Entity Recognition – Fundamentals of Natural Language Processing
Entity Recognition
A company, for example, could use AI to look at articles in industry magazines to find ones that talk about their products or executives or to figure out what each article is really about.
Named entity recognition (NER) automatically finds and classifies named entities in a document. Names, organizations, locations, dates, amounts, monetary values, and percentages are entities. With named entity recognition, you can get important information from a document to determine its subject or add it to a database. It helps quickly identify names, locations, brands, monetary values, and more. Extracting a text’s main points makes it easier to sort unstructured data and find important information when working with large datasets.
Here are some noteworthy applications of named entity recognition.
Organize Tickets in Customer Support
If you are getting more and more customer service requests, you can answer them more quickly by using named entity recognition algorithms. Automate repetitive customer service tasks, like grouping customers’ questions and concerns, to save time and improve how quickly problems are solved. You can also use entity extraction to pull important information, like the names of products or serial numbers, which makes it easier to send tickets to the right agent or team to handle the problem.
Learn from Customer Feedback
Online reviews are an effective way for your clients to give you feedback about your products and business. NER systems can be used to organize all of this feedback from clients and find problems that keep coming up. For instance, you could use NER to find places that are often mentioned in negative customer feedback. This could help you focus on a certain office branch.
Content Suggestion
Many popular apps, like Netflix and YouTube, use recommendation systems to give their users the best experience possible. Many of these systems use named entity recognition as one of the best possible options, which can make suggestions based on what the user has looked for in the past. If you watch a lot of comedies on Netflix, the entity Comedy will make you more recommendations.
