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1
NEPS technical report for science: Scaling results of starting cohort 3 in 6th grade
Funke, Linda; Kähler, Jana; Hahn, Inga. - : Leibniz Institute for Educational Trajectories, 2016. : Bamberg, 2016. : pedocs-Dokumentenserver/DIPF, 2016
In: Bamberg : Leibniz Institute for Educational Trajectories 2016, 28 S. - (NEPS Survey Paper; 5) (2016)
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NEPS technical report for science: Scaling results of starting cohort 4 in 11th grade
Hahn, Inga; Kähler, Jana. - : Leibniz Institute for Educational Trajectories, National Educational Panel Study, 2016. : Bamberg, 2016. : pedocs-Dokumentenserver/DIPF, 2016
In: Bamberg : Leibniz Institute for Educational Trajectories, National Educational Panel Study 2016, 27 S. - (NEPS Survey Paper; 6) (2016)
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3
The impact of topic bias on quality flaw prediction in Wikipedia ...
Ferschke, Oliver; Gurevych, Iryna; Rittberger, Marc. - : Association for Computational Linguistics (ACL), 2013
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4
The impact of topic bias on quality flaw prediction in Wikipedia
In: Association of Computational Linguistics [Hrsg.]: 51st Annual Meeting of the Association for Computational Linguistics. Stroudsburg, Pa. : Association for Computational Linguistics (ACL) 2013, S. 721-730 (2013)
Abstract: With the increasing amount of user generated reference texts in the web, automatic quality assessment has become a key challenge. However, only a small amount of annotated data is available for training quality assessment systems. Wikipedia contains a large amount of texts annotated with cleanup templates which identify quality flaws. We show that the distribution of these labels is topically biased, since they cannot be applied freely to any arbitrary article. We argue that it is necessary to consider the topical restrictions of each label in order to avoid a sampling bias that results in a skewed classifier and overly optimistic evaluation results. We factor out the topic bias by extracting reliable training instances from the revision history which have a topic distribution similar to the labeled articles. This approach better reflects the situation a classifier would face in a real-life application. (DIPF/Orig.)
Keyword: Algorithm; Algorithms; Algorithmus; Bibliotheks- und Informationswissenschaft; Computerunterstütztes Verfahren; ddc:020; Evaluation; Library and information sciences; Nachschlagewerk; On line; Online; Qualität; Qualitätssicherung; Quality; Quality assurance; Reference book; Reliabilität; Reliability; Social Software; Soziale Software; Standard; World wide web 2.0
URL: http://nbn-resolving.de/urn:nbn:de:0111-dipfdocs-184570
https://www.pedocs.de/volltexte/2020/18457/pdf/The_impact_of_topic_bias_on_quality_flaw_prediction_in_Wikipedia_A.pdf
https://www.pedocs.de/volltexte/2020/18457/
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5
Nationale Identitäten und ein gemeinschaftlicher Bildungsanspruch der EU - ein unauflöslicher Widerspruch? ...
Berggreen-Merkel, Ingeborg. - : Waxmann, 2006
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6
Nationale Identitäten und ein gemeinschaftlicher Bildungsanspruch der EU - ein unauflöslicher Widerspruch?
In: Tertium comparationis 12 (2006) 1, S. 24-47 (2006)
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7
Folgerungen der aktuellen Bildungsvergleichsstudien für das Bundesland Hessen und seine Bildungspolitik
In: Hansel, Toni [Hrsg.]: PISA – und die Folgen? Die Wirkung von Leistungsvergleichsstudien in der Schule. Herbolzheim : Centaurus 2003, S. 128-152 (2003)
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8
Trends in Bildung und Schulentwicklung: Deutschland und Europa
In: Trends in Bildung international (2002) 3, S. 1-7 (2002)
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9
Trends in Bildung und Schulentwicklung: Deutschland und Europa ...
Döbert, Hans. - : DIPF, 2002
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