Interaction Knowledge Extraction
Interaction Knowledge Extraction is a scholarly methodological contribution that systematically identifies, formalizes, and distills patterns of interactive behaviors or relationships from empirical or computational data within human-computer, social, or cognitive systems, distinguishing itself by its focus on uncovering latent, higher-order knowledge structures inherent in interaction processes.
69
Publications
11.1K
Citations
273
Authors
125
Institutions
Publications per year
2017–2026
20
Parents
69
Using graph theory to analyze biological networks
Georgios A. Pavlopoulos, Maria Secrier, Charalampos Moschopoulos et al. · BioData Mining · 2011 · 809 citations · Full text
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125
Columbia University
New York, United States
4 h-index
9 publications
345 citations
Yonsei University
Seoul, South Korea
2 h-index
2 publications
73 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
6 publications
276 citations
Tsinghua University
Beijing, China
2 h-index
2 publications
142 citations
University of California, San Francisco
San Francisco, United States
2 h-index
3 publications
7.5K citations
Microsoft Research (United Kingdom)
Cambridge, United Kingdom
2 h-index
10 publications
1.3K citations
Dalian University of Technology
Dalian, China
2 h-index
6 publications
149 citations
University of Copenhagen
Copenhagen, Denmark
2 h-index
6 publications
29.9K citations
1–8 of 125
3 publications · 108 citations
3
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2 publications · 169 citations
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2 publications · 54 citations
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1 publications · 11 citations
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PNAS · 1 publications · 18 citations
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