Titlebook: Semantic Processing of Legal Texts; Where the Language o Enrico Francesconi,Simonetta Montemagni,Daniela Ti Book 2010 Springer-Verlag Berli

Harding

書目名稱Semantic Processing of Legal Texts影響因子(影響力)




書目名稱Semantic Processing of Legal Texts影響因子(影響力)學(xué)科排名




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書目名稱Semantic Processing of Legal Texts網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Semantic Processing of Legal Texts被引頻次




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書目名稱Semantic Processing of Legal Texts年度引用學(xué)科排名




書目名稱Semantic Processing of Legal Texts讀者反饋




書目名稱Semantic Processing of Legal Texts讀者反饋學(xué)科排名

樣式

好色

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

有惡臭

Preserve

表皮

theta-waves

調(diào)情

流利圓滑

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