About this Collection:
Text Analysis APIs
About text analysis APIs
Text Analysis APIs streamlines the data mining process for developers and businesses so that they can quickly classify data from a variety of sources.
What is a text analysis API?
A text analysis application programming interface (API) enables communication between devices. The code contains documentation that defines how implementations called function calls are carried out. In essence, the documentation tells the API what to do. More specifically, the API looks for information in a group of text from one or more sources. It then analyzes the content and then categorizes the data.
Text analytics APIs return statistical tables or graphs, which is slightly different from an API for text analysis.
How does a Text Analysis API work?
These APIs are powered by artificial intelligence (AI). The machine learning technology of Natural Language Processing (NLP) makes it possible for APIs to extract unstructured data automatically. Two terms that are used interchangeably with text analysis are text mining and text extraction. All three have the same meaning.
Classifying unstructured text is the main function of a text analysis API. It does this by assigning categories or preset tags to content. For example, an API might classify the phrase, “It fit my budget!” under “Price.”
Who is text analysis APIs for?
These coding tools are for API users and developers who want to create applications that classify and automatically categorize text from a variety of sources. The sources could be from customer feedback, social media posts, emails, surveys, and others.
Why are APIs like this important?
APIs for text mining enables businesses to recognize the intent of customer feedback, and as a result, they provide a useful way to improve customer service.
Chatbots are good examples of text mining too. An API can classify the text for support and automatically route the customer to the appropriate department.
APIs for text extraction may use sentiment analysis to recognize how text conveys emotion. Businesses bolster their brand by properly handling negative complaints.
What can you expect from this kind of API?
Users and developers can expect accurate text extraction and coding flexibility. Businesses benefit by quickly being able to flag certain tickets, reviews, or social media comments.
Are there examples of free APIs like these?
Open-source libraries such as Python’s NumPy and SciPy are available online. Twinword Text Analysis Bundle API Documentation and its Sentiment Analysis API Documentation are two freemium APIs to try out as well.
Best Text Analysis APIs
- Text Analysis
- Adaptive Text Summarization
- Lingua Robot
- Text Clustering
- Images to Text
- Topic Tagging
Text Analysis API SDKs
All text analysis APIs are supported and made available in multiple developer programming languages and SDKs including:
- Java (Android)
- C# (.NET)
Just select your preference from any API endpoints page.
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