A Comparative Review of Machine Learning for Arabic Named Entity Recognition

Ramzi Esmail Salah, Lailatul Qadri binti Zakaria
2017 International Journal on Advanced Science, Engineering and Information Technology  
Arabic Named Entity Recognition (ANER) systems aim to identify and classify Arabic Named entities (NEs) within Arabic text. Other important tasks in Arabic Natural Language Processing (NLP) depends on ANER such as machine translation, questionanswering, information extraction, etc. In general, ANER systems can be classified into three main approaches, namely, rule-based, machine-learning or hybrid systems. In this paper, we focus on research progress in machine-learning (ML) ANER and compare
more » ... ween linguistic resource, entity type, domain, method, and performance. We also highlight the challenges when processing Arabic NEs through ML systems.
doi:10.18517/ijaseit.7.2.1810 fatcat:ygldyzkm6rdpffsux5fqb7ywy4