Difference between revisions of "Measuring Contextual Fitness Using Error Contexts Extracted from the Wikipedia Revision History"
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| − | Authors evaluate measures of contextual fitness on the task of detecting real-word spelling errors. For that purpose, authors extract naturally occurring errors and their contexts from the [[Wikipedia]] revision history. Authors show that such natural errors are better suited for evaluation than the previously used artificially created errors. In particular, the precision of statistical methods has been largely over-estimated, while the precision of knowledge-based approaches has been under-estimated. Additionally, authors show that knowledge-based approaches can be improved by using semantic relatedness measures that make use of knowledge beyond classical taxonomic relations. Finally, authors show that statistical and knowledge-based methods can be combined for increased performance. | + | Authors evaluate measures of contextual fitness on the task of detecting real-word spelling errors. For that purpose, authors extract naturally occurring errors and their contexts from the [[Wikipedia]] [[revision history]]. Authors show that such natural errors are better suited for evaluation than the previously used artificially created errors. In particular, the precision of statistical methods has been largely over-estimated, while the precision of knowledge-based approaches has been under-estimated. Additionally, authors show that knowledge-based approaches can be improved by using semantic relatedness measures that make use of knowledge beyond classical taxonomic relations. Finally, authors show that statistical and knowledge-based methods can be combined for increased performance. |
== Embed == | == Embed == | ||
Latest revision as of 11:29, 19 May 2019
Authors | Torsten Zesch |
|---|---|
Publication date | 2012 |
ISBN | 978-1-937284-19-0 |
Links | Original Preprint |
Measuring Contextual Fitness Using Error Contexts Extracted from the Wikipedia Revision History - scientific work related to Wikipedia quality published in 2012, written by Torsten Zesch.
Overview
Authors evaluate measures of contextual fitness on the task of detecting real-word spelling errors. For that purpose, authors extract naturally occurring errors and their contexts from the Wikipedia revision history. Authors show that such natural errors are better suited for evaluation than the previously used artificially created errors. In particular, the precision of statistical methods has been largely over-estimated, while the precision of knowledge-based approaches has been under-estimated. Additionally, authors show that knowledge-based approaches can be improved by using semantic relatedness measures that make use of knowledge beyond classical taxonomic relations. Finally, authors show that statistical and knowledge-based methods can be combined for increased performance.
Embed
Wikipedia Quality
Zesch, Torsten. (2012). "[[Measuring Contextual Fitness Using Error Contexts Extracted from the Wikipedia Revision History]]". Association for Computational Linguistics.
English Wikipedia
{{cite journal |last1=Zesch |first1=Torsten |title=Measuring Contextual Fitness Using Error Contexts Extracted from the Wikipedia Revision History |date=2012 |url=https://wikipediaquality.com/wiki/Measuring_Contextual_Fitness_Using_Error_Contexts_Extracted_from_the_Wikipedia_Revision_History |journal=Association for Computational Linguistics}}
HTML
Zesch, Torsten. (2012). "<a href="https://wikipediaquality.com/wiki/Measuring_Contextual_Fitness_Using_Error_Contexts_Extracted_from_the_Wikipedia_Revision_History">Measuring Contextual Fitness Using Error Contexts Extracted from the Wikipedia Revision History</a>". Association for Computational Linguistics.
