Tahani Alsubait

606 total citations
31 papers, 296 citations indexed

About

Tahani Alsubait is a scholar working on Artificial Intelligence, Information Systems and Computer Science Applications. According to data from OpenAlex, Tahani Alsubait has authored 31 papers receiving a total of 296 indexed citations (citations by other indexed papers that have themselves been cited), including 20 papers in Artificial Intelligence, 8 papers in Information Systems and 6 papers in Computer Science Applications. Recurrent topics in Tahani Alsubait's work include Natural Language Processing Techniques (8 papers), Intelligent Tutoring Systems and Adaptive Learning (5 papers) and Educational Technology and Assessment (5 papers). Tahani Alsubait is often cited by papers focused on Natural Language Processing Techniques (8 papers), Intelligent Tutoring Systems and Adaptive Learning (5 papers) and Educational Technology and Assessment (5 papers). Tahani Alsubait collaborates with scholars based in Saudi Arabia, United Kingdom and Pakistan. Tahani Alsubait's co-authors include Ulrike Sattler, Bijan Parsia, Hosam Alhakami, Abdullah Baz, Alaa M. Alqahtani, Mohammed A. Al Ghamdi, Ahmad M. Alghamdi, Eisa Alanazi, Alaa E. Abdel-Hakim and Mazin Alshamrani and has published in prestigious journals such as SHILAP Revista de lepidopterología, Scientific Reports and IEEE Access.

In The Last Decade

Tahani Alsubait

26 papers receiving 278 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Tahani Alsubait Saudi Arabia 11 169 88 67 36 32 31 296
Kamal Eddine El Kadiri Morocco 7 174 1.0× 148 1.7× 45 0.7× 49 1.4× 13 0.4× 18 339
Vu Minh Hieu Phan Australia 9 243 1.4× 38 0.4× 73 1.1× 24 0.7× 77 2.4× 23 393
Selver Softic Austria 8 79 0.5× 80 0.9× 65 1.0× 48 1.3× 16 0.5× 32 203
Asif Nawaz Pakistan 9 110 0.7× 80 0.9× 53 0.8× 22 0.6× 22 0.7× 32 227
Veronika Stoffová Slovakia 11 89 0.5× 60 0.7× 147 2.2× 62 1.7× 39 1.2× 60 311
Tzer‐Long Chen Taiwan 10 130 0.8× 134 1.5× 12 0.2× 15 0.4× 20 0.6× 37 283
Hapnes Toba Indonesia 10 140 0.8× 160 1.8× 86 1.3× 32 0.9× 22 0.7× 60 329
Umi Laili Yuhana Indonesia 9 121 0.7× 170 1.9× 34 0.5× 54 1.5× 26 0.8× 102 301
Zhiyun Ren United States 7 90 0.5× 90 1.0× 110 1.6× 19 0.5× 12 0.4× 16 195
Yu‐Liang Chi Taiwan 8 142 0.8× 72 0.8× 38 0.6× 12 0.3× 15 0.5× 26 245

Countries citing papers authored by Tahani Alsubait

Since Specialization
Citations

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

Fields of papers citing papers by Tahani Alsubait

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Tahani Alsubait. 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 Tahani Alsubait. The network helps show where Tahani Alsubait may publish in the future.

