Naresh Kumar Nagwani
- Artificial Intelligence top 5%
- Information Systems top 2%
- Computer Networks and Communications top 10%
- Signal Processing top 10%
- Software top 5%
- Co-authors
- Shrish VermaAakanksha SharaffPradeep SinghDilip Singh SisodiaMithilesh AtulkarTirath Prasad SahuSanjay ChakrabortyLopamudra Dey
- Topics
- Software Engineering Research (28 papers)Topic Modeling (15 papers)Text and Document Classification Technologies (12 papers)
In The Last Decade
Naresh Kumar Nagwani
93 papers receiving 781 citations
Hit Papers
Peers
Comparison fields: 5 of 101
- Artificial Intelligence 423
- Information Systems 411
- Computer Networks and Communications 163
- Signal Processing 100
- Software 94
Countries citing papers authored by Naresh Kumar Nagwani
This map shows the geographic impact of Naresh Kumar Nagwani'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 Naresh Kumar Nagwani with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Naresh Kumar Nagwani more than expected).
Fields of papers citing papers by Naresh Kumar Nagwani
This network shows the impact of papers produced by Naresh Kumar Nagwani. 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 Naresh Kumar Nagwani. The network helps show where Naresh Kumar Nagwani may publish in the future.
Co-authorship network of co-authors of Naresh Kumar Nagwani
This figure shows the co-authorship network connecting the top 25 collaborators of Naresh Kumar Nagwani. A scholar is included among the top collaborators of Naresh Kumar Nagwani 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 Naresh Kumar Nagwani. Naresh Kumar Nagwani is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 3 | |
| 2 | 3 | |
| 3 | 0 | |
| 4 | 2 | |
| 5 | 3 | |
| 6 | 7 | |
| 7 | 17 | |
| 8 | 2 | |
| 9 | 1 | |
| 10 | 1 | |
| 11 | Impact of word embedding models on text analytics in deep learning environment: a reviewbreakdown → | 107 |
| 12 | 8 | |
| 13 | 8 | |
| 14 | 2 | |
| 15 | 4 | |
| 16 | 11 | |
| 17 | 1 | |
| 18 | An Agile Methodology Based Model for Change- Oriented Software Engineering | 3 |
| 19 | Weather Forecasting using Incremental K-means Clustering | 10 |
| 20 | An Open Source Framework for Data Pre-processing of Online Software Bug Repositories | 2 |
About Naresh Kumar Nagwani
Naresh Kumar Nagwani is a scholar working on Software, Information Systems and Artificial Intelligence, having authored 106 papers that have together received 850 indexed citations. Recurring topics across this work include Software Engineering Research (28 papers), Topic Modeling (15 papers) and Text and Document Classification Technologies (12 papers). The work is most often cited by research in Software (94 citations), Information Systems (411 citations) and Artificial Intelligence (423 citations). Naresh Kumar Nagwani has collaborated with scholars based in India, Lebanon and Jordan. Frequent co-authors include Shrish Verma, Aakanksha Sharaff, Pradeep Singh, Dilip Singh Sisodia, Mithilesh Atulkar, Tirath Prasad Sahu, Sanjay Chakraborty, Lopamudra Dey, Shirish V. Deo and Sarsij Tripathi. Their work appears in journals such as Expert Systems with Applications, IEEE Access and IEEE Transactions on Knowledge and Data Engineering.
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.