El‐Sayed Atlam

898 total citations
46 papers, 555 citations indexed

About

El‐Sayed Atlam is a scholar working on Artificial Intelligence, Information Systems and Computer Vision and Pattern Recognition. According to data from OpenAlex, El‐Sayed Atlam has authored 46 papers receiving a total of 555 indexed citations (citations by other indexed papers that have themselves been cited), including 34 papers in Artificial Intelligence, 15 papers in Information Systems and 5 papers in Computer Vision and Pattern Recognition. Recurrent topics in El‐Sayed Atlam's work include Natural Language Processing Techniques (16 papers), Advanced Text Analysis Techniques (12 papers) and Text and Document Classification Technologies (9 papers). El‐Sayed Atlam is often cited by papers focused on Natural Language Processing Techniques (16 papers), Advanced Text Analysis Techniques (12 papers) and Text and Document Classification Technologies (9 papers). El‐Sayed Atlam collaborates with scholars based in Japan, Egypt and Saudi Arabia. El‐Sayed Atlam's co-authors include Ibrahim Gad, Jun‐ichi Aoe, Ashraf A. Ewis, Masao Fuketa, Osama A. Ghoneim, Amer Malki, Guesh Dagnew, Kazuhiro Morita, M. M. Abd El‐Raouf and Zohair Malki and has published in prestigious journals such as IEEE Access, Information Sciences and Neural Computing and Applications.

In The Last Decade

El‐Sayed Atlam

42 papers receiving 516 citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
El‐Sayed Atlam Japan 14 268 132 56 47 46 46 555
Hasan Rashaideh Jordan 8 178 0.7× 166 1.3× 77 1.4× 16 0.3× 28 0.6× 15 738
M.A. Chyad Malaysia 9 330 1.2× 124 0.9× 39 0.7× 28 0.6× 37 0.8× 12 823
Aijaz Ahmad Reshi Saudi Arabia 10 398 1.5× 81 0.6× 152 2.7× 55 1.2× 31 0.7× 20 795
Stephen Gbenga Fashoto Eswatini 16 148 0.6× 182 1.4× 56 1.0× 50 1.1× 11 0.2× 41 738
Vibhakar Mansotra India 13 237 0.9× 67 0.5× 114 2.0× 23 0.5× 23 0.5× 58 592
María Óskarsdóttir Iceland 14 274 1.0× 95 0.7× 27 0.5× 76 1.6× 14 0.3× 48 865
Vedika Gupta India 14 302 1.1× 84 0.6× 37 0.7× 49 1.0× 15 0.3× 47 695
Shahin Jabbari United States 9 356 1.3× 71 0.5× 52 0.9× 88 1.9× 18 0.4× 16 830
Lilian Berton Brazil 13 379 1.4× 79 0.6× 15 0.3× 44 0.9× 58 1.3× 51 682
André Panisson Italy 15 143 0.5× 79 0.6× 59 1.1× 36 0.8× 17 0.4× 35 730

Countries citing papers authored by El‐Sayed Atlam

Since Specialization
Citations

This map shows the geographic impact of El‐Sayed Atlam's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by El‐Sayed Atlam with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites El‐Sayed Atlam more than expected).

Fields of papers citing papers by El‐Sayed Atlam

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by El‐Sayed Atlam. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by El‐Sayed Atlam. The network helps show where El‐Sayed Atlam may publish in the future.

