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  2. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    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.

  3. Wordtune - Wikipedia

    en.wikipedia.org/wiki/Wordtune

    Wordtune is an AI powered reading and writing companion capable of fixing grammatical errors, understanding context and meaning, suggesting paraphrases or alternative writing tones, and generating written text based on context. [1] [2] [3] It is developed by the Israeli AI company AI21 Labs. [4] [5] [6] [7]

  4. Scribd - Wikipedia

    en.wikipedia.org/wiki/Scribd

    Adler wanted to create a simple way to publish and share written content online. [5] He co-founded Scribd with Jared Friedman and attended the inaugural class of Y Combinator in the summer of 2006. [6] There, Scribd received its initial $120,000 in seed funding and then launched in a San Francisco apartment in March 2007. [7]

  5. Scrivener (software) - Wikipedia

    en.wikipedia.org/wiki/Scrivener_(software)

    Scrivener (/ ˈ s k r ɪ v ən ər /) is a word-processing program and outliner designed for writers. [5] Scrivener provides a management system for documents, notes and metadata.This allows the user to organize notes, concepts, research, and whole documents for easy access and reference (documents including rich text, images, PDF, audio, video, and web pages).

  6. Wikipedia:Artificial intelligence - Wikipedia

    en.wikipedia.org/wiki/Wikipedia:Artificial...

    This may be directly involved with creation of text content, or in support roles related to evaluating article quality, adding metadata, or generating images. As with any machine-generated content, care must be used when employing AI at scale or in applying it where the community consensus is to exercise more caution.

  7. Multi-document summarization - Wikipedia

    en.wikipedia.org/wiki/Multi-document_summarization

    Multi-document summarization is an automatic procedure aimed at extraction of information from multiple texts written about the same topic. The resulting summary report allows individual users, such as professional information consumers, to quickly familiarize themselves with information contained in a large cluster of documents.

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