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Amazon Kendra is a highly accurate and intelligent search service that enables your users to search unstructured and structured data using natural language processing and advanced search algorithms. It returns specific answers to questions, giving users an experience that's close to interacting with a human expert. It is highly scalable and capable of meeting performance demands, tightly integrated with other AWS services such as Amazon S3 and Amazon Lex, and offers enterprise-grade security.
For information on Amazon Kendra API operations, see the API Reference documentation.
Amazon Kendra users can ask the following types of questions, or queries:
Factoid questions — Simple who, what, when, or where questions, such as Who is on duty today? or Where is the nearest service center to Seattle? Factoid questions have fact-based answers that can be returned in the form of a single word or phrase. The answer is retrieved from a FAQ or from your indexed documents.
Descriptive questions — Questions whose answer could be a sentence, passage, or an entire document. For example, How do I connect my Echo Plus to my network? or How do I get tax benefits for lower income families?.
Keyword searches — Questions where the intent and scope are not clear. For example, keynote address. As 'address' can often have several meanings, Amazon Kendra can infer the user's intent behind the search query to return relevant information aligned with the user's intended meaning. Amazon Kendra uses deep learning models to handle this kind of query.
https://docs.aws.amazon.com/kendra/latest/dg/what-is-kendra.html
