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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.
Public documents are free for anyone to read. Authorea also supports private writing: a document and all its attachments can be kept private, visible only to co-authors. A free account allows the user to create one free private document, with more available via a paid subscription.
Recent effort on adaptive information extraction motivates the development of IE systems that can handle different types of text, from well-structured to almost free text -where common wrappers fail- including mixed types. Such systems can exploit shallow natural language knowledge and thus can be also applied to less structured texts.
[4] [5] [6] Possible uses for Coda documents include using them as a wiki, database, or project management tool. [5] Coda has built a formula system, much like spreadsheets commonly have, but in Coda documents, formulas can be used anywhere within the document, and can link to things that aren't just cells, including other documents, calendars ...
AI-based media analysis can facilitate media search, the creation of descriptive keywords for content, content policy monitoring (such as verifying the suitability of content for a particular TV viewing time), speech to text for archival or other purposes, and the detection of logos, products or celebrity faces for ad placement.
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online.cornell.edu has been visited by 10K+ users in the past month
insighthealth.ai has been visited by 10K+ users in the past month