John K. Tarus
Impact in
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- Online Learning and Analytics
- Information Systems top 1%
- Recommender Systems and Techniques
Papers in
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- Recommender Systems and Techniques 4
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- Imbalanced Data Classification Techniques 2
- Advanced Text Analysis Techniques 1
- Data Stream Mining Techniques 1
- Co-authors
- Zhendong Niu (7 shared papers)Ghulam Mustafa (1 shared paper)Abdallah Yousif (4 shared papers)David Gichoya (2 shared papers)Alex Muumbo (1 shared paper)Arshad Ahmad (1 shared paper)Ghulam Mustafa (2 shared papers)
- Journals
- Artificial Intelligence Review (2 papers)The International Review of Research in Open and Distributed Learning (1 paper)Soft Computing (1 paper)Future Generation Computer Systems (1 paper)The Electronic Journal of Information Systems in Developing Countries (1 paper)
- Partner nations
- ChinaKenyaUnited States
In The Last Decade
John K. Tarus
9 papers receiving 889 citations
John K. Tarus's Hit Papers
Peers
Comparison fields: 5 of 84
- Computer Science Applications 283
- Information Systems 539
- Artificial Intelligence 442
- Information Systems and Management 51
- Computational Mathematics 4
Countries citing papers authored by John K. Tarus
This map shows the geographic impact of John K. Tarus'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 John K. Tarus with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites John K. Tarus more than expected).
Fields of papers citing papers by John K. Tarus
This network shows the impact of papers produced by John K. Tarus. 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 John K. Tarus. The network helps show where John K. Tarus may publish in the future.
Co-authors
The 7 scholars most cited alongside John K. Tarus, 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 | Knowledge-based recommendation: a review of ontology-based recommender systems for e-learning Hit paper breakdown → | 2017 | 310 |
| 2 | A hybrid knowledge-based recommender system for e-learning based on ontology and sequential pattern mining Hit paper breakdown → | 2017 | 200 |
| 3 | 2015 | 194 | |
| 4 | 2017 | 120 | |
| 5 | 2017 | 65 | |
| 6 | 2017 | 23 | |
| 7 | 2015 | 12 | |
| 8 | 2015 | 10 | |
| 9 | 2015 | 6 | |
| 10 | 2017 | 0 | |
| 11 | 2025 | 0 |
About John K. Tarus
John K. Tarus is a scholar working on Information Systems, Artificial Intelligence, Computer Science Applications, Information Systems and Management and Accounting, having authored 11 papers that have together received 940 indexed citations. Recurring topics across this work include Online Learning and Analytics (4 papers), Recommender Systems and Techniques (4 papers), Electricity Theft Detection Techniques (2 papers), Technology Adoption and User Behaviour (2 papers), Imbalanced Data Classification Techniques (2 papers), Online and Blended Learning (2 papers), Advanced Text Analysis Techniques (1 paper) and Data Stream Mining Techniques (1 paper). The work is most often cited by research in Computer Science Applications (283 citations), Information Systems (539 citations), Artificial Intelligence (442 citations), Information Systems and Management (51 citations) and Computational Mathematics (4 citations). John K. Tarus has collaborated with scholars based in China, Kenya and United States. Frequent co-authors include Zhendong Niu, Ghulam Mustafa, Abdallah Yousif, David Gichoya, Alex Muumbo, Arshad Ahmad and Ghulam Mustafa. Their work appears in journals such as Artificial Intelligence Review, The International Review of Research in Open and Distributed Learning, Soft Computing, Future Generation Computer Systems and The Electronic Journal of Information Systems in Developing Countries.
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.