Automatic Arabic Summarization: A survey of methodologies and systems
Author(s) -
Lamees M. Al Qassem,
Di Wang,
Zaid Al Mahmoud,
Hassan Barada,
Ahmad Alrubaie,
Nawaf Almoosa
Publication year - 2017
Publication title -
procedia computer science
Language(s) - English
Resource type - Journals
ISSN - 1877-0509
DOI - 10.1016/j.procs.2017.10.088
Subject(s) - automatic summarization , computer science , multi document summarization , arabic , natural language processing , grammar , information retrieval , field (mathematics) , social media , artificial intelligence , world wide web , linguistics , philosophy , mathematics , pure mathematics
Text summarization has been a field of intensive research over the last 50 years, especially for commonly-used and relatively simple-grammar languages such as English. Moreover, the unprecedented growth in the amount of online information available in many languages to users and businesses, including news articles and social media, has made it difficult and time consuming for users to identify and consume sought after content. Hence, an automatic text summarization for various languages to generate accurate and relevant summaries from the huge amount of information available is essential nowadays. Techniques and methodologies for Arabic text summarization are still immature due to the inherent complexity of the Arabic language in terms of both structure and morphology. This paper describes the main challenges for Arabic text summarization and surveys the various methodologies and systems in the literature. This survey would be a good basis for the design of an Arabic automatic text summarization that combines the various “good” features of the existing systems and dismiss the “not-so-good” features.
Accelerating Research
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom
Address
John Eccles HouseRobert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom