Tracking topics on revision graphs of wikipedia edit history
|Tracking topics on revision graphs of wikipedia edit history|
|Author(s)||Li B., Wu J., Iwaihara M.|
|Published in||Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)|
|Keyword(s)||edit history, supergram, topic summarization, Wikipedia (Extra: Artificial intelligence, Computer science, Computers, Degree of similarity, Online encyclopedia, supergram, topic summarization, Wikipedia, Information management)|
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Tracking topics on revision graphs of wikipedia edit history is a 2014 conference paper written in English by Li B., Wu J., Iwaihara M. and published in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics).
Wikipedia is known as the largest online encyclopedia, in which articles are constantly contributed and edited by users. Past revisions of articles after edits are also accessible from the public for confirming the edit process. However, the degree of similarity between revisions is very high, making it difficult to generate summaries for these small changes from revision graphs of Wikipedia edit history. In this paper, we propose an approach to give a concise summary to a given scope of revisions, by utilizing supergrams, which are consecutive unchanged term sequences.
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