New developments in technology have changed businesses across the world. Digitalization is gaining a lot of prominence, and to adapt to the changing standards, most companies have started doing their business online. The utility provided by various types of software online enable companies to track changes in demand and supply and in consumer trends and to project the prices of stocks with ease. Among various kinds of software and modules available, text analysis APIs are the most commonly used software by companies of all types.
However, there are quite a few people out there who have little or no clue about this software.
What is a Text Analysis API?
To understand what text analysis API means, we must first understand what an API is. API or Application Programming Interface is a module or software that acts as a link between two different programs. In simpler terms, API allows two independent programs to communicate with each other, thus allowing them to work together, and provide better utility to its users.
In case of the text analysis APIs, it is a cloud-based tool, which is used to analyze unstructured text and provide various details regarding the text. It is mostly useful in situations where you need specific information from a block of text or texts. This process of extracting specific information from the text is called text mining.
Moreover, the service also includes the Natural Language Processing NLP feature, which allows you to analyze the human language. NLP is an AI-based feature, and therefore, it is not limited to analyzing text. It can understand the voice or audio in multiple languages, signs, expressions, language detection, etc.
How Does Text Analysis API Work?
Generally, text analysis is a process of converting raw and unstructured text into structured text that a machine can read. The reason why a text analysis function is important is the computer, being a machine, is unable to read a high-level language like English. As we know, a computer reads data in a binary form, also referred to as zeros and ones. It is required to convert a high-level language into machine language, thus making it easier for the computer to go through, and compare text, which in turn provides us with valuable information.
With the help of text analytics APIs, this can be easily achieved as they are able to integrate with any app or website. As we have mentioned above, the main job of an API is to act as a communication link between two apps or programs, thus making the text analysis API a valuable tool. It analyzes the text and provides the user with valuable data, which can be converted into a report.
Various Features of Text Analytics API
With the help of machine learning technology, the NLP API tools are able to do a lot more than just text mining and text classification. Some of the most useful features that come with text analysis APIs are:
- Extraction of Key Phrases: A person can use text analysis APIs to extractcertain important or key phrases from a block of text. This feature is especially useful in cases where a business needs to find the overall opinion of their customers. However, it is not practical to read through billions of comments and reviews and find the customers’ opinion. At the same time, the business cannot neglect its customers’ suggestions. This is where key phrase extraction feature comes in. It lets the business owners find out the overall opinion of the customer base by recognizing certain key words or phrases.
- Entity Recognition: It is a process of categorizing named entities into categories pre-defined by the user. In other words, the tools label certain entities such as names of places, people, currency, organization, etc. If the entity is a commonly used entity or a famous one, the user can even link a URL that provides more information about the entity.
- Language Detection Feature: The language detection feature is not a revolutionary feature that this tool has, and there are countless alternatives. Nevertheless, it is still a very useful feature to have on an API. This tool becomes very useful if there are a number of random texts and the languages are not flagged. This is a common situation while managing a content repository, where a lot of documents and texts get stored. By integrating the text analysis API with your repository, you will be able to find and specify the language of each and every text. Moreover, the tool has the ability to recognize a wide range of dialects, languages, and slangs.
- Opinion Mining: With improvements in AI technology, all these tools mentioned have become very powerful and effective. This can be seen in an opinion mining feature. Just like the key phrase, extraction feature, the opinion mining feature also searches for certain phrases and analyzes it, but the major difference between the two is that the opinion miner is specifically made and optimized to analyze the customer opinion from their comments and reviews.
This feature, scans for certain words and from them it understands whether the comment is neutral, negative, or positive. The opinion mining can be done in using different aspects of the text. For example, it can use 1- or 5-star reviews to gauge the sentiment, or it can use various words such as the bad, good or amazing to classify the opinion. These are just some of the most prominent features that come along with text analysis APIs. There are still other features that make them an easy-to-use solution. However, this is not the final form of the tool because the AI industry is constantly growing, and in the near future, there will be an optimized way for the text and entity extraction, which will change the e-commerce field drastically.