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  2. 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.

  3. 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

  4. Information extraction - Wikipedia

    en.wikipedia.org/wiki/Information_extraction

    An example, consider a group of newswire articles on Latin American terrorism with each article presumed to be based upon one or more terroristic acts. We also define for any given IE task a template, which is a(or a set of) case frame(s) to hold the information contained in a single document.

  5. New AI tools can record your medical appointment or draft a ...

    www.aol.com/news/ai-tools-record-medical...

    In one Colorado health system, such messages contain a sentence disclosing they were automatically generated. But doctors can delete that line. “It sounded exactly like him.

  6. Intelligent word recognition - Wikipedia

    en.wikipedia.org/wiki/Intelligent_word_recognition

    IWR also eliminates a large percentage of the manual data entry of handwritten documents that, in the past, could only be keyed by a human, creating an automated workflow. When cursive handwriting is in play, for each word analyzed, the system breaks down the words into a sequence of graphemes, or subparts of letters. These various curves ...

  7. Sentiment analysis - Wikipedia

    en.wikipedia.org/wiki/Sentiment_analysis

    This work is at the document level. One can also classify a document's polarity on a multi-way scale, which was attempted by Pang [8] and Snyder [9] among others: Pang and Lee [8] expanded the basic task of classifying a movie review as either positive or negative to predict star ratings on either a 3- or a 4-star scale, while Snyder [9 ...