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  2. Zamzar - Wikipedia

    en.wikipedia.org/wiki/Zamzar

    In February 2021 Zamzar expanded their tool and announced a new file compression service. [10] The compressor is visually similar to the conversion tool with a drag and drop download feature. As with the converter, users have the option to subscribe for a paid plan if they wish to compress multiple or larger files than the free service permits [11]

  3. Smallpdf.com - Wikipedia

    en.wikipedia.org/wiki/Smallpdf.com

    Smallpdf is a Swiss online web-based PDF software, founded in 2013. [2] It offers free version with limited features to compress, convert and edit PDF documents. [ 3 ] And its paid version offers advanced features like OCR, compress, and more [ 4 ] .

  4. List of archive formats - Wikipedia

    en.wikipedia.org/wiki/List_of_archive_formats

    The replacement for the .sit format that supports more compression methods, UNIX file permissions, long file names, very large files, more encryption options, data specific compressors (JPEG, Zip, PDF, 24-bit image, MP3). The free StuffIt Expander is available for Windows and OS X. .sqx SQX: Windows: Windows: Yes A royalty-free compressing format

  5. Download, install, or uninstall AOL Desktop Gold - AOL Help

    help.aol.com/articles/aol-desktop-downloading...

    Learn how to download and install or uninstall the Desktop Gold software and if your computer meets the system requirements.

  6. LHA (file format) - Wikipedia

    en.wikipedia.org/wiki/LHA_(file_format)

    LHA or LZH is a freeware compression utility and associated file format. It was created in 1988 by Haruyasu Yoshizaki ( 吉崎栄泰 , Yoshizaki Haruyasu ) , a doctor, and originally named LHarc . A complete rewrite of LHarc, tentatively named LHx , was eventually released as LH .

  7. Data compression ratio - Wikipedia

    en.wikipedia.org/wiki/Data_compression_ratio

    Lossless compression of digitized data such as video, digitized film, and audio preserves all the information, but it does not generally achieve compression ratio much better than 2:1 because of the intrinsic entropy of the data. Compression algorithms which provide higher ratios either incur very large overheads or work only for specific data ...

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