Overview
Amazon Comprehend is a natural language processing (NLP) service that uses machine learning to find insights and relationships in text. It solves several problems related to understanding and analyzing large amounts of text data. Here are some of the key problems it addresses:
Text Analysis: Amazon Comprehend can identify the language of the text, extract key phrases, places, people, brands, or events, understand how positive or negative the text is, analyze text using tokenization and parts of speech, and automatically organize a collection of text files by topic.
Sentiment Analysis: It can determine the sentiment of text documents (like social media posts, customer reviews, etc.) as positive, negative, neutral, or mixed. This is particularly useful for businesses that want to understand customer sentiment towards their products or services.
Entity Recognition: Amazon Comprehend can identify different types of entities in the text, such as names of individuals, organizations, locations, dates, quantities, and more. This can be useful in a variety of use cases, including document analysis, voice of customer analysis, and content personalization.
Language Detection: It can identify the dominant language in a text document, which can be useful in routing customer requests to the appropriate customer service representative or for content localization.
Syntax Analysis: Amazon Comprehend can analyze text to understand the role of each word in a sentence, helping to determine the meaning of the sentence.
Document Classification: It can automatically classify documents into predefined categories, helping businesses to organize and categorize their documents effectively.
By solving these problems, Amazon Comprehend helps businesses to understand their customers better, improve their products and services, and make more informed decisions.
Key Features & Functionality