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This article contains a representative list of notable databases and search engines useful in an academic setting for finding and accessing articles in academic journals, institutional repositories, archives, or other collections of scientific and other articles. Databases and search engines differ substantially in terms of coverage and ...
These sites allow you to search for articles that are entirely free to read. Find this article in BASE, a search engine for academic open online resources; Find this article in OAIster, a catalogue of open-access materials; Find this article at JURN, a curated search engine for free academic articles and books; Find this article at OpenDOAR, a ...
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 ...
Though the search engines may be accessed for free, indexed images themselves may be under restricted license. Google Books [3] - Searchable archive of magazines and books (some full-text, including photograph captions and references to photographs from related articles and content).
BASE (Bielefeld Academic Search Engine) is a multi-disciplinary search engine to scholarly internet resources, created by Bielefeld University Library in Bielefeld, Germany. It is based on free and open-source software such as Apache Solr and VuFind . [ 1 ]
Semantic Scholar is free to use and unlike similar search engines (i.e. Google Scholar) does not search for material that is behind a paywall. [ 5 ] [ citation needed ] One study compared the index scope of Semantic Scholar to Google Scholar, and found that for the papers cited by secondary studies in computer science, the two indices had ...
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CiteSeer X uses automated information extraction tools, usually built on machine learning methods such ParsCit, to extract scholarly document metadata such as title, authors, abstract, citations, etc. As such, there are sometime errors in authors and titles. Other academic search engines have similar errors.