Dan Tidhar
Impact in
-
- 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 and Audio Processing 12
- Speech and Audio Processing 2
- Time Series Analysis and Forecasting 2
- Music 3
- Co-authors
- Advaith SiddharthanSimone TeufelMatthew WoolhouseIan CrossSimon DixonDaniel Leech‐WilkinsonMatthias MauchGyörgy Fazekas
- Journals
- Frontiers in Psychology (2 papers)Journal of New Music Research (1 paper)Early Music (1 paper)The Journal of the Acoustical Society of America (1 paper)Journal of Mathematics and Music (1 paper)
- Partner nations
- United KingdomMexicoCanada
In The Last Decade
Dan Tidhar
19 papers receiving 508 citations
Peers
Comparison fields: 5 of 65
- Statistics, Probability and Uncertainty 106
- Artificial Intelligence 328
- Music 27
- Signal Processing 61
- Cognitive Neuroscience 74
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-authorship network
The 22 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 | 2023 | 0 | |
| 2 | 2020 | 2 | |
| 3 | 2016 | 47 | |
| 4 | 2014 | 40 | |
| 5 | 2014 | 7 | |
| 6 | 2014 | 1 | |
| 7 | 2014 | 3 | |
| 8 | 2014 | 1 | |
| 9 | 2012 | 7 | |
| 10 | Synaesthetic Traces: Digital Acquisition of Musical Shapes | 2011 | 2 |
| 11 | 2011 | 5 | |
| 12 | 2010 | 11 | |
| 13 | 2010 | 9 | |
| 14 | 2010 | 7 | |
| 15 | 2009 | 4 | |
| 16 | 2006 | 83 | |
| 17 | 2006 | 301 | |
| 18 | Retrieving hierarchical text structure from typeset scientific articles - a prerequisite for e-science text mining | 2005 | 7 |
| 19 | 2002 | 2 | |
| 20 | 2000 | 12 |
About Dan Tidhar
Dan Tidhar is a scholar working on Signal Processing, Music, Computer Vision and Pattern Recognition, Cognitive Neuroscience and Marketing, having authored 20 papers that have together received 551 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), Speech and Audio Processing (2 papers), Biomedical Text Mining and Ontologies (2 papers), Topic Modeling (2 papers), Time Series Analysis and Forecasting (2 papers) and Advanced Text Analysis Techniques (2 papers). The work is most often cited by research in Statistics, Probability and Uncertainty (106 citations), Artificial Intelligence (328 citations), Music (27 citations), Signal Processing (61 citations) and Cognitive Neuroscience (74 citations). Dan Tidhar has collaborated with scholars based in United Kingdom, Mexico and Canada. Frequent co-authors include Advaith Siddharthan, Simone Teufel, Matthew Woolhouse, Ian Cross, Simon Dixon, Daniel Leech‐Wilkinson, Matthias Mauch, György Fazekas, Emmanouil Benetos and Ian Lewin. Their work appears in journals such as Frontiers in Psychology, Journal of New Music Research, Early Music, The Journal of the Acoustical Society of America 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.