Neelam Mukhtar
- Artificial Intelligence top 5%
- Sentiment Analysis and Opinion Mining 9
- Advanced Text Analysis Techniques 6
- Topic Modeling 4
- Text and Document Classification Technologies 4
- Imbalanced Data Classification Techniques 2
- Modeling and Simulation top 10%
- Information Systems top 10%
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- Stock Market Forecasting Methods 2
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- IoT and Edge/Fog Computing 2
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- Rough Sets and Fuzzy Logic 2
- Co-authors
- Mohammad Abid KhanShah NazirSara ShahzadRohul AminRahmita Wirza O. K. RahmatMuhammad AhsanIván García‐MagariñoJaime Lloret
- Journals
- SHILAP Revista de lepidopterología (1 paper)Artificial Intelligence Review (1 paper)Telematics and Informatics (1 paper)
In The Last Decade
Neelam Mukhtar
17 papers receiving 312 citations
Peers
Comparison fields: 5 of 53
- Artificial Intelligence 243
- Modeling and Simulation 23
- Numerical Analysis 14
- Information Systems 48
- Management Science and Operations Research 16
Countries citing papers authored by Neelam Mukhtar
This map shows the geographic impact of Neelam Mukhtar'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 Neelam Mukhtar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Neelam Mukhtar more than expected).
Fields of papers citing papers by Neelam Mukhtar
This network shows the impact of papers produced by Neelam Mukhtar. 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 Neelam Mukhtar. The network helps show where Neelam Mukhtar may publish in the future.
Co-authorship network
The 18 scholars most cited alongside Neelam Mukhtar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | 2022 | 8 | |
| 2 | 2021 | 3 | |
| 3 | 2021 | 1 | |
| 4 | 2021 | 8 | |
| 5 | Opinion Mining and Summarization: A Comprehensive Review | 2020 | 3 |
| 6 | 2020 | 3 | |
| 7 | 2020 | 10 | |
| 8 | 2019 | 29 | |
| 9 | 2019 | 6 | |
| 10 | 2019 | 32 | |
| 11 | 2019 | 19 | |
| 12 | 2018 | 79 | |
| 13 | 2018 | 24 | |
| 14 | 2017 | 62 | |
| 15 | 2017 | 27 | |
| 16 | Implementation of Urdu Probabilistic Parser | 2016 | 1 |
| 17 | 2016 | 0 | |
| 18 | Algorithm for developing Urdu Probabilistic Parser | 2012 | 5 |
About Neelam Mukhtar
Neelam Mukhtar is a scholar working on Artificial Intelligence, Health Information Management and Signal Processing, having authored 18 papers that have together received 320 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (9 papers), Advanced Text Analysis Techniques (6 papers), Topic Modeling (4 papers), Text and Document Classification Technologies (4 papers), IoT and Edge/Fog Computing (2 papers), Stock Market Forecasting Methods (2 papers), Rough Sets and Fuzzy Logic (2 papers) and Imbalanced Data Classification Techniques (2 papers). The work is most often cited by research in Artificial Intelligence (243 citations), Modeling and Simulation (23 citations) and Numerical Analysis (14 citations). Neelam Mukhtar has collaborated with scholars based in Pakistan, China and Malaysia. Frequent co-authors include Mohammad Abid Khan, Shah Nazir, Sara Shahzad, Rohul Amin, Rahmita Wirza O. K. Rahmat, Muhammad Ahsan, Iván García‐Magariño, Jaime Lloret, Habib Ullah Khan and Muhammad Shafiq. Their work appears in journals such as SHILAP Revista de lepidopterología, Artificial Intelligence Review and Telematics and Informatics.
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.