Amplifying state dissimilarity leads to robust and interpretable clustering of scientific data.
Brooke E. HusicKristy L. Schlueter-KuckJohn O. DabiriPublished in: CoRR (2018)
Keyphrases
- scientific data
- data management
- clustering algorithm
- massive amounts of data
- life sciences
- dissimilarity measure
- scientific information
- data collection
- scientific data sets
- multi dimensional data
- drug discovery
- clustering method
- k means
- geographically distributed
- high energy physics
- relational databases
- feature space
- data clustering
- times faster
- knowledge discovery
- association patterns
- scientific databases
- molecular dynamics
- scientific disciplines
- digital libraries