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Abstractive summarization methods generate new text that did not exist in the original text. [12] This has been applied mainly for text. Abstractive methods build an internal semantic representation of the original content (often called a language model), and then use this representation to create a summary that is closer to what a human might express.
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Perplexity AI is a conversational search engine that uses large language models (LLMs) to answer queries using sources from the web and cites links within the text response. [ 3 ] [ 4 ] Its developer, Perplexity AI, Inc., is based in San Francisco, California .
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In text retrieval, full-text search refers to techniques for searching a single computer-stored document or a collection in a full-text database. Full-text search is distinguished from searches based on metadata or on parts of the original texts represented in databases (such as titles, abstracts, selected sections, or bibliographical references).
During the late 2000s, due to the influence of computer storage and retrieval systems such as the Internet, some scientific publications, primarily those published by Elsevier, started including graphical abstracts alongside the text abstracts. [27] The graphic is intended to summarize or be an exemplar for the main thrust of the article.
Screenshot of performing "Find as you type" in Mozilla Firefox. "ency" was being typed and the first matched text was highlighted in green.. In computing, incremental search, also known as hot search, incremental find or real-time suggestions, is a user interface interaction method to progressively search for and filter through text.
Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words.
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