What is Event Knowledge Graph: A Survey

TL;DR

This survey comprehensively reviews Event Knowledge Graphs (EKGs), covering their history, ontology, acquisition, applications, and future trends, highlighting their growing importance in various AI and data-driven domains.

Contribution

It provides a thorough overview of EKG development, definitions, schemas, and applications, and discusses future research directions in the field.

Findings

EKGs are increasingly used in search, QA, recommendation, finance, and text generation.

The survey identifies key challenges and trends in EKG development.

Future research directions include schema induction and integration techniques.

Abstract

Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are also an essential kind of knowledge in the world, which trigger the spring up of event-centric knowledge representation form like Event KG (EKG). It plays an increasingly important role in many downstream applications, such as search, question-answering, recommendation, financial quantitative investments, and text generation. This paper provides a comprehensive survey of EKG from history, ontology, instance, and application views. Specifically, to characterize EKG thoroughly, we focus on its history, definition, schema induction, acquisition, related representative graphs/systems, and applications. The development processes and trends are studied therein. We further summarize prospective directions to facilitate future research on EKG.