Zobrazeno 1 - 10
of 120
pro vyhledávání: '"Ashraf Elnagar"'
Autor:
Sane Yagi, Shehdeh Fareh, Ashraf Elnagar, Mariam Balajeed, Abdalla El-mneizel, Mohammad Al-Badawi
Publikováno v:
Cogent Arts & Humanities, Vol 11, Iss 1 (2024)
AbstractThis paper investigates the extent to which Arabic punctuation is rule-governed, with the aim of improving text comprehension, disambiguation, and machine translation. The study highlights the lack of systematic punctuation in Arabic written
Externí odkaz:
https://doaj.org/article/310ef3c8c6aa494d926aee5780a1877b
Publikováno v:
Intelligent Systems with Applications, Vol 22, Iss , Pp 200376- (2024)
abstract: This research aims to detect different types of Arabic offensive language in twitter. It uses a multiclass classification system in which each tweet is categorized into one or more of the offensive language types based on the used word(s).
Externí odkaz:
https://doaj.org/article/a78d35efa6104da0bd7f0836eccc1cd1
Publikováno v:
Data in Brief, Vol 53, Iss , Pp 110118- (2024)
Arabic, unlike many languages, suffers from punctuation inconsistency, posing a significant obstacle for Natural Language Processing (NLP). To address this, we present the Arabic Punctuation Dataset (APD), a large collection of annotated Modern Stand
Externí odkaz:
https://doaj.org/article/5aec1c8383514c87b32b3eb8ffd3e542
Autor:
Osama Ahmad Alomari, Ashraf Elnagar, Imad Afyouni, Ismail Shahin, Ali Bou Nassif, Ibrahim Abaker Hashem, Mohammad Tubishat
Publikováno v:
IEEE Access, Vol 10, Pp 121816-121830 (2022)
The rapid growth of electronic documents has resulted from the expansion and development of internet technologies. Text-documents classification is a key task in natural language processing that converts unstructured data into structured form and the
Externí odkaz:
https://doaj.org/article/09af1c0b11134b3a97018a12bc0b07ae
Publikováno v:
International Journal of Data and Network Science, Vol 6, Iss 3, Pp 669-682 (2022)
There are various reasons why vaccine fear has resulted in public rejection. Students have raised concerns about vaccine effectiveness, leading to hesitation when it comes to vaccination. Vaccination apprehension impacts students' perceptions, which
Externí odkaz:
https://doaj.org/article/ae672ebbcc684d61ab8dd1c2ab9f89df
Publikováno v:
IEEE Access, Vol 9, Pp 31010-31042 (2021)
It is becoming increasingly difficult to know who is working on what and how in computational studies of Dialectal Arabic. This study comes to chart the field by conducting a systematic literature review that is intended to give insight into the most
Externí odkaz:
https://doaj.org/article/786196e681f541e6aed6ea528ed4acd4
Publikováno v:
Jordanian Journal of Computers and Information Technology, Vol 06, Iss 03, Pp 263-280 (2020)
Text classification is the process of automatically tagging a textual document with the most relevant set of labels. The aim of this work is to automatically tag an input document based on its vocabulary features. To achieve this goal, two large data
Externí odkaz:
https://doaj.org/article/b6cdb70484fd43088067f27595edbaf3
Publikováno v:
Informatics in Medicine Unlocked, Vol 29, Iss , Pp 100913- (2022)
This study makes use of a cohesive yet innovative research model to identify the determinants of the adoption of smart watches using constructs from the Technology Acceptance Model (TAM) and constructs of smartwatches, including effectiveness, conten
Externí odkaz:
https://doaj.org/article/e181801d0e75470bb518193a9851169c
Publikováno v:
Mathematics, Vol 11, Iss 2, p 459 (2023)
Capsule Neural Network (CapsNet) models are regarded as efficient substitutes for convolutional neural networks (CNN) due to their powerful hierarchical representation capability. Nevertheless, CNN endure their inability of recording spatial informat
Externí odkaz:
https://doaj.org/article/5c2f78caeb4e40c888570090524700c9
Autor:
Ammar Kamal Abasi, Sharif Naser Makhadmeh, Mohammed Azmi Al-Betar, Osama Ahmad Alomari, Mohammed A. Awadallah, Zaid Abdi Alkareem Alyasseri, Iyad Abu Doush, Ashraf Elnagar, Eman H. Alkhammash, Myriam Hadjouni
Publikováno v:
Applied Sciences, Vol 12, Iss 19, p 10057 (2022)
The Lemur Optimizer (LO) is a novel nature-inspired algorithm we propose in this paper. This algorithm’s primary inspirations are based on two pillars of lemur behavior: leap up and dance hub. These two principles are mathematically modeled in the
Externí odkaz:
https://doaj.org/article/9f2e9ea348ca4d8f8ca11cb789203156