US 11,886,230 B2 · Method and system of automatically predicting anomalies in online forms

Abstract

A computer-implemented system and method for predicting and flagging an anomaly entered in a digital form. A server computing device classifies a plurality of data fields of the digital form to identify a set of non-zero value data fields; and obtains an anomaly detection model comprising a statistical tree structure associated with the data field of the digital form. The server computing device receives datasets including a target value of a data field and values of a set of cohorting data features; traverses a statistical tree structure of the anomaly detection model with the target dataset to form a set of target cohorts to determine a target statistic value for the data field; flags the data field value of the target dataset as an anomaly item; and generates one or more confidence scores for a runtime prediction based on one or more variance changes for the data field.

Claims20

Dependent claims

A processor implemented method comprising:

obtaining an anomaly detection model comprising a statistical tree structure associated with an input data feature, the statistical tree structure comprising a plurality of nodes corresponding to a set of cohorts, each cohort comprising a set of statistic values of the input data feature associated with a set of system users, a variance of values of the input data feature and respective cohorting data features;
traversing the statistical tree structure with a target dataset from a first node to a leaf node to form a set of target cohorts and determine a target statistic value of the input data feature at the leaf node;
determining that the target statistic value is not within a pair of thresholds;
and
flagging a data field of the target dataset as an anomalous field.

2 more elements

A system comprising:

a non-transitory storage medium storing computer program instructions;
a processor configured to execute the computer program instructions to cause the system to perform operations comprising:
obtaining an anomaly detection model comprising a statistical tree structure associated with an input data feature, the statistical tree structure comprising a plurality of nodes corresponding to a set of cohorts, each cohort comprising a set of statistic values of the input data feature associated with a set of system users, a variance of values of the input data feature and respective cohorting data features;
traversing the statistical tree structure with a target dataset from a first node to a leaf node to form a set of target cohorts and determine a target statistic value of the input data feature at the leaf node;
determining that the target statistic value is not within a pair of thresholds;
and
flagging a data field of the target dataset as an anomalous field.

4 more elements

Dependencies are inferred from the claim text.

Method and system of automatically predicting anomalies in online forms

Life of this patent

Method and system of automatically predicting anomalies in online forms

Life of this patent

Abstract

Claims20