Algorithm5: A Technique for Fuzzy Similarity Clustering of Chemical Inventories

Autor: John M. Cibulskis, and Patrick Dale McCray, Michael Cibulskis, Thompson N. Doman, Dale P. Spangler
Rok vydání: 1996
Předmět:
Zdroj: Journal of Chemical Information and Computer Sciences. 36:1195-1204
ISSN: 1520-5142
0095-2338
Popis: Clustering of chemical inventories on the basis of structural similarity has been shown to be useful in a number of applications related to the utilization and enhancement of those inventories. However, the widely-used Jarvis−Patrick clustering algorithm displays a number of weaknesses which make it difficult to cluster large databases in a consistent, satisfactory, and timely manner. Jarvis−Patrick clusters tend to be either too large and heterogeneous (i.e., “chained”) or too small and exclusive (i.e., under-clustered), and the algorithm requires time-consuming manual tuning. This paper describes a computer algorithm which is nondirective, in that it performs the clustering without manual tuning yet generates useful clustering results.
Databáze: OpenAIRE