Sentiment Classification of Documents in Serbian: The Effects of Morphological Normalization and Word Embeddings

An open issue in the sentiment classification of texts written in Serbian is the effect of different forms of morphological normalization and the usefulness of leveraging large amounts of unlabeled texts. In this paper, we assess the impact of lemmatizers and stemmers for Serbian on classifiers trai...

وصف كامل

التفاصيل البيبلوغرافية
الحاوية / القاعدة:Telfor Journal
المؤلفون الرئيسيون: V. Batanović, B. Nikolić
التنسيق: مقال
اللغة:الإنجليزية
منشور في: Telecommunications Society, Academic Mind 2017-11-01
الموضوعات:
comparative evaluation
lemmatization
morphology
sentiment analysis
stemming
word embeddings
الوصول للمادة أونلاين: http://journal.telfor.rs/Published/Vol9No2/Vol9No2_A6.pdf
الوصف
الملخص:An open issue in the sentiment classification of texts written in Serbian is the effect of different forms of morphological normalization and the usefulness of leveraging large amounts of unlabeled texts. In this paper, we assess the impact of lemmatizers and stemmers for Serbian on classifiers trained and evaluated on the Serbian Movie Review Dataset. We also consider the effectiveness of using word embeddings, generated from a large unlabeled corpus, as classification features.
تدمد:1821-3251

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