习惯 发表于 2025-3-21 17:53:39
书目名称Natural Language Processing and Information Systems影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0661834<br><br> <br><br>书目名称Natural Language Processing and Information Systems影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0661834<br><br> <br><br>书目名称Natural Language Processing and Information Systems网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0661834<br><br> <br><br>书目名称Natural Language Processing and Information Systems网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0661834<br><br> <br><br>书目名称Natural Language Processing and Information Systems被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0661834<br><br> <br><br>书目名称Natural Language Processing and Information Systems被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0661834<br><br> <br><br>书目名称Natural Language Processing and Information Systems年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0661834<br><br> <br><br>书目名称Natural Language Processing and Information Systems年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0661834<br><br> <br><br>书目名称Natural Language Processing and Information Systems读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0661834<br><br> <br><br>书目名称Natural Language Processing and Information Systems读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0661834<br><br> <br><br>无所不知 发表于 2025-3-21 22:10:42
Conference proceedings 20212021, held online in July 2021...The 19 full papers and 14 short papers were carefully reviewed and selected from 82 submissions. The papers are organized in the following topical sections: role of learning; methodological approaches; semantic relations; classification; sentiment analysis; social meadroit 发表于 2025-3-22 01:46:33
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Sequence-Based Word Embeddings for Effective Text Classificationh the goal of performing different Natural Language Processing (NLP) tasks. Our experiments demonstrated that DiVe is able to outperform existing (more complex) machine learning approaches, while preserving simplicity and scalability.dominant 发表于 2025-3-22 14:59:38
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NumER: A Fine-Grained Numeral Entity Recognition Datasetinstructions. To demonstrate the use of this dataset, we train a numeral BERT model to detect and categorize numerals in documents. Our baseline model achieves an F1-score of 95% and hence demonstrating that the model can capture the semantic meaning of the numeral tokens.谁在削木头 发表于 2025-3-23 02:18:19
Multiword Expression Features for Automatic Hate Speech Detection tweet corpora with different MWE categories and with two types of MWE embeddings, word2vec and BERT. Our experiments demonstrate that the proposed HSD system with MWE features significantly outperforms the baseline system in terms of macro-F1.业余爱好者 发表于 2025-3-23 05:40:29
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