Filtering Reviews by Random Individual Error
M. Geierhos, F. Bäumer, S. Schulze, V. Stuß, in: M. Ali, Y.S. Kwon, C.-H. Lee, J. Kim, Y. Kim (Eds.), Current Approaches in Applied Artificial Intelligence, Springer International Publishing, Cham, 2015, pp. 305–315.
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Buchbeitrag
| Veröffentlicht
| Englisch
Autor*in
Geierhos, Michaela;
Bäumer, Frederik
;
Schulze, Sabine;
Stuß, Valentina
;
Schulze, Sabine;
Stuß, ValentinaHerausgeber*in
Ali, Moonis;
Kwon, Young Sig;
Lee, Chang-Hwan;
Kim, Juntae;
Kim, Yongdai
Abstract
Opinion mining from physician rating websites depends on the quality of the extracted information. Sometimes reviews are user-error prone and the assigned stars or grades contradict the associated content. We therefore aim at detecting random individual error within reviews. Such errors comprise the disagreement in polarity of review texts and the respective ratings. The challenges that thereby arise are (1) the content and sentiment analysis of the review texts and (2) the removal of the random individual errors contained therein. To solve these tasks, we assign polarities to automatically recognized opinion phrases in reviews and then check for divergence in rating and text polarity. The novelty of our approach is that we improve user-generated data quality by excluding error-prone reviews on German physician websites from average ratings.
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Buchtitel
Current Approaches in Applied Artificial Intelligence
Seite
305-315
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Geierhos, Michaela ; Bäumer, Frederik ; Schulze, Sabine ; Stuß, Valentina: Filtering Reviews by Random Individual Error. In: Ali, M. ; Kwon, Y. S. ; Lee, C.-H. ; Kim, J. ; Kim, Y. (Hrsg.): Current Approaches in Applied Artificial Intelligence, Lecture Notes in Computer Science. Cham : Springer International Publishing, 2015, S. 305–315
Geierhos M, Bäumer F, Schulze S, Stuß V. Filtering Reviews by Random Individual Error. In: Ali M, Kwon YS, Lee C-H, Kim J, Kim Y, eds. Current Approaches in Applied Artificial Intelligence. Lecture Notes in Computer Science. Cham: Springer International Publishing; 2015:305-315. doi:10.1007/978-3-319-19066-2_30
Geierhos, M., Bäumer, F., Schulze, S., & Stuß, V. (2015). Filtering Reviews by Random Individual Error. In M. Ali, Y. S. Kwon, C.-H. Lee, J. Kim, & Y. Kim (Eds.), Current Approaches in Applied Artificial Intelligence (pp. 305–315). Cham: Springer International Publishing. https://doi.org/10.1007/978-3-319-19066-2_30
@inbook{Geierhos_Bäumer_Schulze_Stuß_2015, place={Cham}, series={Lecture Notes in Computer Science}, title={Filtering Reviews by Random Individual Error}, DOI={10.1007/978-3-319-19066-2_30}, booktitle={Current Approaches in Applied Artificial Intelligence}, publisher={Springer International Publishing}, author={Geierhos, Michaela and Bäumer, Frederik and Schulze, Sabine and Stuß, Valentina}, editor={Ali, Moonis and Kwon, Young Sig and Lee, Chang-Hwan and Kim, Juntae and Kim, YongdaiEditors}, year={2015}, pages={305–315}, collection={Lecture Notes in Computer Science} }
Geierhos, Michaela, Frederik Bäumer, Sabine Schulze, and Valentina Stuß. “Filtering Reviews by Random Individual Error.” In Current Approaches in Applied Artificial Intelligence, edited by Moonis Ali, Young Sig Kwon, Chang-Hwan Lee, Juntae Kim, and Yongdai Kim, 305–15. Lecture Notes in Computer Science. Cham: Springer International Publishing, 2015. https://doi.org/10.1007/978-3-319-19066-2_30.
M. Geierhos, F. Bäumer, S. Schulze, and V. Stuß, “Filtering Reviews by Random Individual Error,” in Current Approaches in Applied Artificial Intelligence, M. Ali, Y. S. Kwon, C.-H. Lee, J. Kim, and Y. Kim, Eds. Cham: Springer International Publishing, 2015, pp. 305–315.
Geierhos, Michaela, et al. “Filtering Reviews by Random Individual Error.” Current Approaches in Applied Artificial Intelligence, edited by Moonis Ali et al., Springer International Publishing, 2015, pp. 305–15, doi:10.1007/978-3-319-19066-2_30.
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