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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

   The idea came from the need for their families to compress and send large documents via email. [5] The initial version of the site featured a standalone PDF compression tool. [6] Since then, the online platform has introduced over 16 PDF tools to convert, compress and edit PDF documents. [7]

4. 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]

5. Solid Converter PDF - Wikipedia

   en.wikipedia.org/wiki/Solid_Converter_PDF

   Solid Converter PDF is document reconstruction software from Solid Documents which converts PDF files to editable formats. Originally released for the Microsoft Windows operating system, a Mac OS X version was released in 2010. The current versions are Solid Converter PDF 9.0 for Windows and Solid PDF to Word for Mac 2.1.

6. Data compression ratio - Wikipedia

   en.wikipedia.org/wiki/Data_compression_ratio

   For example, uncompressed songs in CD format have a data rate of 16 bits/channel x 2 channels x 44.1 kHz ≅ 1.4 Mbit/s, whereas AAC files on an iPod are typically compressed to 128 kbit/s, yielding a compression ratio of 10.9, for a data-rate saving of 0.91, or 91%.

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. This process condenses extensive ...