ARC Code TI: sequenceMiner
Description
The sequenceMiner was developed to address the problem of detecting and describing anomalies in large sets of high-dimensional symbol sequences. sequenceMiner works by performing unsupervised clustering (grouping) of sequences using the normalized longest common subsequence (LCS) as a similarity measure, followed by a detailed analysis of outliers to detect anomalies. sequenceMiner utilizes a new hybrid algorithm for computing the LCS that has been shown to outperform existing algorithms by a factor of five. sequenceMiner also includes new algorithms for outlier analysis that provide comprehensible indicators as to why a particular sequence was deemed to be an outlier. This provides analysts with a coherent description of the anomalies identified in the sequence, and why they differ from more 'normal' sequences.
Resources
| Name |
Format |
Description |
Link |
|
45 |
SequenceMiner.tar.gz |
http://ti.arc.nasa.gov/m/opensource/downloads/SequenceMiner.tar.gz |
Tags
- cluster
- longest-common-sequence
- lcs
- sequenceminer
- outlier
- detection
- algorithm