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  2. Table extraction - Wikipedia

    en.wikipedia.org/wiki/Table_extraction

    The Python pandas software library can extract tables from HTML webpages via its read_html() function. More challenging is table extraction from PDFs or scanned images, where there usually is no table-specific machine readable markup. [1] Systems that extract data from tables in scientific PDFs have been described. [2] [3]

  3. Information extraction - Wikipedia

    en.wikipedia.org/wiki/Information_extraction

    A recent [when?] development is Visual Information Extraction, [16] [17] that relies on rendering a webpage in a browser and creating rules based on the proximity of regions in the rendered web page. This helps in extracting entities from complex web pages that may exhibit a visual pattern, but lack a discernible pattern in the HTML source code.

  4. reStructuredText - Wikipedia

    en.wikipedia.org/wiki/ReStructuredText

    reStructuredText (RST, ReST, or reST) is a file format for textual data used primarily in the Python programming language community for technical documentation.. It is part of the Docutils project of the Python Doc-SIG (Documentation Special Interest Group), aimed at creating a set of tools for Python similar to Javadoc for Java or Plain Old Documentation (POD) for Perl.

  5. Data extraction - Wikipedia

    en.wikipedia.org/wiki/Data_extraction

    Data extraction is the act or process of retrieving data out of (usually unstructured or poorly structured) data sources for further data processing or data storage (data migration). The import into the intermediate extracting system is thus usually followed by data transformation and possibly the addition of metadata prior to export to another ...

  6. Web scraping - Wikipedia

    en.wikipedia.org/wiki/Web_scraping

    Web scraping is the process of automatically mining data or collecting information from the World Wide Web. It is a field with active developments sharing a common goal with the semantic web vision, an ambitious initiative that still requires breakthroughs in text processing, semantic understanding, artificial intelligence and human-computer interactions.

  7. Keyword extraction - Wikipedia

    en.wikipedia.org/wiki/Keyword_extraction

    Keyword extraction is tasked with the automatic identification of terms that best describe the subject of a document. [1] [2] Key phrases, key terms, key segments or just keywords are the terminology which is used for defining the terms that represent the most relevant information contained in the document. Although the terminology is different ...

  8. py2exe - Wikipedia

    en.wikipedia.org/wiki/Py2exe

    These executables can run on a system without Python installed. [3] It is the most common tool for doing so. py2exe was used to distribute the official BitTorrent client (before the version 6.0) and is still used to distribute SpamBayes as well as other projects. Since May 2014, version 0.9.2.0 of py2exe is available for Python 3. [1]

  9. KNIME - Wikipedia

    en.wikipedia.org/wiki/KNIME

    KNIME workflows can be used as data sets to create report templates that can be exported to document formats such as doc, ppt, xls, pdf and others. Other capabilities of KNIME are: KNIMEs core-architecture allows processing of large data volumes that are only limited by the available hard disk space (not limited to the available RAM). E.g.