Luai Al-Shalabi

905 total citations · 1 hit paper
13 papers, 622 citations indexed

About

Luai Al-Shalabi is a scholar working on Information Systems, Artificial Intelligence and Computational Theory and Mathematics. According to data from OpenAlex, Luai Al-Shalabi has authored 13 papers receiving a total of 622 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Information Systems, 6 papers in Artificial Intelligence and 4 papers in Computational Theory and Mathematics. Recurrent topics in Luai Al-Shalabi's work include Data Mining Algorithms and Applications (5 papers), Rough Sets and Fuzzy Logic (4 papers) and Spam and Phishing Detection (2 papers). Luai Al-Shalabi is often cited by papers focused on Data Mining Algorithms and Applications (5 papers), Rough Sets and Fuzzy Logic (4 papers) and Spam and Phishing Detection (2 papers). Luai Al-Shalabi collaborates with scholars based in Kuwait, Jordan and Hong Kong. Luai Al-Shalabi's co-authors include Zyad Shaaban and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Journal of Computer Science.

In The Last Decade

Luai Al-Shalabi

10 papers receiving 583 citations

Hit Papers

Data Mining: A Preprocessing Engine 2006 2026 2012 2019 2006 100 200 300 400
What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

  1. Data Mining: A Preprocessing Engine
    2006 426 citations Luai Al-Shalabi, Zyad Shaaban et al. Journal of Computer Science profile →

Peers

Luai Al-Shalabi
Zyad Shaaban Saudi Arabia
Youssef Ghanou Morocco
Ying Cao China
Dharmender Kumar India
Nittaya Kerdprasop Thailand
Kittisak Kerdprasop Thailand
Haoyue Liu China
Amelia Ritahani Ismail Malaysia
Zyad Shaaban Saudi Arabia
Luai Al-Shalabi
Citations per year, relative to Luai Al-Shalabi Luai Al-Shalabi (= 1×) peers Zyad Shaaban

Countries citing papers authored by Luai Al-Shalabi

Since Specialization
Citations

This map shows the geographic impact of Luai Al-Shalabi'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 Luai Al-Shalabi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Luai Al-Shalabi more than expected).

Fields of papers citing papers by Luai Al-Shalabi

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Luai Al-Shalabi. 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 Luai Al-Shalabi. The network helps show where Luai Al-Shalabi may publish in the future.

Co-authorship network of co-authors of Luai Al-Shalabi

This figure shows the co-authorship network connecting the top 25 collaborators of Luai Al-Shalabi. A scholar is included among the top collaborators of Luai Al-Shalabi 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 Luai Al-Shalabi. Luai Al-Shalabi is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

13 of 13 papers shown
1.
Al-Shalabi, Luai, et al.. (2024). Phishing detection using clustering and machine learning. IAES International Journal of Artificial Intelligence. 13(4). 4526–4526.
2.
Al-Shalabi, Luai. (2024). Hybrid feature selection based ScC and forward selection methods. International Journal of Data and Network Science. 8(2). 1117–1128. 1 indexed citations
3.
Al-Shalabi, Luai. (2022). New Feature Selection Algorithm Based on Feature Stability and Correlation. IEEE Access. 10. 4699–4713. 8 indexed citations
4.
Al-Shalabi, Luai, et al.. (2021). A WGFS Based Approach to Extract Factors Influencing the Marketing of Korean Language in GCC. SHILAP Revista de lepidopterología. 28(3). 165–181.
5.
Al-Shalabi, Luai. (2019). Rough set-based reduction of incomplete medical datasets by reducing the number of missing values.. The International Arab Journal of Information Technology. 16. 203–210. 1 indexed citations
6.
Al-Shalabi, Luai. (2019). A Data Mining Model for Students’ Choice of College Major Based on Rough Set Theory. Journal of Computer Science. 15(8). 1150–1160. 2 indexed citations
7.
Al-Shalabi, Luai. (2019). Comparative Study of Data Mining Classification Techniques for Detection and Prediction of Phishing Websites. Journal of Computer Science. 15(3). 384–394. 4 indexed citations
8.
Al-Shalabi, Luai. (2010). Knowledge Discovery Process: Guide Lines for New Researchers. 4(1). 21–28. 3 indexed citations
9.
Al-Shalabi, Luai. (2009). Improving Accuracy and Coverage of Data Mining Systems that are Built from Noisy Datasets: A New Model. Journal of Computer Science. 5(2). 131–135. 3 indexed citations
10.
Al-Shalabi, Luai, et al.. (2008). Building ontological relationships: A new approach. Journal of the American Society for Information Science and Technology. 59(11). 1801–1809. 6 indexed citations
11.
Al-Shalabi, Luai, et al.. (2006). A framework to Deal with Missing Data in Data Sets. Journal of Computer Science. 2(9). 740–745. 11 indexed citations
12.
Al-Shalabi, Luai, et al.. (2006). Data Mining: A Preprocessing Engine. Journal of Computer Science. 2(9). 735–739. 426 indexed citations breakdown →
13.
Al-Shalabi, Luai & Zyad Shaaban. (2006). Normalization as a Preprocessing Engine for Data Mining and the Approach of Preference Matrix. 207–214. 157 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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