Raja Marappan

974 total citations
55 papers, 589 citations indexed

About

Raja Marappan is a scholar working on Artificial Intelligence, Information Systems and Industrial and Manufacturing Engineering. According to data from OpenAlex, Raja Marappan has authored 55 papers receiving a total of 589 indexed citations (citations by other indexed papers that have themselves been cited), including 16 papers in Artificial Intelligence, 15 papers in Information Systems and 12 papers in Industrial and Manufacturing Engineering. Recurrent topics in Raja Marappan's work include Recommender Systems and Techniques (14 papers), Scheduling and Timetabling Solutions (11 papers) and Vehicle Routing Optimization Methods (11 papers). Raja Marappan is often cited by papers focused on Recommender Systems and Techniques (14 papers), Scheduling and Timetabling Solutions (11 papers) and Vehicle Routing Optimization Methods (11 papers). Raja Marappan collaborates with scholars based in India, United States and Iraq. Raja Marappan's co-authors include Gopalakrishnan Sethumadhavan, Sekar Kidambi Raju, Doaa Sami Khafaga, Amal H. Alharbi, S. K. Towfek, B. Santhi, Osamah Ibrahim Khalaf, Xingsi Xue, Ghaida Muttashar Abdulsahib and M. Rajasekhar Reddy and has published in prestigious journals such as SHILAP Revista de lepidopterología, Sustainability and Computers & Electrical Engineering.

In The Last Decade

Raja Marappan

45 papers receiving 559 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Raja Marappan India 13 209 151 75 59 56 55 589
Alireza Moayedikia Australia 13 220 1.1× 70 0.5× 76 1.0× 42 0.7× 16 0.3× 17 428
Alessandra Mileo Ireland 15 277 1.3× 134 0.9× 21 0.3× 69 1.2× 22 0.4× 49 672
Norita Md Norwawi Malaysia 14 164 0.8× 195 1.3× 33 0.4× 40 0.7× 26 0.5× 86 551
Huazhong Liu China 13 179 0.9× 110 0.7× 23 0.3× 17 0.3× 14 0.3× 36 539
Guiling Li China 13 422 2.0× 106 0.7× 16 0.2× 35 0.6× 34 0.6× 30 665
T. Velmurugan India 14 323 1.5× 133 0.9× 79 1.1× 21 0.4× 9 0.2× 49 616
Jinquan Zhang China 13 226 1.1× 246 1.6× 21 0.3× 72 1.2× 10 0.2× 44 645
Ashraf Osman Ibrahim Malaysia 14 221 1.1× 122 0.8× 7 0.1× 41 0.7× 28 0.5× 72 569
Jong-Yih Kuo Taiwan 13 263 1.3× 295 2.0× 19 0.3× 37 0.6× 20 0.4× 73 562
Malek Alzaqebah Saudi Arabia 15 266 1.3× 73 0.5× 12 0.2× 106 1.8× 126 2.3× 42 566

Countries citing papers authored by Raja Marappan

Since Specialization
Citations

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

Fields of papers citing papers by Raja Marappan

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Raja Marappan

This figure shows the co-authorship network connecting the top 25 collaborators of Raja Marappan. A scholar is included among the top collaborators of Raja Marappan 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 Raja Marappan. Raja Marappan 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
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Marappan, Raja, et al.. (2023). AI-based Smart Healthcare Disease Diagnosis: Analysis & Design of New Model. 7(1). 15–18. 1 indexed citations
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Marappan, Raja, et al.. (2023). Multi-Layered Non-Local Bayes Model for Lung Cancer Early Diagnosis Prediction with the Internet of Medical Things. Bioengineering. 10(2). 138–138. 14 indexed citations
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Marappan, Raja, et al.. (2023). Soldier’s Position Tracking & Health Monitoring Optimization Model Using Biosensors. 1–4. 1 indexed citations
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Xue, Xingsi, Ghaida Muttashar Abdulsahib, M. Rajasekhar Reddy, et al.. (2023). Design and Analysis of a Deep Learning Ensemble Framework Model for the Detection of COVID-19 and Pneumonia Using Large-Scale CT Scan and X-ray Image Datasets. Bioengineering. 10(3). 363–363. 33 indexed citations
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Marappan, Raja, et al.. (2023). Recent Recommender Systems and Analysis of the Machine Learning Public Instances. 83. 1–6. 2 indexed citations
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Xue, Xingsi, et al.. (2023). Modelling and Analysis of Hybrid Transformation for Lossless Big Medical Image Compression. Bioengineering. 10(3). 333–333. 12 indexed citations
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Raju, Sekar Kidambi, et al.. (2023). Evaluation of Mutual Information and Feature Selection for SARS-CoV-2 Respiratory Infection. Bioengineering. 10(7). 880–880. 1 indexed citations
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Marappan, Raja, et al.. (2023). New Machine Learning Model to Movie Recommender and Sentiment Analysis. 9. 363–366.
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Bharathiraja, N., et al.. (2023). New Recommender System for Online Courses Using Knowledge Graph Modeling. 230. 1–6. 2 indexed citations
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Sabri, My Abdelouahed, et al.. (2023). An Automatic Recommendation Process to Generate Learning Paths Based on Learner Preferences. International Journal of Information and Education Technology. 13(10). 1549–1555. 2 indexed citations
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Marappan, Raja, et al.. (2022). Analysis of COVID-19 Prediction Models: Design & Analysis of New Machine Learning Approach. 6(1). 121–126. 6 indexed citations
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Marappan, Raja & Gopalakrishnan Sethumadhavan. (2016). Solution to graph coloring problem using divide and conquer based genetic method. 1–5. 13 indexed citations
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Marappan, Raja & Gopalakrishnan Sethumadhavan. (2013). A New Genetic Algorithm for Graph Coloring. 49–54. 30 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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