Exploring the Power of Natural Language Processing in Business: 5 practical examples
How Natural Language Processing is used in business
What is Natural Language Processing (NLP)? — Real World Examples
Natural language processing has been gaining significant attention over the years, and it's all for the right reasons. To put it simply, NLP is a field that aims at getting machines to communicate or interact with humans in our language. You might already be familiar with applications like autocorrect, spell checks, and search engines. They make use of NLP.
To give you a better idea of how impactful NLP can be, here are eight exemplary applications that may pique your interest. And if your business deals with massive volumes of text data, hiring a capable NLP consultant like Fast Data Science would indeed be a wise move.
8 Insightful Applications of Natural Language Processing in Business
1. Text Information Extraction
Large volumes of textual data can be difficult to handle, even for businesses. For instance, pharmaceutical firms need to go through large piles of regulatory and clinical trial documents. Sifting through these to find relevant information is an uphill task.
Here’s where NLP helps. With natural language processing tech, these tedious tasks can be automated, saving you time and resources.
2. Spell Check in Forms
With almost everyone owning a smart gadget, typing errors have become very common. NLP rectifies these by using neural networks that correct homonyms and even adapt to languages with complex morphology.
3. Information Retrieval and Answering Queries
This powerful application enables NLP to retrieve information and answer queries in a context-aware manner. These capabilities stem from the use of transformer models or sophisticated neural networks.
4. Converting Between UK and US English Spelling
Algorithms with NLP readily convert or normalise text documents’ spelling between UK or US English to maintain uniformity and accuracy. I was encountering this problem so often that I made my own library for US-UK spelling conversions and put it on Pypi for others to use: https://pypi.org/project/localspelling/ (install with pip install localspelling).
5. Language Identification
NLP algorithms can swiftly identify the language of a given text. This is done through either identifying unique stopwords of different languages or pattern recognition in the text.
The above examples are just a glimpse of what NLP can achieve. Fast Data Science, a highly experienced NLP consulting firm, will help you leverage NLP’s power for your business.
To learn more about the real-world applications of natural language processing, visit this page. You may also like my blog post about Natural Language Processing Tools: The Latest Trends and Developments.
If you or your business require NLP consultation or services, feel free to get in touch with us. We are always ready to help.
