Anomaly, association and clustering detection
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United States of America Patent
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Mar 7, 2017
Grant Date -
Jun 2, 2016
app pub date -
Feb 3, 2016
filing date -
Dec 12, 2011
priority date (Note) -
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Abstract
Techniques are provided for anomaly, association and clustering detection. At least one code table is built for each attribute in a set of data. A first code table corresponding to a first attribute and a second code table corresponding to a second attribute are selected. The first code table and the second code table are merged into a merged code table, and a determination is made to accept or reject the merged code table. An anomaly is detected when a total compression cost for a data point is greater than a threshold compression cost inferred from one or more code tables. An association in a data table is detected by merging attribute groups, splitting data groups, and assigning data points to data groups. A cluster is inferred from a matrix of data and code words for each of the one or more code tables.
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