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|Title||Semantically Enriched Derivation of Legal Advice in the Palestinian Labour Domain|
|Title in Arabic||الاشتقاق المعزز دلاليا للاستشارة القانونية في مجال العمل الفلسطيني|
The Palestinian labour legal law is a rich and complex field with various parts, chapters and articles and is related to other articles and laws. Working with such legal domain to derive legal advice using traditional methods such as face-to-face meetings between the lawyer and the worker is time consuming and does not guarantee the retrieval of useful information and legal cases related to the required advice. Recent technologies and techniques pertinent to information management and retrieval, such as semantic web techniques based on ontology and related knowledge bases, can strongly benefit the legal domain. In this research, we build a semantically enriched approach for the derivation of legal advice in the labour domain based on the Palestinian labour law. We design and build a domain ontology called LabourLawOnt together with a knowledge base for the labour law. The ontology contains terms, relationships, and object and data properties. The set of parts, chapters and articles of the labour law together with various legal cases are added as instances to the ontology to form the legal knowledge base. Also a set of semantic (SWRL) rules are defined and written to be used to infer new knowledge from the knowledge base. The approach is realized through a system prototype designed and implemented as a prove of the concept for the approach including the ontology, the SWRL rules, the knowledge base, a reasoner and a user interface. The system, respectively the approach, is evaluated with the help of a domain expert using 150 legal cases divided into two sets. The first set contains 100 cases entered to the system by the expert and the second set contains 50 cases previously entered as instances in the knowledge base. The results show a success rate of 77% correct legal advice cases related to child labour, a success rate of 80% correct legal advice cases related to women labour, and a success rate of 87.5% correct legal advice cases related to the end of service benefits. The overall accuracy of the system in correctly giving the legal advice is 84%. Keywords: Labour Law, Legal, Semantic Web, SWRL rule, OWL, Inference Engine.
|Publisher||الجامعة الإسلامية - غزة|
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