Sheetal Girase

588 total citations
14 papers, 295 citations indexed

About

Sheetal Girase is a scholar working on Information Systems, Artificial Intelligence and Computer Vision and Pattern Recognition. According to data from OpenAlex, Sheetal Girase has authored 14 papers receiving a total of 295 indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Information Systems, 6 papers in Artificial Intelligence and 3 papers in Computer Vision and Pattern Recognition. Recurrent topics in Sheetal Girase's work include Recommender Systems and Techniques (6 papers), Sentiment Analysis and Opinion Mining (3 papers) and Spam and Phishing Detection (2 papers). Sheetal Girase is often cited by papers focused on Recommender Systems and Techniques (6 papers), Sentiment Analysis and Opinion Mining (3 papers) and Spam and Phishing Detection (2 papers). Sheetal Girase collaborates with scholars based in India. Sheetal Girase's co-authors include Debajyoti Mukhopadhyay and Ranjana Yadav and has published in prestigious journals such as Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation, Procedia Computer Science and 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA).

In The Last Decade

Sheetal Girase

13 papers receiving 272 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Sheetal Girase India 6 230 119 88 36 30 14 295
Bogdan Walek Czechia 6 181 0.8× 118 1.0× 53 0.6× 18 0.5× 26 0.9× 33 267
Miguel A. Rueda-Morales Spain 6 244 1.1× 89 0.7× 97 1.1× 36 1.0× 24 0.8× 7 280
Yan‐Shuo Chang China 6 183 0.8× 130 1.1× 98 1.1× 23 0.6× 14 0.5× 15 283
Inay Ha South Korea 6 231 1.0× 81 0.7× 90 1.0× 23 0.6× 43 1.4× 15 299
Diane Hu United States 8 182 0.8× 164 1.4× 63 0.7× 57 1.6× 19 0.6× 16 286
Ramjeevan Singh Thakur India 9 147 0.6× 167 1.4× 63 0.7× 22 0.6× 20 0.7× 43 340
Hansu Gu United States 14 237 1.0× 201 1.7× 67 0.8× 18 0.5× 13 0.4× 51 360
João Vinagre Portugal 11 179 0.8× 139 1.2× 57 0.6× 67 1.9× 13 0.4× 24 261
P. Dolan United States 3 350 1.5× 214 1.8× 118 1.3× 70 1.9× 16 0.5× 3 446

Countries citing papers authored by Sheetal Girase

Since Specialization
Citations

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

Fields of papers citing papers by Sheetal Girase

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Sheetal Girase

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

All Works

14 of 14 papers shown
1.
Girase, Sheetal, et al.. (2025). Review of sentiment analysis in social media using big data: techniques, tools, and frameworks. International Journal of Basic and Applied Sciences. 14(2). 34–48.
2.
Girase, Sheetal, et al.. (2021). Project Based Learning Methodology: An Effective Way of learning Software Engineering through Database Design and Web Technology Project. Journal of Engineering Education/Journal of engineering education transformations/Journal of engineering education transformation. 34(0). 375–375. 3 indexed citations
3.
Girase, Sheetal, et al.. (2018). A Study on Application Scenario of Video Summarization. 2018 Second International Conference on Electronics, Communication and Aerospace Technology (ICECA). 936–943. 3 indexed citations
5.
Girase, Sheetal, et al.. (2017). Analysing recommendation of colleges for students using data mining techniques. 1–5. 4 indexed citations
6.
Mukhopadhyay, Debajyoti, et al.. (2016). User Profiling for University Recommender System Using Automatic Information Retrieval. Procedia Computer Science. 78. 5–12. 14 indexed citations
7.
9.
Girase, Sheetal, et al.. (2015). Performance analysis of classification and ranking techniques. 1. 1–6. 1 indexed citations
10.
Girase, Sheetal, et al.. (2015). Introducing Hybrid Technique for Optimization of Book Recommender System. Procedia Computer Science. 45. 23–31. 33 indexed citations
11.
Girase, Sheetal, et al.. (2015). A Survey of various Web Page Ranking Algorithms. International Journal of Computer Applications. 132(10). 30–35. 2 indexed citations
12.
Girase, Sheetal, et al.. (2015). Matrix Factorization Model in Collaborative Filtering Algorithms: A Survey. Procedia Computer Science. 49. 136–146. 193 indexed citations
13.
Girase, Sheetal, et al.. (2012). Comparison of various Elicitation Techniques and Requirement Prioritisation Techniques. 1(3). 13 indexed citations
14.
Yadav, Ranjana, et al.. (2011). A Review of Heat Pipe Systems for Heat Recovery and Renewable Energy Application. International Journal of Current Engineering and Technology. 4 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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