William Pentney
Impact in
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- Context-Aware Activity Recognition Systems
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- Complex Network Analysis Techniques
Papers in ⓘ
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- Data Management and Algorithms 4
- Time Series Analysis and Forecasting 3
- Co-authors
- Marina Meilă (2 shared papers)Matthai Philipose (4 shared papers)Ana-Maria Popescu (2 shared papers)Tanzeem Choudhury (1 shared paper)Henry Kautz (2 shared papers)Jeff Bilmes (2 shared papers)A.E. Mohr (1 shared paper)Jason D. Hartline (1 shared paper)
- Journals
- Algorithmica (1 paper)National Conference on Artificial Intelligence (4 papers)
- Partner nations
- United States
In The Last Decade
William Pentney
8 papers receiving 286 citations
Peers
Comparison fields: 5 of 51
- Computer Vision and Pattern Recognition 164
- Statistical and Nonlinear Physics 52
- Computer Networks and Communications 95
- Artificial Intelligence 127
- Signal Processing 37
Countries citing papers authored by William Pentney
This map shows the geographic impact of William Pentney'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 William Pentney with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites William Pentney more than expected).
Fields of papers citing papers by William Pentney
This network shows the impact of papers produced by William Pentney. 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 William Pentney. The network helps show where William Pentney may publish in the future.
Co-authors
The 14 scholars most cited alongside William Pentney, 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 | Common sense based joint training of human activity recognizers | 2007 | 102 |
| 2 | 2007 | 67 | |
| 3 | Sensor-based understanding of daily life via large-scale use of common sense | 2006 | 49 |
| 4 | Spectral clustering of biological sequence data | 2005 | 33 |
| 5 | 2005 | 21 | |
| 6 | Learning large scale common sense models of everyday life | 2007 | 20 |
| 7 | Evolving the Semantic Web with Mangrove. | 2003 | 12 |
| 8 | Structure learning on large scale common sense statistical models of human state | 2008 | 8 |
About William Pentney
William Pentney is a scholar working on Signal Processing, Computer Science Applications, Geography, Planning and Development, Computer Vision and Pattern Recognition and Geometry and Topology, having authored 8 papers that have together received 312 indexed citations. Recurring topics across this work include Data Management and Algorithms (4 papers), Time Series Analysis and Forecasting (3 papers), Context-Aware Activity Recognition Systems (3 papers), Complex Network Analysis Techniques (1 paper), Machine Learning in Bioinformatics (1 paper), Data Stream Mining Techniques (1 paper), Bayesian Modeling and Causal Inference (1 paper) and Genomics and Phylogenetic Studies (1 paper). The work is most often cited by research in Computer Vision and Pattern Recognition (164 citations), Statistical and Nonlinear Physics (52 citations), Computer Networks and Communications (95 citations), Artificial Intelligence (127 citations) and Signal Processing (37 citations). William Pentney has collaborated with scholars based in United States. Frequent co-authors include Marina Meilă, Matthai Philipose, Ana-Maria Popescu, Tanzeem Choudhury, Henry Kautz, Jeff Bilmes, A.E. Mohr, Jason D. Hartline, Deepak Kumar Verma and Luke K. McDowell. Their work appears in journals such as Algorithmica and National Conference on Artificial Intelligence.
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.