View source for US Patent Application 17664719. GRAPH ENCODERS FOR BUSINESS PROCESS ANOMALY DETECTION simplified abstract

=GRAPH ENCODERS FOR BUSINESS PROCESS ANOMALY DETECTION=


==Organization Name==

[[:Category:International Business Machines Corporation|International Business Machines Corporation]]


[[Category:International Business Machines Corporation]]

==Inventor(s)==

[[:Category:Siyu Huo of White Plains NY (US)|Siyu Huo of White Plains NY (US)]][[Category:Siyu Huo of White Plains NY (US)]]

[[:Category:Prabhat Maddikunta Reddy of Danbury CT (US)|Prabhat Maddikunta Reddy of Danbury CT (US)]][[Category:Prabhat Maddikunta Reddy of Danbury CT (US)]]

[[:Category:Vatche Isahagian of Belmont MA (US)|Vatche Isahagian of Belmont MA (US)]][[Category:Vatche Isahagian of Belmont MA (US)]]

[[:Category:Vinod Muthusamy of Austin TX (US)|Vinod Muthusamy of Austin TX (US)]][[Category:Vinod Muthusamy of Austin TX (US)]]

[[:Category:Prerna Agarwal of New Delhi (IN)|Prerna Agarwal of New Delhi (IN)]][[Category:Prerna Agarwal of New Delhi (IN)]]

==GRAPH ENCODERS FOR BUSINESS PROCESS ANOMALY DETECTION - A simplified explanation of the abstract==


This abstract first appeared for US patent application 17664719 titled 'GRAPH ENCODERS FOR BUSINESS PROCESS ANOMALY DETECTION

==Simplified Explanation==

The patent application describes a method, computer system, and computer program for detecting anomalies in business process logs.
* Converts business process logs into a graphical data structure.
* Generates an optimized graph encoding for anomaly detection using unsupervised machine learning.
* Computes an anomaly score for each activity in the business process log using a process aware metric based on feature representation.
* Labels data points with high anomaly scores.


==Original Abstract Submitted==

A method, computer system, and a computer program product for anomaly detection is provided. The present invention may include converting business process logs into a graphical data structure. The present invention may include generating an optimized graph encoding for anomaly detection using an unsupervised machine learning model. The present invention may include computing an anomaly score for each activity of the business process log using a process aware metric based on feature representation. The present invention may include labeling each of the one or more data points with a high anomaly score.



[[Category:G06Q10/06]]
[[Category:G06N3/08]]