US 2023/0419129 A1 · METHOD AND SYSTEM FOR EXCEPTION MANAGEMENT

Abstract

State of the art approaches of exception management are reactive, manual, and intuition-driven. Command center teams often react to exceptions. They also use BI tools which only provide statistical observation, but fail to mine domain-aware insights and actionable recommendations. The disclosure herein generally relates to analyzing process exceptions, and, more particularly, to a method and system for generating a data model to analyze and predict process exceptions. The system generates a data model by using information on rules, associated properties and exceptions, as training data. The data model is further used to process information on different rules to identify exceptions, and then to generate recommendations in response to identified exceptions.

Claims12

Dependent claims

A processor implemented method of generating a data model for exception management, comprising:

obtaining exception data corresponding to a plurality of exceptions as input data, wherein the exception data comprising a) date of exception, b) type of exception, and c) a plurality of attributes of exception;
generating a plurality of data properties and a plurality of quality properties of the exception data by executing a plurality of classification algorithms on the obtained exception data;
determining an algorithm matching the obtained exception data, based on the data properties and the quality properties;
and
generating the data model utilizing a training data comprising a) the data properties, b) the quality properties, and c) information on the algorithm matching the obtained exception data.

2 more elements

A system for generating a data model for exception management, comprising:

one or more hardware processors;
a communication interface;
and
a memory storing a plurality of instructions, wherein the plurality of instructions when executed, cause the one or more hardware processors to:
obtain exception data corresponding to a plurality of exceptions as input data, wherein the exception data comprising a) date of exception, b) type of exception, and c) a plurality of attributes of exception;
generate a plurality of data properties and a plurality of quality properties of the exception data by executing a plurality of classification algorithms on the obtained exception data;
determine an algorithm matching the obtained exception data, based on the data properties and the quality properties;
and
generate the data model utilizing a training data comprising a) the data properties, b) the quality properties, and c) information on the algorithm matching the obtained exception data.

6 more elements

One or more non-transitory machine-readable information storage mediums comprising one or more instructions which when executed by one or more hardware processors cause:

obtaining exception data corresponding to a plurality of exceptions as input data, wherein the exception data comprising a) date of exception, b) type of exception, and c) a plurality of attributes of exception;
generating a plurality of data properties and a plurality of quality properties of the exception data by executing a plurality of classification algorithms on the obtained exception data;
determining an algorithm matching the obtained exception data, based on the data properties and the quality properties;
and
generating the data model utilizing a training data comprising a) the data properties, b) the quality properties, and c) information on the algorithm matching the obtained exception data.

2 more elements

Dependencies are inferred from the claim text.

Method and system for exception management

Life of this patent

Method and system for exception management

Life of this patent

Abstract

Claims12