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2. Document AI - Wikipedia

   en.wikipedia.org/wiki/Document_ai

   Document AI. Document AI, also known as Document Intelligence, refers to a field of technology that employs machine learning (ML) techniques, such as natural language processing (NLP).[1] These techniques are used to develop computer models capable of analyzing documents in a manner akin to human review. Through NLP, computer systems are able ...

3. Perplexity AI - Wikipedia

   en.wikipedia.org/wiki/Perplexity_AI

   Perplexity's paid variant, the "Pro" mode (formerly Copilot), asks the user clarifying questions to refine queries. It enables users to upload and analyze local files, including images, alongside generating images using AI. Additionally, it provides access to an API. [6] Perplexity launched a new enterprise version of its product in April 2024. [1]

4. Applications of artificial intelligence - Wikipedia

   en.wikipedia.org/wiki/Applications_of_artificial...

   Artificial intelligence supported design of aircraft, [363] or AIDA, is used to help designers in the process of creating conceptual designs of aircraft. This program allows the designers to focus more on the design itself and less on the design process. The software also allows the user to focus less on the software tools.

5. Vector space model - Wikipedia

   en.wikipedia.org/wiki/Vector_space_model

   Vector space model. Vector space model or term vector model is an algebraic model for representing text documents (or more generally, items) as vectors such that the distance between vectors represents the relevance between the documents. It is used in information filtering, information retrieval, indexing and relevancy rankings.

6. Natural language processing - Wikipedia

   en.wikipedia.org/wiki/Natural_language_processing

   Natural language processing (NLP) is an interdisciplinary subfield of computer science and artificial intelligence.It is primarily concerned with providing computers with the ability to process data encoded in natural language and is thus closely related to information retrieval, knowledge representation and computational linguistics, a subfield of linguistics.

7. Latent semantic analysis - Wikipedia

   en.wikipedia.org/wiki/Latent_semantic_analysis

   e. Latent semantic analysis (LSA) is a technique in natural language processing, in particular distributional semantics, of analyzing relationships between a set of documents and the terms they contain by producing a set of concepts related to the documents and terms. LSA assumes that words that are close in meaning will occur in similar pieces ...