Homocystinuria
发表于 2025-3-26 21:37:11
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贝雷帽
发表于 2025-3-27 04:48:51
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forthy
发表于 2025-3-27 05:27:28
Building Large Arabic Multi-domain Resources for Sentiment Analysisressing: the best performing classifiers and feature representation methods, the effect of introducing lexicon based features and factors affecting the accuracy of sentiment classification in general. All the datasets, experiments code and results have been made publicly available for scientific purposes.
脆弱吧
发表于 2025-3-27 12:52:35
Learning Ranked Sentiment Lexiconstwo large datasets with 703,000 movie reviews and 189,000 hotel reviews showed that the proposed method outperforms the baselines while using a significantly lower dimensional lexicon than other methods.
inhibit
发表于 2025-3-27 14:44:31
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流利圆滑
发表于 2025-3-27 21:34:19
Feature Selection for Twitter Sentiment Analysis: An Experimental Study results in subjectivity classification to the NRC state-of-the-art system with 4 million features that has ranked first in 2013 SemEval competition. Also, our selected features have shown a relative performance gain in the ensemble classification over the baseline of uni-gram and bi-gram features of 9.9% on CrowdScale and 11.9% on SemEval.
TSH582
发表于 2025-3-27 22:45:04
An Iterative Emotion Classification Approach for Microblogsn results converge. Experimental results obtained by three different multi-label classifiers on NLP & CC2013 Chinese microblog emotion classification bakeoff dataset demonstrates the effectiveness of our iterative emotion classification approach.
恃强凌弱
发表于 2025-3-28 04:06:34
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entice
发表于 2025-3-28 08:57:31
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Inordinate
发表于 2025-3-28 11:29:58
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