Eleanor Selfridge-Field
- Signal Processing top 2%
- Computer Vision and Pattern Recognition top 5%
- Music top 1%
- Cognitive Neuroscience
- Artificial Intelligence
- Co-authors
- Craig Stuart SappYiwen LiuH. C. Robbins LandonMira BalabanClaude V. PaliscaCraig ListerKemal Ebci̇oğluOtto Laske
- Topics
- Music and Audio Processing (26 papers)Music Technology and Sound Studies (26 papers)Diverse Musicological Studies (26 papers)
- Journals
- SHILAP Revista de lepidopterologíaThe American Historical ReviewComputer Music Journal
- Partner nations
- United States
In The Last Decade
Eleanor Selfridge-Field
40 papers receiving 285 citations
Peers
Comparison fields: 5 of 56
- Signal Processing 273
- Computer Vision and Pattern Recognition 265
- Music 92
- Cognitive Neuroscience 92
- Artificial Intelligence 49
Countries citing papers authored by Eleanor Selfridge-Field
This map shows the geographic impact of Eleanor Selfridge-Field'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 Eleanor Selfridge-Field with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Eleanor Selfridge-Field more than expected).
Fields of papers citing papers by Eleanor Selfridge-Field
This network shows the impact of papers produced by Eleanor Selfridge-Field. 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 Eleanor Selfridge-Field. The network helps show where Eleanor Selfridge-Field may publish in the future.
Co-authorship network of co-authors of Eleanor Selfridge-Field
This figure shows the co-authorship network connecting the top 25 collaborators of Eleanor Selfridge-Field. A scholar is included among the top collaborators of Eleanor Selfridge-Field 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 Eleanor Selfridge-Field. Eleanor Selfridge-Field 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 | Music analysis : east and west | 2 |
| 3 | Modeling Music as Markov Chains: Composer Identiflcation | 2 |
| 4 | Music Query: Methods, Models, and User Studies (Computing in Musicology) | 4 |
| 5 | Towards a Measure of Cognitive Distance in Melodic Similarity | 3 |
| 6 | 10 | |
| 7 | Conceptual and representational issues in melodic comparison | 55 |
| 8 | Melodic Similarity : concepts, procedures, and applications | 63 |
| 9 | Introduction: describing musical information | 1 |
| 10 | Beyond codes: issues in musical representation | 1 |
| 11 | DARMS , its dialects, and its uses | 1 |
| 12 | 0 | |
| 13 | 3 | |
| 14 | 2 | |
| 15 | 1 | |
| 16 | 1 | |
| 17 | 1 | |
| 18 | 1 | |
| 19 | 1 | |
| 20 | 3 |
About Eleanor Selfridge-Field
Eleanor Selfridge-Field is a scholar working on Music, Signal Processing and General Arts and Humanities, having authored 53 papers that have together received 399 indexed citations. Recurring topics across this work include Music and Audio Processing (26 papers), Music Technology and Sound Studies (26 papers) and Diverse Musicological Studies (26 papers). The work is most often cited by research in Music (92 citations), Signal Processing (273 citations) and Computer Vision and Pattern Recognition (265 citations). Eleanor Selfridge-Field has collaborated with scholars based in United States. Frequent co-authors include Craig Stuart Sapp, Yiwen Liu, H. C. Robbins Landon, Mira Balaban, Claude V. Palisca, Craig Lister, Kemal Ebci̇oğlu, Otto Laske, Cláudio Sartori and Craig Harris. Their work appears in journals such as SHILAP Revista de lepidopterología, The American Historical Review and Computer Music Journal.
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.