Rodger J. McNab

1.4k citations
23 papers · 894 indexed · h-index 12

Rodger J. McNab

22 papers receiving 743 citations

Peers

Rodger J. McNab
Comparison fields: 5 of 63
  • Signal Processing 501
  • Computer Vision and Pattern Recognition 503
  • Music 57
  • Information Systems 218
  • Artificial Intelligence 285
Replace Julián Urbano with:
Julián Urbano Spain
Donald Byrd United States
Jeremy Pickens United States
Yves Raimond United Kingdom
Eva Zangerle Austria
Marius Kaminskas Italy
Raluca Paiu Germany
Pavel Pecina Czechia
Brewster Kahle United States
Byeong Man Kim South Korea
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Citations per field
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Citations per year

Countries citing papers authored by Rodger J. McNab

Since Specialization
Citations

This map shows the geographic impact of Rodger J. McNab'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 Rodger J. McNab with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Rodger J. McNab more than expected).

Fields of papers citing papers by Rodger J. McNab

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Rodger J. McNab. 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 Rodger J. McNab. The network helps show where Rodger J. McNab may publish in the future.

Co-authorship network

The 11 scholars most cited alongside Rodger J. McNab, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Rodger J. McNab Line = papers co-authored together Rodger J. McNab links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1 200211
2 20026
3 200033
4 2000111
5 2000112
6 200067
7
Human-computer interaction for digital libraries A transaction log analysis of a digital library
20003
8 199922
9 199957
10 199820
11 199837
12
Melody based tune retrieval over the World Wide Web
19981
13 199798
14
The New Zealand Digital Library MELody in DEX
19979
15
Music Information Retrieval Using Audio Input
19971
16 199711
17
Melody transcription for interactive applications
19965
18 1996203
19
A program to teach sight-singing
19961
20
Signal processing for melody transcription
199555

About Rodger J. McNab

Rodger J. McNab is a scholar working on Signal Processing, Music, Computer Vision and Pattern Recognition, Literature and Literary Theory and Information Systems and Management, having authored 23 papers that have together received 894 indexed citations. Recurring topics across this work include Music and Audio Processing (11 papers), Music Technology and Sound Studies (9 papers), Digital Humanities and Scholarship (5 papers), Information Retrieval and Search Behavior (4 papers), Speech and Audio Processing (4 papers), Advanced Text Analysis Techniques (4 papers), Video Analysis and Summarization (3 papers) and Diverse Musicological Studies (3 papers). The work is most often cited by research in Signal Processing (501 citations), Computer Vision and Pattern Recognition (503 citations), Music (57 citations), Information Systems (218 citations) and Artificial Intelligence (285 citations). Rodger J. McNab has collaborated with scholars based in New Zealand, United States and United Kingdom. Frequent co-authors include Ian H. Witten, Lloyd A. Smith, Sally Jo Cunningham, David Bainbridge, Stefan Boddie, Steve Jones, William J. Teahan, Yingying Wen, Craig G. Nevill-Manning and Russell Beale. Their work appears in journals such as Computational Linguistics, International Journal on Digital Libraries, D-Lib Magazine, The Electronic Library and Multimedia Tools and Applications.

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.

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