Name
Abstract | ||
|---|---|---|
Relational database systems solve many of the traditional problems for processing of structured data. However, unstructured data in the form of images, video, audio and multimedia is growing at a tremendous rate and introduces new requirements that are not met by today's database engines. One well known example is content-based retrieval that involves similarity searching and indexing in high-dimensional feature spaces. In addition there has been much recent focus on applying machine learning techniques involving semantics modeling, spatio-temporal indexing, multi-modal (audio-, visual-, textual-) integration and relevance feedback searching. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1145/1160939.1160957 | CVDB |
Keywords | Field | DocType |
indexation,face recognition,semantic model,outliers,feature space,relational database system,structured data,machine learning,similarity search | Facial recognition system,Relevance feedback,Information retrieval,Computer science,Search engine indexing,Outlier,Unstructured data,Relational database management system,Data model,Multimedia,Semantics | Conference |
ISBN | Citations | PageRank |
1-59593-151-1 | 0 | 0.34 |
References | Authors | |
1 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| John R. Smith | 1 | 4939 | 487.88 |
| David Doermann | 2 | 4313 | 312.70 |
| Amarnath Gupta | 3 | 1311 | 226.69 |
| Jonathan Goldstein | 4 | 1686 | 142.21 |
| Uri Shaft | 5 | 1050 | 107.01 |
| Nalini K. Ratha | 6 | 1090 | 93.04 |