@inproceedings{e1863890f35c4e33abac4d88d1d97243,
title = "Noun Extraction Tool for ANLP Applications",
abstract = "Noun is a word representing an idea, a thing, a person or a place. Identifying nouns in Arabic texts is an important task in many Arabic Natural Language Processing (ANLP) applications. This paper presents a noun extraction system that extracts nouns according to Arabic grammar rules. The system was evaluated against the widely used Stanford Arabic Part of Speech (POS) tagger. The results show that our proposed method is more efficient and achieves benchmark accuracies.",
keywords = "ANLP, Arabic, Arabic Natural Language Processing, Information Retrieval, Noun Extraction, Text Summarization, text summarization",
author = "\{Al Qassem\}, Lamees and Di Wang and Hassan Barada",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 12th IEEE International Conference on Semantic Computing, ICSC 2018 ; Conference date: 31-01-2018 Through 02-02-2018",
year = "2018",
month = apr,
day = "9",
doi = "10.1109/ICSC.2018.00060",
language = "British English",
series = "Proceedings - 12th IEEE International Conference on Semantic Computing, ICSC 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "308--309",
booktitle = "Proceedings - 12th IEEE International Conference on Semantic Computing, ICSC 2018",
address = "United States",
}