| Literature database|
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Literature database is included as keyword or extra keyword in 2 datasets, 0 tools and 3 publications.
|WikiLit||A few MB||English||WikiLit is a comprehensive literature review of scholarly research on Wikipedia (it does not include literature nor studies about other wikis).|
|WikiPapers||A few MB||English||WikiPapers is compilation of resources (conference papers, journal articles, theses, books, datasets and tools) focused on the research of wikis.|
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|Title||Author(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|WikiLit: Collecting the Wiki and Wikipedia Literature||Phoebe Ayers
|WikiSym||English||2011||This workshop has three key goals. First, we will examine existing and proposed systems for collecting and analyzing the research literature about wikis. Second, we will discuss the challenges in building such a system and will engage participants to design a sustainable collaborative system to achieve this goal. Finally, we will provide a forum to build upon ongoing wiki community discussions about problems and opportunities in finding and sharing the wiki research literature.||1||2|
|WikiLit: Collecting the wiki and Wikipedia literature||Phoebe Ayers
|WikiSym 2011 Conference Proceedings - 7th Annual International Symposium on Wikis and Open Collaboration||English||2011||This workshop has three key goals. First, we will examine existing and proposed systems for collecting and analyzing the research literature about wikis. Second, we will discuss the challenges in building such a system and will engage participants to design a sustainable collaborative system to achieve this goal. Finally, we will provide a forum to build upon ongoing wiki community discussions about problems and opportunities in finding and sharing the wiki research literature.||0||2|
|Hierarchical topic-based communities construction for authors in a literature database||Wu C.-L.
|Lecture Notes in Computer Science||English||2010||In this paper, given a set of research papers with only title and author information, a mining strategy is proposed to discover and organize the communities of authors according to both the co-author relationships and research topics of their published papers. The proposed method applies the CONGA algorithm to discover collaborative communities from the network constructed from the co-author relationship. To further group the collaborative communities of authors according to research interests, the CiteSeerX is used as an external source to discover the hidden hierarchical relationships among the topics covered by the papers. In order to evaluate whether the constructed topic-based collaborative community is semantically meaningful, the first part of evaluation is to measure the consistency between the terms appearing in the published papers of a topic-based collaborative community and the terms in the documents related to the specific topic retrieved from other external source. The experimental results show that 81.61% of the topic-based collaborative communities satisfy the consistency requirement. On the other hand, the accuracy of the discovered sub-concept relationship is verified by checking the Wikipedia categories. It is shown that 75.96% of the sub-concept terms are properly assigned in the concept hierarchy.||0||0|