a practical level of understanding. You may encounter NLP in many business applications on a daily basis, dealing with systems like spell checkers, search engines, translation tools, and voice assistants. Most of the top-tier versions of these technologies utilize NLP.

The following are some significant use cases of NLP applied to different industries:

• Named Entity Recognition

This includes identification of entities in a paragraph(like a person, organization, date, location, time, etc.), and further classifying them into categories according to the need..

• Part-of-speech tagging

Part-of-speech tagging is the task that involves marking up words in a sentence as nouns, verbs, adjectives, adverbs, and other descriptors.

• Summarization

Summarization is the task that includes text shortening by identifying the important parts and creating a summary

• Sentiment analysis

Sentiment analysis is the task that implies a broad range of subjective analysis to identify positive or negative feelings in a sentence, the sentiment of a customer review, judging mood via written text or voice analysis, and other similar tasks.

• Text classification

Text classification is the task that involves assigning tags/categories to text according to the content. Text classifiers can be used to structure, organize, and categorize any text.

Now that you’ve got a better understanding of NLP, check out these natural language processing applications that showcase how versatile NLP is:

Chatbots

Customer service automation offers opportunities to put NLP to work, too. Chatbots built on NLP technologies represent an opportunity to remove humans from mundane tasks and assign them to more involved queries. The e-commerce and customer support sectors have been using them with great effect for several years.

Survey Analysis

Surveys are an important way of evaluating a company’s performance. Companies conduct many surveys to get customer’s feedback on various products. This can be very useful in understanding the flaws and help companies improve their products.

Hiring and recruitment

By harnessing NLP, HR professionals can now considerably speed up candidate search by filtering out relevant resumes and crafting bias-proof and gender-neutral job descriptions. By using semantic analysis, NLP-based software sifts through the relevant synonyms to help recruiters detect candidates that meet the job requirements.

Social Media Marketing

One of the main strengths of NLP is its capacity to deal with unstructured social media data. Brand marketers can identify who the key influencers are in growth areas. Likewise, marketers can determine what types of content will resonate with social media followers. The goal is to target specific influencers with the right content to drive awareness and message diffusion.

Security Authentication

With the arrival of NLP technology, it’s possible to integrate more advanced security techniques. By using question generation, data scientists are able to build stronger security systems.

Conclusion

NLP applications are increasing at a fast pace and the technology has all it takes to accelerate customer service. NLP based software now even impacts our personal lives as well. NLP use cases provide a better and basic understanding of what this technology can do to maximize productivity, streamline operations, deliver insights and keep up with the competition.