Relevance Feedback Evaluation is a methodological framework within information retrieval that systematically assesses the effectiveness of relevance feedback techniques by measuring improvements in retrieval performance based on user-provided relevance judgments.
204
Publications
15.4K
Citations
486
Authors
195
Institutions
Publications per year
2017–2026
13
Parents
Publications
204
Relevance feedback in information retrieval
J. J. Rocchio · Medical Entomology and Zoology · 1971 · 2.6K citations
Accurately interpreting clickthrough data as implicit feedback
Thorsten Joachims, Laura Granka, Bing Pan et al. · 2005 · 1.4K citations
Using statistical testing in the evaluation of retrieval experiments
David A. Hull · 1993 · 530 citations · Full text
1–5 of 204
Authors
486
- SR
7
h-index
- CB
4
h-index
- GV
4
h-index
- OF
4
h-index
- DA
4
h-index
1–5 of 486
Institutions
195
University of Massachusetts Amherst
Amherst Center, United States
8 h-index
13 publications
1K citations
Microsoft (United States)
Redmond, United States
6 h-index
15 publications
715 citations
Cornell University
Ithaca, United States
6 h-index
18 publications
12.5K citations
University of North Texas
Denton, United States
4 h-index
4 publications
400 citations
Stanford University
Stanford, United States
4 h-index
8 publications
2.3K citations
University of Waterloo
Waterloo, Canada
4 h-index
11 publications
226 citations
University of Illinois Urbana-Champaign
Urbana, United States
4 h-index
9 publications
440 citations
University of Amsterdam
Amsterdam, The Netherlands
4 h-index
10 publications
248 citations
1–8 of 195
Venues
- Information Processing & Management
21 publications · 1.3K citations
19
h-index
- Information Retrieval
6 publications · 238 citations
6
h-index
- Text REtrieval Conference
Conference · 5 publications · 113 citations
5
h-index
- Journal of the American Society for Information Science
JASIS · 5 publications · 1.6K citations
5
h-index
- Pattern Recognition Letters
4 publications · 208 citations
4
h-index
1–5