Co-authorship network of co-authors of Tahani Alsubait

This figure shows the co-authorship network connecting the top 25 collaborators of Tahani Alsubait. A scholar is included among the top collaborators of Tahani Alsubait 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 Tahani Alsubait. Tahani Alsubait 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.
Alsubait, Tahani, et al.. (2026). An intelligent life prediction approach employing machine learning models for the power transformers. Scientific Reports. 16(1). 4016–4016.
2.
Alsubait, Tahani, et al.. (2025). Enhancing Crowd Safety at Hajj: Real-Time Detection of Abnormal Behavior Using YOLOv9. IEEE Access. 13. 37748–37761.
3.
Abdel-Hakim, Alaa E., et al.. (2025). Toward an Integrated Intelligent Framework for Crowd Control and Management (IICCM). IEEE Access. 13. 58559–58575.
4.
Alsubait, Tahani, et al.. (2025). An enhanced framework for real-time dense crowd abnormal behavior detection using YOLOv8. Artificial Intelligence Review. 58(7). 1 indexed citations
5.
Alsubait, Tahani, et al.. (2024). Evaluation of machine learning-based regression techniques for prediction of diabetes levels fluctuations. Heliyon. 11(1). e41199–e41199. 3 indexed citations
6.
Alhakami, Hosam, Hosam Alhakami, Tahani Alsubait, et al.. (2023). Advancing Sustainable Healthcare through Enhanced Therapeutic Communication with Elderly Patients in the Kingdom of Saudi Arabia. Sustainability. 15(22). 15778–15778.
7.
Alqahtani, Alaa M., Hosam Alhakami, Tahani Alsubait, & Abdullah Baz. (2021). A Survey of Text Matching Techniques. SHILAP Revista de lepidopterología. 11(1). 6656–6661. 18 indexed citations
8.
Alhakami, Hosam, et al.. (2020). A Comparison of EDM Tools and Techniques. International Journal of Advanced Computer Science and Applications. 11(12). 5 indexed citations
9.
Alsubait, Tahani, et al.. (2020). A Review of Optimization Algorithms for University Timetable Scheduling. SHILAP Revista de lepidopterología. 10(6). 6410–6417. 20 indexed citations
10.
Alhakami, Hosam, et al.. (2020). Data Mining for Student Advising. International Journal of Advanced Computer Science and Applications. 11(3). 5 indexed citations
11.
Alsubait, Tahani, et al.. (2020). Sentiment Analysis of Arabic Reviews for Saudi Hotels Using Unsupervised Machine Learning. Journal of Computer Science. 16(9). 1258–1267. 5 indexed citations
12.
Alhakami, Hosam, et al.. (2020). Educational Data Mining Applications and Techniques. International Journal of Advanced Computer Science and Applications. 11(4). 25 indexed citations
13.
Alsubait, Tahani. (2015). ONTOLOGY-BASED MULTIPLE-CHOICE QUESTION GENERATION. Research Explorer (The University of Manchester). 3 indexed citations
14.
Alsubait, Tahani, Bijan Parsia, & Ulrike Sattler. (2015). Ontology-Based Multiple Choice Question Generation. KI - Künstliche Intelligenz. 30(2). 183–188. 35 indexed citations
15.
Alsubait, Tahani, Bijan Parsia, & Ulrike Sattler. (2014). Measuring Conceptual Similarity in Ontologies: How Bad is a Cheap Measure?. Research Explorer (The University of Manchester). 365–377. 1 indexed citations
16.
Alsubait, Tahani, Bijan Parsia, & Ulrike Sattler. (2014). Generating multiple choice questions from ontologies: Lessons learnt. Research Explorer (The University of Manchester). 73–84. 26 indexed citations
17.
Alsubait, Tahani, Bijan Parsia, & Ulrike Sattler. (2014). Generating Multiple Questions From Ontologies: How Far Can We Go?. 1 indexed citations
18.
Alsubait, Tahani, Bijan Parsia, & Ulrike Sattler. (2012). Mining Ontologies for Analogy Questions: A Similarity-based Approach.. Research Explorer (The University of Manchester). 13 indexed citations
19.
Alsubait, Tahani, Bijan Parsia, & Ulrike Sattler. (2012). Next generation of e-assessment: automatic generation of questions. International Journal of Technology Enhanced Learning. 4(3/4). 156–156. 7 indexed citations
20.
Alsubait, Tahani, Bijan Parsia, & Ulrike Sattler. (2012). Automatic generation of analogy questions for student assessment: an Ontology-based approach. Research in Learning Technology. 20(sup1). 19198–19198. 12 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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