Aspect-Level Sentiment Analysis in Czech
作者： Josef Steinberger , Tomáš Brychcín , Michal Konkol
DOI: 10.3115/V1/W14-2605
关键词:
摘要: This paper presents a pioneering research on aspect-level sentiment analysis in Czech. The main contribution of the is newly created Czech aspectlevel corpus, based data from restaurant reviews. We annotated corpus with two variants ‐ aspect terms and categories. consists 1,244 sentences 1,824 aspects freely available to community. Furthermore, we propose baseline system supervised machine learning. Our detects Fmeasure 68.65% their polarities accuracy 66.27%. categories are recognized F-measure 74.02% 66.61%.
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