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Automatic vandalism detection in wikipedia: Towards a machine learning approach
Abstract Since the end of 2006 several autonomous bSince the end of 2006 several autonomous bots are, or have been, running on Wikipedia to keep the encyclopedia free from vandalism and other damaging edits. These expert systems, however, are far from optimal and should be improved to relieve the human editors from the burden of manually reverting such edits. We investigate the possibility of using machine learning techniques to build an autonomous system capable to distinguish vandalism from legitimate edits. We highlight the results of a small but important step in this direction by applying commonly known machine learning algorithms using a straightforward feature representation. Despite the promising results, this study reveals that elementary features, which are also used by the current approaches to fight vandalism, are not sufficient to build such a system. They will need to be accompanied by additional information which, among other things, incorporates the semantics of a revision. Copyrighttes the semantics of a revision. Copyright
Abstractsub Since the end of 2006 several autonomous bSince the end of 2006 several autonomous bots are, or have been, running on Wikipedia to keep the encyclopedia free from vandalism and other damaging edits. These expert systems, however, are far from optimal and should be improved to relieve the human editors from the burden of manually reverting such edits. We investigate the possibility of using machine learning techniques to build an autonomous system capable to distinguish vandalism from legitimate edits. We highlight the results of a small but important step in this direction by applying commonly known machine learning algorithms using a straightforward feature representation. Despite the promising results, this study reveals that elementary features, which are also used by the current approaches to fight vandalism, are not sufficient to build such a system. They will need to be accompanied by additional information which, among other things, incorporates the semantics of a revision. Copyrighttes the semantics of a revision. Copyright
Bibtextype inproceedings  +
Has author Smets K. + , Goethals B. + , Verdonk B. +
Has extra keyword Autonomous systems + , Feature representation + , Machine learning algorithms + , Machine learning techniques + , Machine learning + , Wikipedia + , Artificial intelligence + , Expert systems + , Robot learning + , Learning algorithms +
Isbn 9781577353836  +
Language English +
Number of citations by publication 3  +
Number of references by publication 0  +
Pages 43–48  +
Published in AAAI Workshop - Technical Report +
Title Automatic vandalism detection in wikipedia: Towards a machine learning approach +
Type conference paper  +
Volume WS-08-15  +
Year 2008 +
Creation dateThis property is a special property in this wiki. 6 November 2014 19:57:38  +
Categories Publications without keywords parameter  + , Publications without license parameter  + , Publications without DOI parameter  + , Publications without remote mirror parameter  + , Publications without archive mirror parameter  + , Publications without paywall mirror parameter  + , Conference papers  + , Publications without references parameter  + , Publications  +
Modification dateThis property is a special property in this wiki. 6 November 2014 19:57:38  +
DateThis property is a special property in this wiki. 2008  +
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