Christopher Ifeanyi Eke
- Artificial Intelligence top 5%
- Information Systems top 5%
- Computer Vision and Pattern Recognition top 10%
- Sociology and Political Science
- Signal Processing top 10%
- Co-authors
- Liyana ShuibAndronicus A. AkinyeluAbsalom E. EzugwuAbiodun M. IkotunLaith AbualigahJeffrey O. AgushakaAzah Anir NormanHenry Friday Nweke
- Topics
- Text and Document Classification Technologies (5 papers)Advanced Malware Detection Techniques (5 papers)Sentiment Analysis and Opinion Mining (4 papers)
- Journals
- PLoS ONEIEEE AccessSolar Energy
In The Last Decade
Christopher Ifeanyi Eke
24 papers receiving 806 citations
Hit Papers
Peers
Comparison fields: 5 of 140
- Artificial Intelligence 399
- Information Systems 139
- Computer Vision and Pattern Recognition 111
- Sociology and Political Science 73
- Signal Processing 72
Countries citing papers authored by Christopher Ifeanyi Eke
This map shows the geographic impact of Christopher Ifeanyi Eke'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 Christopher Ifeanyi Eke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Christopher Ifeanyi Eke more than expected).
Fields of papers citing papers by Christopher Ifeanyi Eke
This network shows the impact of papers produced by Christopher Ifeanyi Eke. 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 Christopher Ifeanyi Eke. The network helps show where Christopher Ifeanyi Eke may publish in the future.
Co-authorship network of co-authors of Christopher Ifeanyi Eke
This figure shows the co-authorship network connecting the top 25 collaborators of Christopher Ifeanyi Eke. A scholar is included among the top collaborators of Christopher Ifeanyi Eke 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 Christopher Ifeanyi Eke. Christopher Ifeanyi Eke is excluded from the visualization to improve readability, since they are connected to all nodes in the network.
All Works
| # | Work | Indexed citations |
|---|---|---|
| 1 | 2 | |
| 2 | 1 | |
| 3 | 0 | |
| 4 | 1 | |
| 5 | 11 | |
| 6 | 2 | |
| 7 | 0 | |
| 8 | 4 | |
| 9 | 6 | |
| 10 | 16 | |
| 11 | 1 | |
| 12 | 7 | |
| 13 | 39 | |
| 14 | A comprehensive survey of clustering algorithms: State-of-the-art machine learning applications, taxonomy, challenges, and future research prospectsbreakdown → | 493 |
| 15 | 1 | |
| 16 | 16 | |
| 17 | 2 | |
| 18 | 1 | |
| 19 | 0 | |
| 20 | 84 |
About Christopher Ifeanyi Eke
Christopher Ifeanyi Eke is a scholar working on Health Informatics, Computer Science Applications and Signal Processing, having authored 28 papers that have together received 841 indexed citations. Recurring topics across this work include Text and Document Classification Technologies (5 papers), Advanced Malware Detection Techniques (5 papers) and Sentiment Analysis and Opinion Mining (4 papers). The work is most often cited by research in Artificial Intelligence (399 citations), Signal Processing (72 citations) and Information Systems (139 citations). Christopher Ifeanyi Eke has collaborated with scholars based in Nigeria, Malaysia and Zambia. Frequent co-authors include Liyana Shuib, Andronicus A. Akinyelu, Absalom E. Ezugwu, Abiodun M. Ikotun, Laith Abualigah, Jeffrey O. Agushaka, Azah Anir Norman, Henry Friday Nweke, Aaron Zimba and Abdelrahman H. Hussein. Their work appears in journals such as PLoS ONE, IEEE Access and Solar Energy.
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.