Please use this identifier to cite or link to this item: http://hdl.handle.net/20.500.11889/5684
Title: Information extraction from Arabic law documents
Authors: Abu Shamma, Samah
Ayasa, Aseel
Sleem, Wala
Yahya, Adnan
Keywords: Information retrieval - Automation
Legal documents - Computer programs
Machine learning - Technique
Artificial intelligence
Electronic data processing
Issue Date: 1-Jul-2018
Abstract: Information hidden in unstructured or semi-structured documents can be quite useful. To pull this information, an information extraction system is needed. Making extracted information available in structured format enables answering more complex queries of interest to law professionals. In this paper we address the issue of Arabic information extraction from law documents. We describe a system that extracts some important information of interest to potential users of these documents with minimal human intervention. The system employs a hybrid approach that utilizes machine learning and rule based approaches to extract the needed information from the texts.
Description: Information extraction from Arabic law documents Mar 2017 – Present Project description It's Samah Abu Shamma graduation project. It extracts some useful information from Arabic legal documents for people how are interested in law field. Project brief description : It takes a raw (.txt) file legal file and it extracts from it the name of the judge/s, lawyer/s, parties ( plaintiffs and defendants ) and the case's verdict. Machine Learning techniques and rule based approach are used to build the Extraction system.
URI: http://hdl.handle.net/20.500.11889/5684
Appears in Collections:Fulltext Publications (BZU Community)

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