Systems and methods for detection of anomalous entities
US9753968B1 · kind B1 · utility
Assignee
Inventors
Key dates
| Filing date | Jun 20, 2016 |
| Grant date | Sep 5, 2017 |
| Priority date | — |
| Expiry date | Jun 20, 2036 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG16H50/70
- WIPO fieldMedical technology
- WIPO sectorInstruments
Abstract
There is provided a computer-implemented method of identifying anomalous entities in a dataset, comprising: selecting a subset of training entities from entities of at least one dataset; determining dummy tuplets of entities in the subset by applying a permutation function on real tuplets, wherein the real tuplets represent original and normal data of the at least one dataset, wherein the dummy tuplets represent anomalous data based on artificially created data not found in the original and normal at least one dataset, each one of the real tuplets and dummy tuplets comprises at least two of the training entities; analyzing the dummy tuplets and the real tuplets to identify at least one predefined characteristic relation that statistically differentiates between the real tuplets and the dummy tuplets according to a distinguishing requirement; and outputting the identified at least one predefined characteristic relation to identify a normal entity and/or an anomalous entity.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.