Legal knowledge based systems
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Legal knowledge based systems JURIX "95 : telecommunication and AI & law

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Published by Koninklijke Vermande in Lelystad .
Written in English

Subjects:

  • Law -- Methodology -- Data processing -- Congresses.,
  • Artificial intelligence -- Congresses.,
  • Expert systems (Computer science) -- Congresses.,
  • Technology and law -- Congresses.,
  • Telecommunication -- Law and legislation -- Congresses.

Book details:

Edition Notes

Other titlesJURIX "95, Telecommunication and AI & law, Telecommunication and AI and law
Statementthe Foundation for Legal Knowledge Systems ; editors, J.C. Hage ... [et. al.].
ContributionsHage, J. C., Foundation for Legal Knowledge Systems.
Classifications
LC ClassificationsK212 .L444 1995
The Physical Object
Pagination141 p. :
Number of Pages141
ID Numbers
Open LibraryOL561554M
ISBN 109054582529
LC Control Number96145473

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A legal expert system is a domain-specific expert system that uses artificial intelligence to emulate the decision-making abilities of a human expert in the field of law.: Legal expert systems employ a rule base or knowledge base and an inference engine to accumulate, reference and produce expert knowledge on specific subjects within the legal domain. Get this from a library! Legal knowledge based systems: JURIX ' foundations of legal knowledge systems. [Robert W Van Kralingen; Foundation for Legal Knowledge Systems. Conference] -- Papers presented at JURIX '96 conference held on Decem in Tilburg, The Netherlands. A knowledge-based system (KBS) is a system that uses artificial intelligence techniques in problem-solving processes to support human decision-making, learning, and action. Ideal for advanced-undergraduate and graduate students, as well as business professionals, this text is designed to help users develop an appreciation of KBS and their architecture and understand 5/5(1). Legal Knowledge Management: Insights and Practice on *FREE* shipping on qualifying offers. Legal Knowledge Management: Insights and PracticeFormat: Paperback.

  This book compiles the experience of the largest project in knowledge-based systems and the law yet undertaken. It provides an in-depth introduction to representation of law in computer programs, as well as more advanced discussion and description of large knowledge-based systems building, legal representation, cooperative work, and interface Book Edition: 1. Knowledge-based Systems is an international and interdisciplinary journal in the field of artificial intelligence. The journal will publish original, innovative and creative research results in the field, and is designed to focus on research in knowledge-based and other artificial intelligence techniques-based systems with the following objectives and capabilities: to support human . a better analysis and better systems later on. 3. Legal knowledge engineering: what are the problems? All approaches to legal knowledge engineering have as an implicit and general goal the development of (better) legal knowledge-based systems (KBS). This implies two categories of problems. The first category consists of knowledge engineering and.   Favorit Book Knowledge-based Systems and Legal Applications (APIC) Online. aswewrrew. Full version Knowledge-based Systems and Legal Applications (APIC) Any Format. gospomurti. Best ebook Knowledge-based Systems and Legal Applications (APIC) For Full. Raze.

Subject: Overig (niet-programmatisch) onderzoek: Organization: onbekend/nvt. Centrum voor MigratierechtCited by: knowledge based systems JURIX The Foundation for Legal Knowledge Systems, Lelystad: Koninklijke Vermande, , pp. , ISBN 90 5. More information about the JURIX foundation and its activities can be obtained by. KNOWLEDGE. Information as to a fact. 2. Many acts are perfectly innocent when the party performing them is not aware of certain circumstances attending them for example, a man may pass a counterfeit note and be guiltless, if he did not know it was so he may receive stolen goods if he were not aware of the fact that they were stolen. CiteScore: ℹ CiteScore: CiteScore measures the average citations received per document published in this title. CiteScore values are based on citation counts in a given year (e.g. ) to documents published in three previous calendar years (e.g. – 14), divided by the number of documents in these three previous years (e.g. – 14).