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2. 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].

3. PDF - Wikipedia

   en.wikipedia.org/wiki/PDF

   Many commercial offset printers have accepted the submission of press-ready PDF files as a print source, specifically the PDF/X-1a subset and variations of the same. [83] The submission of press-ready PDF files is a replacement for the problematic need for receiving collected native working files.

4. bzip2 - Wikipedia

   en.wikipedia.org/wiki/Bzip2

   bzip2 is a free and open-source file compression program that uses the Burrows–Wheeler algorithm.It only compresses single files and is not a file archiver.It relies on separate external utilities such as tar for tasks such as handling multiple files, and other tools for encryption, and archive splitting.

5. List of PDF software - Wikipedia

   en.wikipedia.org/wiki/List_of_PDF_software

   an Office suite; allows to export (and import, with accuracy limitations) PDF files. Microsoft Word 2013: Proprietary: Desktop software. The 2013 edition of Office allows PDF files to be converted into a format that can be edited. Nitro PDF Reader: Trialware: Text highlighting, draw lines and measure distances in PDF files. Nitro PDF Pro ...

6. Data compression ratio - Wikipedia

   en.wikipedia.org/wiki/Data_compression_ratio

   Thus, a representation that compresses the storage size of a file from 10 MB to 2 MB yields a space saving of 1 - 2/10 = 0.8, often notated as a percentage, 80%. For signals of indefinite size, such as streaming audio and video, the compression ratio is defined in terms of uncompressed and compressed data rates instead of data sizes:

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 ...