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Publikationstyp: Konferenz: Paper
Art der Begutachtung: Keine Angabe
Titel: JOINT_FORCES : unite competing sentiment classifiers with random forest
Autor/-in: Dürr, Oliver
Uzdilli, Fatih
Cieliebak, Mark
DOI: 10.21256/zhaw-3779
Tagungsband: Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014)
Seite(n): 366
Seiten bis: 369
Angaben zur Konferenz: International Workshop on Semantic Evaluation (SemEval-2014), Dublin, Irland, 23-24 August 2014
Erscheinungsdatum: 2014
Verlag / Hrsg. Institution: Association for Computational Linguistics
ISBN: 978-1-941643-24-2
Sprache: Englisch
Schlagwörter: Sentiment analysis; Random forest; Competition; Ensemble method
Fachgebiet (DDC): 410.285: Computerlinguistik
Zusammenfassung: In this paper, we describe how we created a meta-classifier to detect the message-level sentiment of tweets. We participated in SemEval-2014 Task 9B by combining the results of several existing classifiers using a random forest. The results of 5 other teams from the competition as well as from 7 general purpose commercial classifiers were used to train the algorithm. This way, we were able to get a boost of up to 3.24 F1 score points.
URI: https://digitalcollection.zhaw.ch/handle/11475/7363
Volltext Version: Publizierte Version
Lizenz (gemäss Verlagsvertrag): CC BY 4.0: Namensnennung 4.0 International
Departement: School of Engineering
Organisationseinheit: Institut für Informatik (InIT)
Institut für Datenanalyse und Prozessdesign (IDP)
Enthalten in den Sammlungen:Publikationen School of Engineering

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Dürr, O., Uzdilli, F., & Cieliebak, M. (2014). JOINT_FORCES : unite competing sentiment classifiers with random forest [Conference paper]. Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014), 366–369. https://doi.org/10.21256/zhaw-3779
Dürr, O., Uzdilli, F. and Cieliebak, M. (2014) ‘JOINT_FORCES : unite competing sentiment classifiers with random forest’, in Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014). Association for Computational Linguistics, pp. 366–369. Available at: https://doi.org/10.21256/zhaw-3779.
O. Dürr, F. Uzdilli, and M. Cieliebak, “JOINT_FORCES : unite competing sentiment classifiers with random forest,” in Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014), 2014, pp. 366–369. doi: 10.21256/zhaw-3779.
DÜRR, Oliver, Fatih UZDILLI und Mark CIELIEBAK, 2014. JOINT_FORCES : unite competing sentiment classifiers with random forest. In: Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014). Conference paper. Association for Computational Linguistics. 2014. S. 366–369. ISBN 978-1-941643-24-2
Dürr, Oliver, Fatih Uzdilli, and Mark Cieliebak. 2014. “JOINT_FORCES : Unite Competing Sentiment Classifiers with Random Forest.” Conference paper. In Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014), 366–69. Association for Computational Linguistics. https://doi.org/10.21256/zhaw-3779.
Dürr, Oliver, et al. “JOINT_FORCES : Unite Competing Sentiment Classifiers with Random Forest.” Proceedings of the International Workshop on Semantic Evaluation (SemEval-2014), Association for Computational Linguistics, 2014, pp. 366–69, https://doi.org/10.21256/zhaw-3779.


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