Co-authorship network of co-authors of El‐Sayed Atlam

This figure shows the co-authorship network connecting the top 25 collaborators of El‐Sayed Atlam. A scholar is included among the top collaborators of El‐Sayed Atlam based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with El‐Sayed Atlam. El‐Sayed Atlam is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Atlam, El‐Sayed, et al.. (2025). Optimized AI and IoT-Driven Framework for Intelligent Water Resource Management. IEEE Access. 13. 97628–97646. 1 indexed citations
2.
Atlam, El‐Sayed, et al.. (2024). SLM-DFS: A systematic literature map of deepfake spread on social media. Alexandria Engineering Journal. 111. 446–455. 5 indexed citations
3.
Alwateer, Majed, El‐Sayed Atlam, M. M. Abd El‐Raouf, Osama A. Ghoneim, & Ibrahim Gad. (2024). Missing Data Imputation: A Comprehensive Review. Journal of Computer and Communications. 12(11). 53–75. 14 indexed citations
4.
Malki, Amer, El‐Sayed Atlam, Aboul Ella Hassanien, et al.. (2022). SARIMA model-based forecasting required number of COVID-19 vaccines globally and empirical analysis of peoples’ view towards the vaccines. Alexandria Engineering Journal. 61(12). 12091–12110. 13 indexed citations
5.
Noor, Talal H., Abdulqader M. Almars, El‐Sayed Atlam, & Ayman Noor. (2022). Deep Learning Model for Predicting Consumers’ Interests of IoT Recommendation System. International Journal of Advanced Computer Science and Applications. 13(10). 8 indexed citations
6.
Malki, Amer, El‐Sayed Atlam, & Ibrahim Gad. (2022). Machine learning approach of detecting anomalies and forecasting time-series of IoT devices. Alexandria Engineering Journal. 61(11). 8973–8986. 36 indexed citations
7.
Noor, Talal H., El‐Sayed Atlam, Abdulqader M. Almars, Ayman Noor, & Amer Malki. (2022). An IoT-Based Energy Conservation Smart Classroom System. Intelligent Automation & Soft Computing. 35(3). 3785–3799. 4 indexed citations
8.
Mohammed, Zeinab, et al.. (2021). Psychological problems among the university students in Saudi Arabia during the COVID‐19 pandemic. International Journal of Clinical Practice. 75(11). e14853–e14853. 18 indexed citations
9.
Malki, Zohair, El‐Sayed Atlam, Ashraf A. Ewis, et al.. (2020). ARIMA models for predicting the end of COVID-19 pandemic and the risk of second rebound. Neural Computing and Applications. 33(7). 2929–2948. 88 indexed citations
10.
Malki, Zohair, et al.. (2020). Bidirectional Residual LSTM-based Human Activity Recognition. Computer and Information Science. 13(3). 40–40. 21 indexed citations
11.
Atlam, El‐Sayed, et al.. (2017). A new retrieval method based on time series variation using field association terms. Mathematical Methods in the Applied Sciences. 41(15). 5780–5791. 5 indexed citations
12.
Atlam, El‐Sayed, et al.. (2013). An Efficient Method of Summarizing Documents Using Impression Measurements. Computing and Informatics / Computers and Artificial Intelligence. 32(2). 371–391.
13.
Atlam, El‐Sayed, Kazuhiro Morita, Masao Fuketa, & Jun‐ichi Aoe. (2011). A new approach for Arabic text classification using Arabic field‐association terms. Journal of the American Society for Information Science and Technology. 62(11). 2266–2276. 2 indexed citations
14.
Atlam, El‐Sayed. (2008). A NEW APPROACH FOR TEXT SIMILARITY USING ARTICLES. International Journal of Information Technology & Decision Making. 7(1). 23–34. 5 indexed citations
15.
Atlam, El‐Sayed, et al.. (2007). Ranking of field association terms using Co-word analysis. Information Processing & Management. 44(2). 738–755. 46 indexed citations
16.
Atlam, El‐Sayed, et al.. (2006). A New Algorithm for Construction Specific Field Terms Using Co-occurrence Words Information. 2. 990–993. 1 indexed citations
17.
Atlam, El‐Sayed, et al.. (2005). Automatic building of new Field Association word candidates using search engine. Information Processing & Management. 42(4). 951–962. 18 indexed citations
18.
Atlam, El‐Sayed, et al.. (2005). Knowledge discovery method to accomplish english document classification. 39. 268–268. 1 indexed citations
19.
Atlam, El‐Sayed, et al.. (2003). An evaluation method of words tendency using decision tree. 2. 129–132.
20.
Atlam, El‐Sayed, Makoto Okada, Masami Shishibori, & Jun‐ichi Aoe. (2002). An evaluation method of words tendency depending on time-series variation and its improvements. Information Processing & Management. 38(2). 157–171. 4 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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