In-vehicle Data Mining
In-Vehicle Data Mining is a computational methodology within telematics analytics that involves the systematic extraction, analysis, and interpretation of vehicle-generated data streams to uncover latent patterns, behaviors, and insights specific to vehicular operations and driver dynamics.
66
Publications
3.1K
Citations
221
Authors
98
Institutions
Publications per year
2017–2026
43
Parents
66
Automobile Driver Fingerprinting
Miro Enev, Alex Takakuwa, Karl Koscher et al. · Proceedings on Privacy Enhancing Technologies · 2015 · 231 citations · Full text
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98
ETH Zurich
Zurich, Switzerland
4 h-index
4 publications
147 citations
Chalmers University of Technology
Gothenburg, Sweden
3 h-index
12 publications
275 citations

Renmin University of China
Beijing, China
3 h-index
3 publications
89 citations
Volvo Cars (Sweden)
Gothenburg, Sweden
3 h-index
5 publications
144 citations
Guangdong University of Technology
Guangzhou, China
2 h-index
9 publications
573 citations
Texas Department of Transportation
Austin, United States
2 h-index
7 publications
88 citations
University of Wisconsin–Madison
Madison, United States
2 h-index
5 publications
59 citations
Volvo (Sweden)
Gothenburg, Sweden
2 h-index
3 publications
98 citations
1–8 of 98
4 publications · 184 citations
5
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4 publications · 177 citations
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TRIP · 2 publications · 40 citations
2
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2 publications · 159 citations
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2 publications · 99 citations
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1–5