Harding
发表于 2025-3-21 16:22:06
书目名称Semantic Processing of Legal Texts影响因子(影响力)<br> http://figure.impactfactor.cn/if/?ISSN=BK0864663<br><br> <br><br>书目名称Semantic Processing of Legal Texts影响因子(影响力)学科排名<br> http://figure.impactfactor.cn/ifr/?ISSN=BK0864663<br><br> <br><br>书目名称Semantic Processing of Legal Texts网络公开度<br> http://figure.impactfactor.cn/at/?ISSN=BK0864663<br><br> <br><br>书目名称Semantic Processing of Legal Texts网络公开度学科排名<br> http://figure.impactfactor.cn/atr/?ISSN=BK0864663<br><br> <br><br>书目名称Semantic Processing of Legal Texts被引频次<br> http://figure.impactfactor.cn/tc/?ISSN=BK0864663<br><br> <br><br>书目名称Semantic Processing of Legal Texts被引频次学科排名<br> http://figure.impactfactor.cn/tcr/?ISSN=BK0864663<br><br> <br><br>书目名称Semantic Processing of Legal Texts年度引用<br> http://figure.impactfactor.cn/ii/?ISSN=BK0864663<br><br> <br><br>书目名称Semantic Processing of Legal Texts年度引用学科排名<br> http://figure.impactfactor.cn/iir/?ISSN=BK0864663<br><br> <br><br>书目名称Semantic Processing of Legal Texts读者反馈<br> http://figure.impactfactor.cn/5y/?ISSN=BK0864663<br><br> <br><br>书目名称Semantic Processing of Legal Texts读者反馈学科排名<br> http://figure.impactfactor.cn/5yr/?ISSN=BK0864663<br><br> <br><br>
样式
发表于 2025-3-22 00:16:01
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好色
发表于 2025-3-22 03:06:44
Using Linguistic Information and Machine Learning Techniques to Identify Entities from Juridical Docniques, is described in this paper. In this approach, top-level legal concepts are identified and used for document classification using Support Vector Machines. Named entities, such as, locations, organizations, dates, and document references, are identified using semantic information from the outp
LIEN
发表于 2025-3-22 06:20:19
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有恶臭
发表于 2025-3-22 09:00:02
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Preserve
发表于 2025-3-22 15:27:50
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表皮
发表于 2025-3-22 18:17:04
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theta-waves
发表于 2025-3-22 23:04:31
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调情
发表于 2025-3-23 02:08:36
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流利圆滑
发表于 2025-3-23 06:17:46
Automated Classification of Norms in Sources of Lawisting systems use models that do not reflect the entire law, and simplify parts of the text. These models are difficult to validate, maintain and re-use. We propose to create an intermediate model that has an isomorphic representation of the structure of the original text. A first step towards auto