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  2. Template:Extract - Wikipedia

    en.wikipedia.org/wiki/Template:Extract

    This template is used on approximately 8,800 pages and changes may be widely noticed. Test changes in the template's /sandbox or /testcases subpages, or in your own user subpage . Consider discussing changes on the talk page before implementing them.

  3. Information extraction - Wikipedia

    en.wikipedia.org/wiki/Information_extraction

    Structured data is semantically well-defined data from a chosen target domain, interpreted with respect to category and context. Information extraction is the part of a greater puzzle which deals with the problem of devising automatic methods for text management, beyond its transmission, storage and display.

  4. Template:Archives - Wikipedia

    en.wikipedia.org/wiki/Template:Archives

    Box to list archived discussions on talk pages Template parameters [Edit template data] Parameter Description Type Status List of manual archives 1 list Inline list of manually maintained archives Example [[/Archive 1]], [[/Archive 2]] Content optional Demospace parameter for box demospace Demospace parameter for {{talk other}} Suggested values talk other Default talk Unknown optional Large ...

  5. Data extraction - Wikipedia

    en.wikipedia.org/wiki/Data_extraction

    Typical unstructured data sources include web pages, emails, documents, PDFs, social media, scanned text, mainframe reports, spool files, multimedia files, etc. Extracting data from these unstructured sources has grown into a considerable technical challenge, where as historically data extraction has had to deal with changes in physical hardware formats, the majority of current data extraction ...

  6. Automatic summarization - Wikipedia

    en.wikipedia.org/wiki/Automatic_summarization

    Automatic summarization is the process of shortening a set of data computationally, to create a subset (a summary) that represents the most important or relevant information within the original content. Artificial intelligence algorithms are commonly developed and employed to achieve this, specialized for different types of data.

  7. RStudio - Wikipedia

    en.wikipedia.org/wiki/RStudio

    R Markdown can be used to create dynamic reports that are automatically updated when new data become available. These reports can also be exported in various formats, including HTML, PDF, Microsoft Word, and LaTeX, with templates specific to the requirements of many scientific journals. [7] R Markdown vignettes and Jupyter notebooks make the ...

  8. Extract, transform, load - Wikipedia

    en.wikipedia.org/wiki/Extract,_transform,_load

    Most data integration tools skew towards ETL, while ELT is popular in database and data warehouse appliances. Similarly, it is possible to perform TEL (Transform, Extract, Load) where data is first transformed on a blockchain (as a way of recording changes to data, e.g., token burning) before extracting and loading into another data store. [14]

  9. Knowledge extraction - Wikipedia

    en.wikipedia.org/wiki/Knowledge_extraction

    Knowledge extraction is the creation of knowledge from structured (relational databases, XML) and unstructured (text, documents, images) sources.The resulting knowledge needs to be in a machine-readable and machine-interpretable format and must represent knowledge in a manner that facilitates inferencing.