Difference between revisions of "Wikipedia Edit Number Prediction from the Past Edit Record based on Auto-Supervised Learning"
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== Overview == | == Overview == | ||
This paper describes approach to the [[Wikipedia]] Participation Challenge that seeks to predict the number of edits a Wikipedia editor will make in the next five months. Authors approach takes a time series analysis approach in combination with supervised learning, which authors call auto-supervised learning. The best model of solutions achieved a 41% improvement over WMF's baseline predictive model. The result is low accuracy compared with related work but showed 9th place in ICDM contest. | This paper describes approach to the [[Wikipedia]] Participation Challenge that seeks to predict the number of edits a Wikipedia editor will make in the next five months. Authors approach takes a time series analysis approach in combination with supervised learning, which authors call auto-supervised learning. The best model of solutions achieved a 41% improvement over WMF's baseline predictive model. The result is low accuracy compared with related work but showed 9th place in ICDM contest. | ||
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+ | == Embed == | ||
+ | === Wikipedia Quality === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | Yoshida, Yutaka; Ohwada, Hayato. (2012). "[[Wikipedia Edit Number Prediction from the Past Edit Record based on Auto-Supervised Learning]]".DOI: 10.1109/ICSAI.2012.6223541. | ||
+ | </nowiki> | ||
+ | </code> | ||
+ | |||
+ | === English Wikipedia === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | {{cite journal |last1=Yoshida |first1=Yutaka |last2=Ohwada |first2=Hayato |title=Wikipedia Edit Number Prediction from the Past Edit Record based on Auto-Supervised Learning |date=2012 |doi=10.1109/ICSAI.2012.6223541 |url=https://wikipediaquality.com/wiki/Wikipedia_Edit_Number_Prediction_from_the_Past_Edit_Record_based_on_Auto-Supervised_Learning}} | ||
+ | </nowiki> | ||
+ | </code> | ||
+ | |||
+ | === HTML === | ||
+ | <code> | ||
+ | <nowiki> | ||
+ | Yoshida, Yutaka; Ohwada, Hayato. (2012). &quot;<a href="https://wikipediaquality.com/wiki/Wikipedia_Edit_Number_Prediction_from_the_Past_Edit_Record_based_on_Auto-Supervised_Learning">Wikipedia Edit Number Prediction from the Past Edit Record based on Auto-Supervised Learning</a>&quot;.DOI: 10.1109/ICSAI.2012.6223541. | ||
+ | </nowiki> | ||
+ | </code> |
Revision as of 11:48, 15 September 2019
Authors | Yutaka Yoshida Hayato Ohwada |
---|---|
Publication date | 2012 |
DOI | 10.1109/ICSAI.2012.6223541 |
Links | Original |
Wikipedia Edit Number Prediction from the Past Edit Record based on Auto-Supervised Learning - scientific work related to Wikipedia quality published in 2012, written by Yutaka Yoshida and Hayato Ohwada.
Overview
This paper describes approach to the Wikipedia Participation Challenge that seeks to predict the number of edits a Wikipedia editor will make in the next five months. Authors approach takes a time series analysis approach in combination with supervised learning, which authors call auto-supervised learning. The best model of solutions achieved a 41% improvement over WMF's baseline predictive model. The result is low accuracy compared with related work but showed 9th place in ICDM contest.
Embed
Wikipedia Quality
Yoshida, Yutaka; Ohwada, Hayato. (2012). "[[Wikipedia Edit Number Prediction from the Past Edit Record based on Auto-Supervised Learning]]".DOI: 10.1109/ICSAI.2012.6223541.
English Wikipedia
{{cite journal |last1=Yoshida |first1=Yutaka |last2=Ohwada |first2=Hayato |title=Wikipedia Edit Number Prediction from the Past Edit Record based on Auto-Supervised Learning |date=2012 |doi=10.1109/ICSAI.2012.6223541 |url=https://wikipediaquality.com/wiki/Wikipedia_Edit_Number_Prediction_from_the_Past_Edit_Record_based_on_Auto-Supervised_Learning}}
HTML
Yoshida, Yutaka; Ohwada, Hayato. (2012). "<a href="https://wikipediaquality.com/wiki/Wikipedia_Edit_Number_Prediction_from_the_Past_Edit_Record_based_on_Auto-Supervised_Learning">Wikipedia Edit Number Prediction from the Past Edit Record based on Auto-Supervised Learning</a>".DOI: 10.1109/ICSAI.2012.6223541.