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- W2106976443 abstract "We present a new feature type named rating-based feature and evaluate the contribution of this feature to the task of document-level sentiment analysis. We achieve state-of-the-art results on two publicly available standard polarity movie datasets: on the dataset consisting of 2000 reviews produced by Pang and Lee (2004) we obtain an accuracy of 91.6% while it is 89.87% evaluated on the dataset of 50000 reviews created by Maas et al. (2011). We also get a performance at 93.24% on our own dataset consisting of 233600 movie reviews, and we aim to share this dataset for further research in sentiment polarity analysis task." @default.
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- W2106976443 date "2014-01-01" @default.
- W2106976443 modified "2023-09-24" @default.
- W2106976443 title "Sentiment Classification on Polarity Reviews: An Empirical Study Using Rating-based Features" @default.
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- W2106976443 doi "https://doi.org/10.3115/v1/w14-2621" @default.
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