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Google Scholar is a freely accessible web search engine that indexes the full text or metadata of scholarly literature across an array of publishing formats and disciplines. . Released in beta in November 2004, the Google Scholar index includes peer-reviewed online academic journals and books, conference papers, theses and dissertations, preprints, abstracts, technical reports, and other ...
Google Books (previously known as Google Book Search, Google Print, and by its code-name Project Ocean) [1] is a service from Google that searches the full text of books and magazines that Google has scanned, converted to text using optical character recognition (OCR), and stored in its digital database. [2]
Google Scholar: Multidisciplinary Free Google [68] HCI Bibliography: Human-computer interface: An electronic bibliography for most of HCI for researchers, developers, educators, and students Free Gary Perlman [69] HubMed: Medicine: An alternative interface to the PubMed medical literature database Free Alf Eaton [70] IEEE Xplore
Each table is arranged alphabetically by the specific work, then by the language of the translation. Translations are then sub-arranged by date of publication (earliest-latest). Where possible, the date of publication given is the date of the first edition by that translator. More modern editions/versions may be available.
According to American scholar Samuel Ross, there are 2,700 Qur’an commentaries extant in manuscript form, and 300 commentaries have been published. Considering that around 96% of the Arabic-language manuscripts remain unstudied, Ross argues that "by extrapolation there may be thousands of additional commentaries still waiting to be discovered."
The full automation of the proof correction cycles has only become possible with the onset of online collaborative writing platforms, such as Authorea, Google Docs, Overleaf, and various others, where a remote service oversees the copy-editing interactions of multiple authors and exposes them as explicit, actionable historic events.
The English-to-German translation model was trained on the 2014 WMT English-German dataset consisting of nearly 4.5 million sentences derived from TED Talks and high-quality news articles. A separate translation model was trained on the much larger 2014 WMT English-French dataset, consisting of 36 million sentences.
Machine translation, like DeepL or Google Translate, is a useful starting point for translations, but translators must revise errors as necessary and confirm that the translation is accurate, rather than simply copy-pasting machine-translated text into the English Wikipedia. Do not translate text that appears unreliable or low-quality.