Santanu Kumar Rath

4.1k total citations · 1 hit paper
143 papers, 2.6k citations indexed

About

Santanu Kumar Rath is a scholar working on Information Systems, Artificial Intelligence and Computer Networks and Communications. According to data from OpenAlex, Santanu Kumar Rath has authored 143 papers receiving a total of 2.6k indexed citations (citations by other indexed papers that have themselves been cited), including 69 papers in Information Systems, 58 papers in Artificial Intelligence and 41 papers in Computer Networks and Communications. Recurrent topics in Santanu Kumar Rath's work include Software Engineering Research (48 papers), Software Reliability and Analysis Research (37 papers) and Software System Performance and Reliability (23 papers). Santanu Kumar Rath is often cited by papers focused on Software Engineering Research (48 papers), Software Reliability and Analysis Research (37 papers) and Software System Performance and Reliability (23 papers). Santanu Kumar Rath collaborates with scholars based in India, Türkiye and Nigeria. Santanu Kumar Rath's co-authors include Abinash Tripathy, A.K. Agrawal, Lov Kumar, Ranjan Kumar Behera, Shashank Mouli Satapathy, Mukesh Kumar, Sanjay Misra, Suchismita Chinara, Monalisa Jena and Ashish Sureka and has published in prestigious journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and Knowledge-Based Systems.

In The Last Decade

Santanu Kumar Rath

134 papers receiving 2.4k citations

Hit Papers

align trajectories

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.

Classification of sentiment reviews using n-gram machine learning approach

2016 417 citations Abinash Tripathy, A.K. Agrawal et al. Expert Systems with Applications profile →

Peers

Santanu Kumar Rath

AI

IS

CNC

SOFTW

MB

Lichao Sun United States

Yucong Duan China

Hareton Leung Hong Kong

Jiqiang Liu China

Behrouz H. Far Canada

Anthony Finkelstein United Kingdom

Ebrahim Bagheri Canada

Jun Han Australia

Ying Zou Canada

Lichao Sun United States

Santanu Kumar Rath

2.3k ×1.9

AI

727 ×0.7

IS

727 ×1.5

CNC

168 ×0.4

SOFTW

123 ×0.8

MB

Citations per year, relative to Santanu Kumar Rath Santanu Kumar Rath (= 1×) peers Lichao Sun

Countries citing papers authored by Santanu Kumar Rath

Since Specialization

Citations

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

Fields of papers citing papers by Santanu Kumar Rath

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Santanu Kumar Rath. 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 Santanu Kumar Rath. The network helps show where Santanu Kumar Rath may publish in the future.

Co-authorship network of co-authors of Santanu Kumar Rath

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

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Rath, Santanu Kumar, et al.. (2021). Real time SOA based credit card fraud detection system using machine learning techniques. 7. 1–6. 1 indexed citations

2.

Rath, Santanu Kumar, et al.. (2020). Core Temperature Estimation for a Cylindrical Cell Battery Module. 1–10. 3 indexed citations

3.

Rath, Santanu Kumar, et al.. (2020). Detection of breast cancer tumours based on feature reduction and classification of thermograms. Quantitative InfraRed Thermography Journal. 18(5). 300–313. 26 indexed citations

4.

Satapathy, Shashank Mouli, et al.. (2016). Early stage software effort estimation using random forest technique based on use case points. IET Software. 10(1). 10–17. 54 indexed citations

5.

Kumar, Mukesh, et al.. (2016). Analysis of microarray leukemia data using an efficient MapReduce-based K-nearest-neighbor classifier. Journal of Biomedical Informatics. 60. 395–409. 21 indexed citations

6.

Tripathy, Abinash, A.K. Agrawal, & Santanu Kumar Rath. (2016). Classification of sentiment reviews using n-gram machine learning approach. Expert Systems with Applications. 57. 117–126. 417 indexed citations breakdown →

7.

Kumar, Lov, et al.. (2016). Analysis of control flow complexity metrics for web service composition. 1. 389–394. 3 indexed citations

8.

Tripathy, Abinash & Santanu Kumar Rath. (2015). Object Oriented Analysis using Natural Language Processing concepts: A\n Review. arXiv (Cornell University).

9.

Kumar, Lov & Santanu Kumar Rath. (2015). A model to assess the effectiveness of fault prediction techniques for quality assurance. 1–6. 3 indexed citations

10.

Rath, Santanu Kumar, et al.. (2015). Formalization of Web Security Patterns. LA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas). 14(1). 14–25. 12 indexed citations

11.

Vipsita, Swati & Santanu Kumar Rath. (2015). Sequence-based protein superfamily classification using computational intelligence techniques: a review. International Journal of Data Mining and Bioinformatics. 11(4). 424–424. 2 indexed citations

12.

Kumar, Lov & Santanu Kumar Rath. (2015). Quality Assessment of Web Services Using Multivariate Adaptive Regression Splines. 238–245. 3 indexed citations

13.

Kumar, Lov & Santanu Kumar Rath. (2015). Predicting Object-Oriented Software Maintainability using Hybrid Neural Network with Parallel Computing Concept. 100–109. 13 indexed citations

14.

Satapathy, Shashank Mouli, et al.. (2014). Early Stage Software Effort Estimation using Random Forest Technique based on Optimized Class Point Approach. Americanae (AECID Library). 1 indexed citations

15.

Kumar, Lov & Santanu Kumar Rath. (2014). Hybrid neural network approach for predicting maintainability of object-oriented software. Americanae (AECID Library). 13(2). 10–21. 2 indexed citations

16.

Satapathy, Shashank Mouli, et al.. (2014). Story Point Approach based Agile Software Effort Estimation using Various SVR Kernel Methods.. Software Engineering and Knowledge Engineering. 304–307. 26 indexed citations

17.

Rath, Santanu Kumar, et al.. (2014). Extended Clique percolation method to detect overlapping community structure. 31–37. 12 indexed citations

18.

Vipsita, Swati & Santanu Kumar Rath. (2013). Two-Stage Approach for Protein Superfamily Classification. 2013. 1–12. 11 indexed citations

19.

Rath, Santanu Kumar, et al.. (2009). Gene Expression Analysis Using Clustering. International Journal of Computer and Electrical Engineering. 155–164. 3 indexed citations

20.

Rath, Santanu Kumar, Jagdish C. Patra, & Alex C. Kot. (2002). An intelligent pressure sensor with self-calibration capability using artificial neural networks. Swinburne Research Bank (Swinburne University of Technology). 4. 2563–2568. 6 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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