Name
Title | ||
|---|---|---|
The appearance of the giant component in descriptor graphs and its application for descriptor selection |
Abstract | ||
|---|---|---|
The paper presents a random graph based analysis approach for evaluating descriptors based on pairwise distance distributions on real data. Starting from the Erdős-Rényi model the paper presents results of investigating random geometric graph behaviour in relation with the appearance of the giant component as a basis for choosing descriptors based on their clustering properties. Experimental results prove the existence of the giant component in such graphs, and based on the evaluation of their behaviour the graphs, the corresponding descriptors are compared, and validated in proof-of-concept retrieval tests. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-33247-0_9 | CLEF |
Keywords | Field | DocType |
random graph,random geometric graph behaviour,analysis approach,descriptor selection,pairwise distance distribution,giant component,clustering property,descriptor graph,nyi model,proof-of-concept retrieval test,corresponding descriptors,graph analysis,feature selection | Pairwise comparison,Graph,Random graph,Pattern recognition,Feature selection,Computer science,Power graph analysis,Giant component,Artificial intelligence,Cluster analysis,Random geometric graph | Conference |
Citations | PageRank | References |
2 | 0.35 | 10 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Anita Keszler | 1 | 9 | 2.17 |
| Levente Kovács | 2 | 98 | 38.25 |
| Tamás Szirányi | 3 | 152 | 26.92 |