Method and system for predicting and classifying event sequences embedded in a knowledge graph

Abstract

A computer-implemented method for event sequence forecasting of a process instance includes building up and training a three-layered prediction model including a first, a second and a third layer. The first layer is a graph embedding layer that assigns a fixed-dimensional graph embedding vector to each node and relation type in a fused event and knowledge graph that contains available structural information including events, knowledge graph nodes, and links between the events and the knowledge graph nodes. The second layer is an event embedding layer that assigns to each event of the process instance a fixed-dimensional event embedding vector. The third layer is a prediction layer that receives as input a sequence of event embeddings from the second layer and that generates as output a prediction of an unknown property of the event sequence used as input.

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