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Enhancing the Quality of the Arabic Content for Nursing on Internet

Published: 14 December 2021 Publication History

Editorial Notes

NOTICE OF CONCERN: ACM has received evidence that casts doubt on the integrity of the peer review process for the ICEMIS 2021Conference. As a result, ACM is issuing a Notice of Concern for all papers published and strongly suggests that the papers from this Conference not be cited in the literature until ACM's investigation has concluded and final decisions have been made regarding the integrity of the peer review process for this Conference.

Abstract

A number of international studies have shown that the 52% of web content for nursing area is English and only 1% is Arabic. Although there is a lack of Arabic Nursing content online, almost Arabic nursing content is unstructured and this reflects negatively to the quality of web content. Unstructured web content is resulted from web pages that generated by social networks such as Facebook, Twitters and others.
Thus, a number of recommendations are proposed in this article to enhance the value of Arabic nursing content. It is important increase the percentage of the Arabic content on Internet but the most important is to improve the quality of Arabic nursing content. The main interesting point is to have semi-structured or fully structured Arabic content.
The structured content consists of quality authentic information, quality presentation and quality writing including proper grammar, concise and comprehensive style. Gunupudi et.al [109-129] proposed several machine learning techniques that perform dimensionality reduction and classification in order to improve the performance. However we should work on other elements namely, databases [1-31,41-49], security on Internet [32-40,50-89], e-learning [90-119] and software engineering [120-129].

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[126] Nagaraja, Arun, Gunupudi, Rajesh Kumar, Saravana Kumar, R., Mangathayaru, N., “Optimization of Access Points in Wireless Sensor Network: An Approach towards Security”, Intelligent Systems in Cybernetics and Automation Theory, 2015, Volume 348, pp 299-306
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[127] G. R. Kumar, N. Mangathayaru, G. Narsimha and G. S. Reddy, ”Evolutionary approach for intrusion detection,” 2017 International Conference on Engineering & MIS (ICEMIS), Monastir, 2017, pp. 1-6.
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          ICEMIS'21: The 7th International Conference on Engineering & MIS 2021
          October 2021
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          DOI:10.1145/3492547
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