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Bibliometric-Enhanced arXiv: A Data Set for Paper-Based and Citation-Based Tasks

Saier, Tarek; Färber, Michael


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    <subfield code="a">&lt;p&gt;We propose a new data set based on &lt;strong&gt;all publications from all scientific fields available on arXiv.org&lt;/strong&gt;. Apart from providing the &lt;strong&gt;papers&amp;#39; plain text&lt;/strong&gt;, &lt;strong&gt;in-text citations&lt;/strong&gt; were annotated via global identifiers. As far as possible, cited publications were linked to the &lt;strong&gt;Microsoft Academic Graph&lt;/strong&gt;. Our data set consists of &lt;strong&gt;over one million documents&lt;/strong&gt; and &lt;strong&gt;29.2 million citation contexts&lt;/strong&gt;. The data set, which is made freely available for research purposes, not only can enhance the future evaluation of researchpaper-based and citation context-based approaches but also serve as a basis for novel ideas to analyze papers.&lt;/p&gt;

&lt;p&gt;More information can be found in our paper &lt;a href="http://ceur-ws.org/Vol-2345/paper2.pdf"&gt;Bibliometric-Enhanced arXiv: A Data Set for Paper-Based and Citation-Based Tasks&lt;/a&gt;.&lt;/p&gt;

&lt;p&gt;See &lt;a href="https://github.com/IllDepence/unarXive"&gt;https://github.com/IllDepence/unarXive&lt;/a&gt; for the source code which has been used for creating the data set.&lt;/p&gt;</subfield>
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