Dan Tidhar
Impact in
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- scientometrics and bibliometrics research
- Artificial Intelligence top 5%
- Topic Modeling
- Advanced Text Analysis Techniques
- Natural Language Processing Techniques
- Semantic Web and Ontologies
Papers in
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- Music Technology and Sound Studies 13
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- Music and Audio Processing 12
- Time Series Analysis and Forecasting 2
- Co-authors
- Simone Teufel (2 shared papers)Advaith Siddharthan (2 shared papers)Matthew Woolhouse (2 shared papers)Ian Cross (1 shared paper)Simon Dixon (7 shared papers)Daniel Leech‐Wilkinson (2 shared papers)Matthias Mauch (3 shared papers)Emmanouil Benetos (4 shared papers)
- Journals
- Frontiers in Psychology (2 papers)The Journal of the Acoustical Society of America (1 paper)Journal of New Music Research (1 paper)Early Music (1 paper)Journal of Mathematics and Music (1 paper)
- Partner nations
- United KingdomGermanyMexico
In The Last Decade
Dan Tidhar
19 papers receiving 510 citations
Peers
Comparison fields: 5 of 65
- Statistics, Probability and Uncertainty 105
- Artificial Intelligence 325
- Music 27
- Signal Processing 61
- Cognitive Neuroscience 73
Countries citing papers authored by Dan Tidhar
This map shows the geographic impact of Dan Tidhar'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 Dan Tidhar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Dan Tidhar more than expected).
Fields of papers citing papers by Dan Tidhar
This network shows the impact of papers produced by Dan Tidhar. 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 Dan Tidhar. The network helps show where Dan Tidhar may publish in the future.
Co-authors
The 21 scholars most cited alongside Dan Tidhar, 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 | 2006 | 299 | |
| 2 | 2006 | 83 | |
| 3 | 2016 | 47 | |
| 4 | 2014 | 41 | |
| 5 | 2000 | 12 | |
| 6 | 2010 | 11 | |
| 7 | 2010 | 9 | |
| 8 | Retrieving hierarchical text structure from typeset scientific articles - a prerequisite for e-science text mining | 2005 | 7 |
| 9 | 2012 | 7 | |
| 10 | 2010 | 7 | |
| 11 | 2014 | 7 | |
| 12 | 2011 | 5 | |
| 13 | 2009 | 4 | |
| 14 | 2014 | 3 | |
| 15 | Synaesthetic Traces: Digital Acquisition of Musical Shapes | 2011 | 2 |
| 16 | 2020 | 2 | |
| 17 | 2002 | 2 | |
| 18 | 2014 | 1 | |
| 19 | 2014 | 1 | |
| 20 | 2023 | 0 |
About Dan Tidhar
Dan Tidhar is a scholar working on Computer Vision and Pattern Recognition, Signal Processing, Cognitive Neuroscience, Music and Artificial Intelligence, having authored 20 papers that have together received 550 indexed citations. Recurring topics across this work include Music Technology and Sound Studies (13 papers), Music and Audio Processing (12 papers), Neuroscience and Music Perception (7 papers), Diverse Musicological Studies (2 papers), Advanced Text Analysis Techniques (2 papers), Topic Modeling (2 papers), Biomedical Text Mining and Ontologies (2 papers) and Time Series Analysis and Forecasting (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (105 citations), Artificial Intelligence (325 citations), Music (27 citations), Signal Processing (61 citations) and Cognitive Neuroscience (73 citations). Dan Tidhar has collaborated with scholars based in United Kingdom, Germany and Mexico. Frequent co-authors include Simone Teufel, Advaith Siddharthan, Matthew Woolhouse, Ian Cross, Simon Dixon, Daniel Leech‐Wilkinson, Matthias Mauch, Emmanouil Benetos, György Fazekas and Nicolas Gold. Their work appears in journals such as Frontiers in Psychology, The Journal of the Acoustical Society of America, Journal of New Music Research, Early Music and Journal of Mathematics and Music.
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.