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  2. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    An example of a summarization problem is document summarization, which attempts to automatically produce an abstract from a given document. Sometimes one might be interested in generating a summary from a single source document, while others can use multiple source documents (for example, a cluster of articles on the

  3. Wordtune - Wikipedia

    en.wikipedia.org/wiki/Wordtune

    Users can use the tool to paraphrase text being composed on services like Gmail, Google Docs, Facebook, Twitter, and LinkedIn. [ 10 ] On November 14, 2021, AI21 released Wordtune Read — an AI-powered Chrome extension and standalone app designed to process large amounts of written text from websites, documents, or YouTube videos, and summarize ...

  4. Help:WordToWiki - Wikipedia

    en.wikipedia.org/wiki/Help:WordToWiki

    Microsoft released an add-in that allows you to save your Microsoft Office Word 2007 or above documents straight into MediaWiki. Download the "Microsoft Office Word Add-in For MediaWiki" from Microsoft Download Center, and install it. Save the document as "MediaWiki (*.txt)" file type. Copy the text from the (*.txt) file into your Wiki page

  5. Word2vec - Wikipedia

    en.wikipedia.org/wiki/Word2vec

    An extension of word vectors for creating a dense vector representation of unstructured radiology reports has been proposed by Banerjee et al. [23] One of the biggest challenges with Word2vec is how to handle unknown or out-of-vocabulary (OOV) words and morphologically similar words. If the Word2vec model has not encountered a particular word ...

  6. Facebook is reportedly developing AI to summarize news - AOL

    www.aol.com/facebook-reportedly-developing-ai...

    According to a report from BuzzFeed News, Facebook is testing an AI-powered tool called TL;DR (Too Long; Didn’t Read) to summarize news pieces, so you don’t even have to click through to read ...

  7. Document AI - Wikipedia

    en.wikipedia.org/wiki/Document_ai

    Data is typically distinguished in spatial data and time-series data, the former can be things like images, maps, graphs, etc. the latter can be e.g. stock-price or a voice recording. Document AI combines text data, which has a time dimension, with other types of data, such as the position of an address in a business letter, which is spatial.

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