Titlebook: Computational Linguistics and Intelligent Text Processing; 18th International C Alexander Gelbukh Conference proceedings 2018 Springer Natu

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Supervised?Domain?Adaptation via Label?Alignment for Opinion?Expression?Extractionjections that can improve the performance of a sequence model (e.g. CRF) in the target domain by align features with the true label sequence. We test our methods on product reviews and observe significant improvement in performance in comparison to baseline methods.

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https://doi.org/10.1007/978-3-642-88296-8such significant words as features from the corpus reduces the amount of irrelevant information in the feature set under supervised sentiment classification settings. In this paper, we conceptually study and compare various types of feature building methods, . . test and . for sentiment analysis tas

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Herbert Oertel,Martin B?hle,Ulrich Dohrmannxt, such as tweets (Twitter messages). The paper presents a comparison of three sets of tweets marked for sarcasm, two annotated manually and one annotated using the common strategy of relying on the authors correctly using hashtags to mark sarcasm. To evaluate the difficulty of the datasets, a stat

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