Choo‐Yee Ting

955 total citations
50 papers, 556 citations indexed

About

Choo‐Yee Ting is a scholar working on Artificial Intelligence, Computer Science Applications and Information Systems. According to data from OpenAlex, Choo‐Yee Ting has authored 50 papers receiving a total of 556 indexed citations (citations by other indexed papers that have themselves been cited), including 19 papers in Artificial Intelligence, 14 papers in Computer Science Applications and 12 papers in Information Systems. Recurrent topics in Choo‐Yee Ting's work include Online Learning and Analytics (14 papers), Intelligent Tutoring Systems and Adaptive Learning (8 papers) and Innovative Teaching and Learning Methods (6 papers). Choo‐Yee Ting is often cited by papers focused on Online Learning and Analytics (14 papers), Intelligent Tutoring Systems and Adaptive Learning (8 papers) and Innovative Teaching and Learning Methods (6 papers). Choo‐Yee Ting collaborates with scholars based in Malaysia and Singapore. Choo‐Yee Ting's co-authors include Somnuk Phon-Amnuaisuk, Kok–Chin Khor, Khairil Imran Ghauth, Ian K. T. Tan, Chee-Onn Wong, Adeeba Kamarulzaman, Alvin Kuo Jing Teo, Timothy William, Fadzilah Kamaludin and Michelle Chan and has published in prestigious journals such as SHILAP Revista de lepidopterología, IEEE Access and Computers & Education.

In The Last Decade

Choo‐Yee Ting

44 papers receiving 506 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Choo‐Yee Ting Malaysia 13 202 157 117 96 80 50 556
Pablo de la Fuente Spain 12 108 0.5× 131 0.8× 143 1.2× 60 0.6× 98 1.2× 49 662
Pierluigi Ritrovato Italy 13 270 1.3× 129 0.8× 63 0.5× 176 1.8× 208 2.6× 51 769
Yusep Rosmansyah Indonesia 14 126 0.6× 119 0.8× 127 1.1× 74 0.8× 176 2.2× 91 534
Atta Badii United Kingdom 16 187 0.9× 55 0.4× 29 0.2× 118 1.2× 147 1.8× 93 735
Hwa‐Young Jeong South Korea 16 163 0.8× 65 0.4× 31 0.3× 222 2.3× 236 3.0× 87 732
Eitel J. M. Lauría United States 10 214 1.1× 327 2.1× 32 0.3× 58 0.6× 87 1.1× 23 580
Jānis Grundspeņķis Latvia 12 228 1.1× 68 0.4× 61 0.5× 24 0.3× 189 2.4× 71 498
José Antonio Gutiérrez Spain 13 114 0.6× 127 0.8× 94 0.8× 33 0.3× 220 2.8× 52 599
Adriana S. Vivacqua Brazil 11 123 0.6× 76 0.5× 32 0.3× 56 0.6× 122 1.5× 98 467
Álvaro Figueira Portugal 9 231 1.1× 151 1.0× 34 0.3× 35 0.4× 198 2.5× 58 696

Countries citing papers authored by Choo‐Yee Ting

Since Specialization
Citations

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

Fields of papers citing papers by Choo‐Yee Ting

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Choo‐Yee Ting. 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 Choo‐Yee Ting. The network helps show where Choo‐Yee Ting may publish in the future.

Co-authorship network of co-authors of Choo‐Yee Ting

This figure shows the co-authorship network connecting the top 25 collaborators of Choo‐Yee Ting. A scholar is included among the top collaborators of Choo‐Yee Ting 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 Choo‐Yee Ting. Choo‐Yee Ting 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.
Ting, Choo‐Yee, et al.. (2024). Predicting graduate-on-time using machine learning. AIP conference proceedings. 3153. 20003–20003. 1 indexed citations
2.
Ting, Choo‐Yee, et al.. (2024). Behavioural user segmentation of app users based on functionality interaction patterns. Cogent Engineering. 11(1).
3.
Ting, Choo‐Yee, et al.. (2024). Leveraging LLMs for optimised feature selection and embedding in structured data: A case study on graduate employment classification. Computers and Education Artificial Intelligence. 8. 100356–100356. 1 indexed citations
4.
Ting, Choo‐Yee, et al.. (2024). A Multilingual BERT Embeddings Approach in Identifying Factors Influencing Employability Among Pre-University Students. Siti Hasmah Digital Library-MMU Institutiona Repository (Multimedia University). 130–135.
5.
Ting, Choo‐Yee, et al.. (2023). No-Show Passenger Prediction for Flights. SHILAP Revista de lepidopterología. 7(3-2). 2056–2056. 1 indexed citations
6.
7.
Ting, Choo‐Yee, et al.. (2022). Geospatial Features Influencing the Formation of COVID-19 Clusters. Journal of System and Management Sciences. 3 indexed citations
8.
Teo, Alvin Kuo Jing, et al.. (2022). Characterisation of COVID-19 deaths by vaccination types and status in Malaysia between February and September 2021. The Lancet Regional Health - Western Pacific. 18. 100354–100354. 8 indexed citations
9.
Teo, Alvin Kuo Jing, et al.. (2022). Risk stratification and assessment framework for international travel and border measures amidst the COVID-19 pandemic – A Malaysian perspective. Travel Medicine and Infectious Disease. 47. 102318–102318. 4 indexed citations
10.
Ting, Choo‐Yee, et al.. (2020). Performance Evaluation of Explainable Machine Learning on Non-Communicable Diseases. Solid State Technology. 2780–2793. 2 indexed citations
11.
Ting, Choo‐Yee, et al.. (2020). Geospatial Insights for Retail Recommendation Using Similarity Measures. Big Data. 8(6). 519–527. 1 indexed citations
12.
Ting, Choo‐Yee, et al.. (2019). Retail Site Selection using Machine Learning Algorithms. International Journal of Recent Technology and Engineering (IJRTE). 8(4). 2422–2431. 2 indexed citations
13.
Ting, Choo‐Yee, et al.. (2018). Analytic hierarchy process (AHP) for business site selection. AIP conference proceedings. 2016. 20151–20151. 25 indexed citations
14.
Ting, Choo‐Yee, et al.. (2018). Geospatial Analytics in Retail Site Selection and Sales Prediction. Big Data. 6(1). 42–52. 19 indexed citations
15.
Ting, Choo‐Yee, et al.. (2015). Dataset of scientific inquiry learning environment. British Journal of Educational Technology. 46(5). 1038–1050. 2 indexed citations
16.
Ting, Choo‐Yee, et al.. (2012). A Push-Pull Chunk Delivery for Mesh-Based P2P Live Streaming. IEICE Transactions on Information and Systems. E95.D(12). 2958–2959.
17.
Ting, Choo‐Yee, Kok–Chin Khor, & Somnuk Phon-Amnuaisuk. (2010). Features and Bayesian Network Model of Conceptual Change for INQPRO. 2. 305–309. 2 indexed citations
18.
Khor, Kok–Chin, Choo‐Yee Ting, & Somnuk Phon-Amnuaisuk. (2009). From Feature Selection to Building of Bayesian Classifiers: A Network Intrusion Detection Perspective. American Journal of Applied Sciences. 6(11). 1948–1959. 18 indexed citations
19.
Ting, Choo‐Yee & Somnuk Phon-Amnuaisuk. (2009). Optimal dynamic decision network model for scientific inquiry learning environment. Applied Intelligence. 33(3). 387–406. 4 indexed citations
20.
Ting, Choo‐Yee, et al.. (2008). Modeling and intervening across time in scientific inquiry exploratory learning environment. Educational Technology & Society. 11(3). 239–258. 5 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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2026