Amira M. Idrees
-
- Online Learning and Analytics 7
- Information Systems top 5%
- Data Mining Algorithms and Applications 7
- Spam and Phishing Detection 6
- Management Information Systems top 10%
- Big Data and Business Intelligence 7
- Artificial Intelligence top 10%
- Sentiment Analysis and Opinion Mining 8
- Advanced Text Analysis Techniques 6
- Data Stream Mining Techniques 6
- Marketing top 10%
- Customer churn and segmentation 5
- Co-authors
- Ayman E. KhedrHesham HassanMaryam HazmanMahmoud A. MahmoudHesham A. HefnyMahmoud OthmanAbdulwahab Ali AlmazroiIrfan Ahmed
- Journals
- SHILAP Revista de lepidopterología (2 papers)Expert Systems with Applications (1 paper)IEEE Access (4 papers)
- Partner nations
- EgyptSaudi Arabia
In The Last Decade
Amira M. Idrees
52 papers receiving 425 citations
Peers
Comparison fields: 5 of 74
- Computer Science Applications 66
- Information Systems 165
- Management Information Systems 62
- Artificial Intelligence 200
- Marketing 53
Countries citing papers authored by Amira M. Idrees
This map shows the geographic impact of Amira M. Idrees'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 Amira M. Idrees with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Amira M. Idrees more than expected).
Fields of papers citing papers by Amira M. Idrees
This network shows the impact of papers produced by Amira M. Idrees. 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 Amira M. Idrees. The network helps show where Amira M. Idrees may publish in the future.
Co-authorship network
The 18 scholars most cited alongside Amira M. Idrees, 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 | 2025 | 0 | |
| 2 | 2024 | 1 | |
| 3 | 2024 | 0 | |
| 4 | 2023 | 10 | |
| 5 | 2023 | 3 | |
| 6 | 2023 | 7 | |
| 7 | 2023 | 2 | |
| 8 | 2023 | 2 | |
| 9 | 2023 | 18 | |
| 10 | 2023 | 1 | |
| 11 | 2023 | 3 | |
| 12 | 2022 | 3 | |
| 13 | 2022 | 1 | |
| 14 | 2021 | 1 | |
| 15 | Reforming Home Energy Consumption Behavior based on Mining Techniques, A Collaborative Home Appliances Approach | 2020 | 2 |
| 16 | 2020 | 5 | |
| 17 | 2019 | 11 | |
| 18 | 2016 | 7 | |
| 19 | 2016 | 10 | |
| 20 | Sampling technique selection framework for knowledge discovery | 2010 | 11 |
About Amira M. Idrees
Amira M. Idrees is a scholar working on Computer Science Applications, Information Systems and Management Information Systems, having authored 57 papers that have together received 432 indexed citations. Recurring topics across this work include Sentiment Analysis and Opinion Mining (8 papers), Online Learning and Analytics (7 papers), Data Mining Algorithms and Applications (7 papers), Big Data and Business Intelligence (7 papers), Spam and Phishing Detection (6 papers), Advanced Text Analysis Techniques (6 papers), Data Stream Mining Techniques (6 papers) and Customer churn and segmentation (5 papers). The work is most often cited by research in Computer Science Applications (66 citations), Information Systems (165 citations) and Management Information Systems (62 citations). Amira M. Idrees has collaborated with scholars based in Egypt and Saudi Arabia. Frequent co-authors include Ayman E. Khedr, Hesham Hassan, Maryam Hazman, Mahmoud A. Mahmoud, Hesham A. Hefny, Mahmoud Othman, Abdulwahab Ali Almazroi, Irfan Ahmed, Mohamed Abdelsalam and Wael H. Gomaa. Their work appears in journals such as SHILAP Revista de lepidopterología, Expert Systems with Applications and IEEE Access.
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.