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ARC Code TI: sequenceMiner
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.
Complete Metadata
| @type | dcat:Dataset |
|---|---|
| accessLevel | public |
| accrualPeriodicity | irregular |
| bureauCode |
[
"026:00"
]
|
| contactPoint |
{
"fn": "Dennis Koga",
"@type": "vcard:Contact",
"hasEmail": "mailto:dennis.koga@nasa.gov"
}
|
| 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. |
| distribution |
[
{
"@type": "dcat:Distribution",
"format": "TAR",
"mediaType": "application/x-tar",
"downloadURL": "http://ti.arc.nasa.gov/m/opensource/downloads/SequenceMiner.tar.gz"
}
]
|
| identifier | OCIO-Fitara-137 |
| issued | 2015-01-07 |
| keyword |
[
"algorithm",
"cluster",
"detection",
"lcs",
"longest-common-sequence",
"outlier",
"sequenceminer"
]
|
| modified | 2025-07-14 |
| programCode |
[
"026:046"
]
|
| publisher |
{
"name": "Ames Research Center",
"@type": "org:Organization"
}
|
| theme |
[
"Management/Operations"
]
|
| title | ARC Code TI: sequenceMiner |
