Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/6458
Title: Information Extraction from Arabic Law Documents
Authors: Samah Abu Shamma 
Aseel Ayasa 
Wala’ Sleem 
Adnan Yahya 
Keywords: Natural language processing (Computer science) - Arabic Language;Data mining - Data processing;Named Entity Recognition;Named Entity Recognition, Arabic;Natural language processing, Arabic;Information extrcation, Arabic
Issue Date: 16-Dec-2020
Publisher: IEEE
Source: Samah Abu Shamma, Aseel Ayasa, Wala’ Sleem and Adnan Yahya. Information Extraction from Arabic Law Documents. The 14th IEEE International Conference Application of Information and Communication Technologies (AICT2020). 07-09 Oct 2020 | Tashkent, Uzbekistan
Conference: The 14th IEEE International Conference Application of Information and Communication Technologies 07-09 Oct 2020 | Tashkent, Uzbekistan 
Abstract: Information hidden in unstructured or semi-structured law documents can be very useful but may not be readily accessible. To get this information, an information extraction (IE) system is needed. Making extracted information available in structured form enables answering complex queries that may go well beyond simple keyword search and thus may be of interest to law professionals. In this paper we address the issue of Arabic information extraction from law documents. We describe a system we developed to extract important information, that may be of interest to potential users of these documents, with minimal human intervention. We employs a hybrid approach that utilizes machine learning and rule-based methods and Arabic NLP to facilitate the extraction of needed information. The approach was applied to a limited class of Arabic law documents and we are working on extending it to other document types and to other fields.
URI: http://hdl.handle.net/20.500.11889/6458
Appears in Collections:Fulltext Publications

Files in This Item:
File Description SizeFormat
ExtractionFromLawDocs2020CameraReadyV3.pdf662.35 kBAdobe PDFView/Open
Show full item record

Google ScholarTM

Check


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.