短暂
发表于 2025-3-21 18:02:28
书目名称Intelligent Natural Language Processing: Trends and Applications影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0469844<br><br> <br><br>书目名称Intelligent Natural Language Processing: Trends and Applications影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0469844<br><br> <br><br>书目名称Intelligent Natural Language Processing: Trends and Applications网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0469844<br><br> <br><br>书目名称Intelligent Natural Language Processing: Trends and Applications网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0469844<br><br> <br><br>书目名称Intelligent Natural Language Processing: Trends and Applications被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0469844<br><br> <br><br>书目名称Intelligent Natural Language Processing: Trends and Applications被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0469844<br><br> <br><br>书目名称Intelligent Natural Language Processing: Trends and Applications年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0469844<br><br> <br><br>书目名称Intelligent Natural Language Processing: Trends and Applications年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0469844<br><br> <br><br>书目名称Intelligent Natural Language Processing: Trends and Applications读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0469844<br><br> <br><br>书目名称Intelligent Natural Language Processing: Trends and Applications读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0469844<br><br> <br><br>
Measured
发表于 2025-3-21 23:13:22
Studies in Computational Intelligencehttp://image.papertrans.cn/i/image/469844.jpg
Control-Group
发表于 2025-3-22 01:46:36
https://doi.org/10.1007/978-3-319-67056-0Big Data; Natural Language Processing; NLP; Computational Linguistics; Computational Intelligence
大雨
发表于 2025-3-22 04:39:57
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镇压
发表于 2025-3-22 09:20:36
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纪念
发表于 2025-3-22 14:56:27
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homeostasis
发表于 2025-3-22 19:30:17
Using Twitter to Monitor Political Sentiment for Arabic Slangram and bigram) and another time by using feature selection. The main objective of this paper is to measure the accuracy of each method and determine which method is more accurate for Arabic text classification. The results show that unigram and information gain attribute selection achieves the highest accuracy and the lowest error rate.
Addictive
发表于 2025-3-22 22:34:11
The Key Challenges for Arabic Machine Translationfrom handling a complex and rich vocabulary, to designing adequate MT metrics that take morphology into consideration. We present and highlight the key challenges for Arabic language translation into English.
疲劳
发表于 2025-3-23 03:44:35
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招待
发表于 2025-3-23 09:32:28
Book 2018vities concerning the latest advances, techniques, and applications of natural language processing systems, and to promote the exchange of new ideas and lessons learned...Taken together, the chapters of this book provide a collection of high-quality research works that address broad challenges in bo