Russel Pears
- Artificial Intelligence top 5%
- Information Systems top 5%
- Signal Processing top 5%
- Computer Networks and Communications top 10%
- Management Science and Operations Research top 10%
- Co-authors
- Yun Sing KohM. Asif NaeemAndy M. ConnorGillian DobbieA.C.M. FongStephen G. MacDonellNikola KasabovDilip Kumar Limbu
- Topics
- Data Stream Mining Techniques (16 papers)Time Series Analysis and Forecasting (14 papers)Data Mining Algorithms and Applications (13 papers)
- Journals
- SHILAP Revista de lepidopterologíaExpert Systems with ApplicationsIEEE Access
- Partner nations
- New ZealandPakistanNetherlands
In The Last Decade
Russel Pears
59 papers receiving 538 citations
Peers
Comparison fields: 5 of 99
- Artificial Intelligence 305
- Information Systems 182
- Signal Processing 107
- Computer Networks and Communications 99
- Management Science and Operations Research 61
Countries citing papers authored by Russel Pears
This map shows the geographic impact of Russel Pears'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 Russel Pears with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Russel Pears more than expected).
Fields of papers citing papers by Russel Pears
This network shows the impact of papers produced by Russel Pears. 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 Russel Pears. The network helps show where Russel Pears may publish in the future.
Co-authorship network of co-authors of Russel Pears
This figure shows the co-authorship network connecting the top 25 collaborators of Russel Pears. A scholar is included among the top collaborators of Russel Pears 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 Russel Pears. Russel Pears 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 | 15 | |
| 3 | 6 | |
| 4 | 4 | |
| 5 | 2 | |
| 6 | 7 | |
| 7 | 3 | |
| 8 | 66 | |
| 9 | Dynamic Symbolic Execution Guided by Data Dependency Analysis for High Structural Coverage | 2 |
| 10 | 1 | |
| 11 | Data guided approach to generate multi-dimensional schema for targeted knowledge discovery | 4 |
| 12 | 33 | |
| 13 | 11 | |
| 14 | 0 | |
| 15 | A methodology for integrating and exploiting data mining techniques in the design of data warehouses | 4 |
| 16 | Improving web information retrieval using shared contexts | 2 |
| 17 | Non-redundant rare itemset generation | 1 |
| 18 | Rare association rule mining via transaction clustering | 12 |
| 19 | 0 | |
| 20 | 1 |
About Russel Pears
Russel Pears is a scholar working on Signal Processing, Software and Artificial Intelligence, having authored 61 papers that have together received 568 indexed citations. Recurring topics across this work include Data Stream Mining Techniques (16 papers), Time Series Analysis and Forecasting (14 papers) and Data Mining Algorithms and Applications (13 papers). The work is most often cited by research in Software (50 citations), Signal Processing (107 citations) and Artificial Intelligence (305 citations). Russel Pears has collaborated with scholars based in New Zealand, Pakistan and Netherlands. Frequent co-authors include Yun Sing Koh, M. Asif Naeem, Andy M. Connor, Gillian Dobbie, A.C.M. Fong, Stephen G. MacDonell, Nikola Kasabov, Dilip Kumar Limbu, Wai K. Yeap and Farhaan Mirza. 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.