Name
Abstract | ||
|---|---|---|
Many projects in engineering and science require data classification based on different heuristics. Designers, for example, classify automobile engine performance as acceptable or unacceptable based on a combination of efficiency, emissions, noise levels, and other criteria. Researchers routinely classify documents as "relevant to the current project" or "irrelevant." Genome decoding divides chromosomes into genes, regulatory regions, signals, and so on. Pathologists identify cells as cancerous or benign. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1109/MCISE.2003.1225861 | Computing in Science and Engineering |
Keywords | Field | DocType |
Clustering algorithms,Automotive engineering,Data engineering,Design engineering,Automobiles,Engines,Noise level,Genomics,Bioinformatics,Decoding | Fuzzy clustering,Data mining,Computer science,Automotive engine,Heuristics,Artificial intelligence,Decoding methods,Data classification,Cluster analysis,Classified information,Machine learning,Data reduction | Journal |
Volume | Issue | ISSN |
5 | 5 | 1521-9615 |
Citations | PageRank | References |
4 | 0.70 | 1 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Nargess Memarsadeghi | 1 | 33 | 7.70 |
| O'Leary, Dianne P. | 2 | 1064 | 222.93 |
| Yalin Evren Sagduyu | 3 | 370 | 43.22 |