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  2. PDF Split and Merge - Wikipedia

    en.wikipedia.org/wiki/PDF_Split_and_Merge

    Split PDF files in a number of ways: After every page, even pages or odd pages; After a given set of page numbers; Every n pages; By bookmark level; By size, where the generated files will roughly have the specified size; Rotate PDF files where multiple files can be rotated, either every page or a selected set of pages (i.e. Mb).

  3. PDF - Wikipedia

    en.wikipedia.org/wiki/PDF

    Linearized PDF files (also called "optimized" or "web optimized" PDF files) are constructed in a manner that enables them to be read in a Web browser plugin without waiting for the entire file to download, since all objects required for the first page to display are optimally organized at the start of the file. [27]

  4. PDFtk - Wikipedia

    en.wikipedia.org/wiki/Pdftk

    PDFtk (short for PDF Toolkit) is a toolkit for manipulating Portable Document Format (PDF) documents. [3] [4] It runs on Linux, Windows and macOS. [5] It comes in three versions: PDFtk Server (open-source command-line tool), PDFtk Free and PDFtk Pro (proprietary paid). [2] It is able to concatenate, shuffle, split and rotate PDF files.

  5. Sumatra PDF - Wikipedia

    en.wikipedia.org/wiki/Sumatra_PDF

    Sumatra PDF is a free and open-source document viewer that supports many document formats including: Portable Document Format (PDF), Microsoft Compiled HTML Help (CHM), DjVu, EPUB, FictionBook (FB2), MOBI, PRC, Open XML Paper Specification (OpenXPS, OXPS, XPS), and Comic Book Archive file (CB7, CBR, CBT, CBZ). [3]

  6. File:Ilovepdf.svg - Wikipedia

    en.wikipedia.org/wiki/File:Ilovepdf.svg

    Original file (SVG file, nominally 85 × 75 pixels, file size: 660 bytes) This is a file from the Wikimedia Commons . Information from its description page there is shown below.

  7. Data compression - Wikipedia

    en.wikipedia.org/wiki/Data_compression

    Data compression aims to reduce the size of data files, enhancing storage efficiency and speeding up data transmission. K-means clustering, an unsupervised machine learning algorithm, is employed to partition a dataset into a specified number of clusters, k, each represented by the centroid of its points.

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