| 摘要 |
Techniques are disclosed that leverage time series techniques to express entityactivity data in a longitudinal temporal form, which may then be employed to dynamically classify the entity's behavior. In some embodiments, groupings or segmentations of different entities that exhibit similar profiles of longitudinal temporal form are identified using various techniques, including frequency-domain analysis, and/or unsupervised model based clustering. The clustering of entities enables directing of offerings to, for example, a telecommunication's customer based on characteristics of the cluster. |
