Francesconi, E., Montemagni, S., Peters, W., Tiscornia, D. (Eds.)
2010, XII, 249p. 42 illus..
Springer eBooks may be purchased by end-customers only and are sold without copy protection (DRM free). Instead, all eBooks include personalized watermarks. This means you can read the Springer eBooks across numerous devices such as Laptops, eReaders, and tablets.
You can pay for Springer eBooks with Visa, Mastercard, American Express or Paypal.
After the purchase you can directly download the eBook file or read it online in our Springer eBook Reader. Furthermore your eBook will be stored in your MySpringer account. So you can always re-download your eBooks.
ThelegaldomainrepresentsaprimarycandidateforWeb-basedinformationd- tribution,exchangeandmanagement,astesti?edbythenumerouse-government, e-justice and e-democracy initiatives worldwide. The last few years have seen a growing body of research and practice in the ?eld of arti?cial intelligence and law addressing aspects such as automated legal reasoning and argumentation, semantic and cross-languagelegalinformation retrieval, document classi?cation, legal drafting, legal knowledge discovery and extraction. Many e?orts have also been devoted to the construction of legal ontologies and their application to the law domain. A number of di?erent workshops and conferences have been organized on these topics in the framework of the arti?cial intelligence and law community: among them, the ICAIL (International Conference on Arti?cial Intelligence and Law) and the Jurix (International Conference on Legal Knowledge and Inf- mation Systems) conferences; several workshops on legal ontologies have been held by the AI&Law Association (LOAIT) and by the Legal XML Community (LegalXMLWorkshopsandLegalXML Summer School).In allthese events,the topics of languageresourcesand human language technologiesreceiveincreasing attention. The situation is quite di?erent within the computational linguistics com- nity, where little attention has been paid to the legal domain besides a few isolated contributions and/or projects focussing on the processing of legal texts.
Content Level »Professional/practitioner
Keywords »argumentation - artificial intelligence - classification - corpus - information extraction - information retrieval - intelligence - knowledge - knowledge discovery - knowledge representation
Legal Text Processing and Information Extraction.- Legal Language and Legal Knowledge Management Applications.- Named Entity Recognition and Resolution in Legal Text.- Using Linguistic Information and Machine Learning Techniques to Identify Entities from Juridical Documents.- Approaches to Text Mining Arguments from Legal Cases.- Legal Text Processing and Construction of Knowledge Resources.- Automatic Identification of Legal Terms in Czech Law Texts.- Integrating a Bottom–Up and Top–Down Methodology for Building Semantic Resources for the Multilingual Legal Domain.- Ontology Based Law Discovery.- Multilevel Legal Ontologies.- Legal Text Processing and Semantic Indexing, Summarization and Translation.- Semantic Indexing of Legal Documents.- Automated Classification of Norms in Sources of Law.- Efficient Multilabel Classification Algorithms for Large-Scale Problems in the Legal Domain.- An Automatic System for Summarization and Information Extraction of Legal Information.- Evaluation Metrics for Consistent Translation of Japanese Legal Sentences.