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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

   HTML Form format HTML 4.01 Specification since PDF 1.5; HTML 2.0 since 1.2 Forms Data Format (FDF) based on PDF, uses the same syntax and has essentially the same file structure, but is much simpler than PDF since the body of an FDF document consists of only one required object. Forms Data Format is defined in the PDF specification (since PDF 1.2).

4. List of PDF software - Wikipedia

   en.wikipedia.org/wiki/List_of_PDF_software

   Default PDF and file viewer for GNOME; replaces GPdf. Supports addition and removal (since v3.14), of basic text note annotations. CUPS: Apache License 2.0: No No No Yes Printing system can render any document to a PDF file, thus any Linux program with print capability can produce PDF files Pdftk: GPLv2: No Yes Yes

5. 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 for tasks such as handling multiple files, encryption, and archive-splitting.

6. List of archive formats - Wikipedia

   en.wikipedia.org/wiki/List_of_archive_formats

   This means that compressed archives with the UC2 file extension can hold almost 1 million files. .uca PerfectCompress [17] Windows: Windows: No Based on PAQ, RZM, CSC, CCM, and 7zip. The format consists of a PAQ, RZM, CSC, or CCM compressed file and a manifest with compression settings stored in a 7z archive. .uha UHarc DOS/Windows: DOS/Windows ...

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.