Annotation Recommendation
Annotation Recommendation is a computational method that selectively identifies and proposes contextual additions to visualizations by analyzing content relevance, user needs, and perceptual effectiveness, thereby enhancing information comprehension and analytical insight.
20
Publications
1.5K
Citations
66
Authors
33
Institutions
Publications per year
2017–2026
9
Parents
20
YEDDA: A Lightweight Collaborative Text Span Annotation Tool
Jie Yang, Yue Zhang, Linwei Li et al. · 2018 · 112 citations · Full text
Computing, Computer Science, Natural Language Processing +12
SAGES consensus recommendations on an annotation framework for surgical video
Ozanan R. Meireles, Guy Rosman, Maria S. Altieri et al. · Surgical Endoscopy · 2021 · 108 citations · Full text
1–5 of 20
66
3
h-index
3
h-index
2
h-index
2
h-index
2
h-index
1–5 of 66
33
Arizona State University
Tempe, United States
2 h-index
4 publications
106 citations

DePaul University
Chicago, United States
2 h-index
8 publications
260 citations
IBM (United States)
Armonk, United States
2 h-index
2 publications
53 citations
Engineering Arts (United States)
Tempe, United States
1 h-index
2 publications
20 citations
Yahoo (Spain)
Madrid, Spain
1 h-index
2 publications
1.9K citations
Duke University
Durham, United States
1 h-index
1 publications
108 citations
Florida State University
Tallahassee, United States
1 h-index
3 publications
81 citations

University of Wollongong
Wollongong, Australia
1 h-index
5 publications
65 citations
1–8 of 33
Repository · 2 publications · 49 citations
2
h-index
1 publications · 51 citations
1
h-index
1 publications · 19 citations
1
h-index
1 publications · 108 citations
1
h-index
IJAIT · 1 publications · 11 citations
1
h-index
1–5