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2. Help:WordToWiki - Wikipedia

   en.wikipedia.org/wiki/Help:WordToWiki

   OpenOffice or LibreOffice. LibreOffice Writer can save Word documents directly to wikitext: go to File → Export → Save as type: Mediawiki. (For Linux users it may be necessary to install the library libreoffice-wiki-publisher ). Alternatively, use the command-line utility like this: soffice --headless --convert-to txt:MediaWiki mydocument.doc.

3. Zamzar - Wikipedia

   en.wikipedia.org/wiki/Zamzar

   Zamzar is currently free to use, but there is a limit of two conversions per hour for files up to 100MB. Users can pay a monthly subscription in order to access preferential features, such as unlimited file conversions, online file management, shorter response and queuing times and other benefits. Naming etymology

4. Wikipedia:Tools/Editing tools - Wikipedia

   en.wikipedia.org/wiki/Wikipedia:Tools/Editing_tools

   wikEd is a full-featured, in-browser text editor that adds enhanced text processing functions to Wikipedia and other MediaWiki edit pages (currently Mozilla, Firefox, SeaMonkey, Safari, and Chrome only). Features include: Pasting formatted text, e.g. from MS-Word (including tables)

5. AOL Mail

   mail.aol.com

   Get AOL Mail for FREE! Manage your email like never before with travel, photo & document views. Personalize your inbox with themes & tabs. You've Got Mail!

6. Lossy compression - Wikipedia

   en.wikipedia.org/wiki/Lossy_compression

   In information technology, lossy compression or irreversible compression is the class of data compression methods that uses inexact approximations and partial data discarding to represent the content. These techniques are used to reduce data size for storing, handling, and transmitting content. The different versions of the photo of the cat on ...

7. Word2vec - Wikipedia

   en.wikipedia.org/wiki/Word2vec

   e. Word2vec is a technique in natural language processing (NLP) for obtaining vector representations of words. These vectors capture information about the meaning of the word based on the surrounding words. The word2vec algorithm estimates these representations by modeling text in a large corpus. Once trained, such a model can detect synonymous ...