Ranking Features
Ranking Features is a computational attribute or signal used within information retrieval systems to quantify the relevance of a document or item with respect to a given query, distinguished by its role in determining the relative position of results in a ranked list.
168
Publications
10.7K
Citations
563
Authors
261
Institutions
Publications per year
2017–2026
57
Parents
168
A Data-Driven Design for Fault Detection of Wind Turbines Using Random Forests and XGboost
Dahai Zhang, Liyang Qian, Baijin Mao et al. · IEEE Access · 2018 · 577 citations · Full text
Granular Prototyping in Fuzzy Clustering
A Bargiela, Witold Pedrycz, Kaoru Hirota · IEEE Transactions on Fuzzy Systems · 2004 · 433 citations
Ranking a random feature for variable and feature selection
Hervé Stoppiglia, Gérard Dreyfus, Rémi Dubois et al. · 2003 · 294 citations
1–5 of 168
563
3
h-index
3
h-index
3
h-index
3
h-index
3
h-index
1–5 of 563
261
Microsoft (United States)
Redmond, United States
11 h-index
24 publications
2.2K citations
Microsoft Research Asia (China)
Beijing, China
7 h-index
16 publications
3.1K citations
Tsinghua University
Beijing, China
5 h-index
15 publications
885 citations
Carnegie Mellon University
Pittsburgh, United States
5 h-index
18 publications
1.7K citations

Chinese Academy of Sciences
Beijing, China
5 h-index
12 publications
267 citations

University of Glasgow
Glasgow, United Kingdom
4 h-index
12 publications
721 citations
University of Science and Technology of China
Hefei, China
4 h-index
10 publications
842 citations
Yahoo (United States)
Sunnyvale, United States
3 h-index
10 publications
355 citations
1–8 of 261
4 publications · 196 citations
4
h-index
3 publications · 135 citations
3
h-index
3 publications · 656 citations
3
h-index
TFS · 3 publications · 589 citations
3
h-index
TKDE · 3 publications · 341 citations
3
h-index
1–5