A Hierarchical Classifier Applied to Multi-way Sentiment Detection
نویسندگان
چکیده
This paper considers the problem of document-level multi-way sentiment detection, proposing a hierarchical classifier algorithm that accounts for the inter-class similarity of tagged sentiment-bearing texts. This type of classifier also provides a natural mechanism for reducing the feature space of the problem. Our results show that this approach improves on state-of-the-art predictive performance for movie reviews with three-star and fourstar ratings, while simultaneously reducing training times and memory requirements.
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