Name
Abstract | ||
|---|---|---|
•A robust unsupervised graph-based rank aggregation function is presented.•It is targeted for general applicability, such as image, textual, or multimodal retrieval tasks.•A fusion graph is proposed to gather information and inter-relationship of multiple retrieval results.•A novel similarity retrieval score is formulated using fusion graphs and minimum common subgraphs.•The Extensive experimental protocol shows significant gains over state-of-the-art basseline methods. |
Year | DOI | Venue |
|---|---|---|
2019 | 10.1016/j.ipm.2019.03.008 | Information Processing & Management |
Keywords | Field | DocType |
Rank aggregation,Content-based retrieval,Multimodal retreival,Graph-based fusion | Manifold structure,Data mining,Graph,Contextual information,Ranking,Hyperparameter,Computer science,Document retrieval,Merge (version control),Computation | Journal |
Volume | Issue | ISSN |
56 | 4 | 0306-4573 |
Citations | PageRank | References |
2 | 0.37 | 14 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Ícaro Cavalcante Dourado | 1 | 2 | 1.05 |
| Daniel Carlos Guimarães Pedronette | 2 | 304 | 25.47 |
| Ricardo Torres | 3 | 38 | 4.58 |