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Identifying Explicit Features for Sentiment Analysis in Consumer Reviews

机译:识别消费者评论中情感分析的显式功能

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With the number of reviews growing every day, it has become more important for both consumers and producers to gather the information that these reviews contain in an effective way. For this, a well performing feature extraction method is needed. In this paper we focus on detecting explicit features. For this purpose, we use grammatical relations between words in combination with baseline statistics of words as found in the review text. Compared to three investigated existing methods for explicit feature detection, our method significantly improves the F_1-measure on three publicly available data sets.
机译:随着评论数量每天都在增长,对于消费者和生产者而言,有效收集这些评论所包含的信息变得越来越重要。为此,需要一种性能良好的特征提取方法。在本文中,我们专注于检测显式特征。为此,我们将单词之间的语法关系与评论文本中的单词基线统计结合起来使用。与研究的三种用于显式特征检测的现有方法相比,我们的方法显着改进了三个公开数据集上的F_1量度。

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