Data is growing day by day, at a speed and power never seen before, making it important to have easier ways of finding information. With this range of knowledge available, it is essential to find the right information at the right time. Text classification helps us to do exactly that.

Artificial intelligence (AI) encompasses multiple types of machine learning approaches, including computer vision, natural language processing (NLP), audio intelligence, and so on. As the name suggests, NLP is the branch of AI that centers on language and teaching computers how to understand and use it in a natural, human-like manner.

You can do a lot in the back end of a website to make it easier for customers to find products that will interest them. Manually tagging photos, putting products in multiple categories, and adding suggested alternatives are a few of the most common methods for enhancing the buyer’s experience on an e-commerce site. However, this approach has certain limitations, especially for e-commerce businesses that have large inventories or product selections that are continually updated by multiple users.

There was an experiment conducted in 2017 in London, with 100 lawyers participating in the event. The experiment involved finding accuracy in credit card irregularities in applications sent to the Finance Ombudsman. Where lawyers predicted an accuracy of 66.3%, a trained AI program achieved the accuracy of 86.6%.

Imagine a lawyer doing research for a case. Where humans may take weeks or even months to complete a particular research, AI will complete the research and provide results in a matter of seconds. Here, Artificial Intelligence will be able to perform better than experienced lawyers. 

The shift in consumer preferences and technological advancements is transforming the way people shop online. E-commerce businesses are using artificial intelligence to win over customer trust and loyalty through effective personalization. When there are plenty of products on offer, it’s highly important to showcase the right product to the right consumer.

We generally categorize everything that we come across in life, for example, we group books, music, and movies into specific genres based on their special characteristics. Digitization has helped apply the same concept to online content such as web pages, blog posts, news, e-books, and other learning content. With the immense increase in online availability of information, data needs to be found easily and analyzed faster. This is where content categorization steps in.

One of the biggest challenge faced by e-commerce companies is to bridge the gap between human thought process and autonomous technology. Natural Language Processing or NLP is a big step in this direction. It makes use of the enormous data generated every day, and organizes it properly to generate relevant search results.

Nowadays, NLP in e-commerce platforms is used for extracting attributes and improving product search. Hence consumers get to see relevant products matching their requirements when they shop online. Advanced NLP-based sorting systems enhance the online shopping experience by understanding the behavior of target customers.

In this article, we will see how to use machine learning for Text Analysis. Natural language processing is a branch of AI and machine learning that aims at extracting meaning out of text by using machine learning algorithms.

Natural Language Processing (NLP) has become more than an emerging technology. It has multiple applications in businesses today and is being widely used in various industries. NLP tools understand the meaning and context of phrases and provides automated support. They can be incorporated in any feature involving language, including online search, extract meaning, generate text, summarize a long document, or detect spam email.

Social media marketing is now crucial for businesses to remain competitive. Facebook and Twitter allow companies to spread the word about upcoming products or events and provide customer support on their platform. Instagram can be used to showcase products to over 500 million people active on the app at least once a day. Customer support on social media is preferred by about 63% of people, as compared to phone or email. Due to these platforms, businesses can engage with customers and maintain a relationship with influencers. They educate companies on how customers feel when they buy their product, ways in which they’re using them, and helps generate ideas on new business opportunities.