Building a K-Pop knowledge graph using an entertainment ontology

Abstract

Recently, the Korean popular (K-Pop) music industry has grown into a popular subculture among teenagers and young adults worldwide, which resulted in widespread interest in the fashion and style of idolised Korean singers and groups. Although English social media websites provide some content related to K-Pop, these websites lack diversity and rapid updating of information compared to local Korean websites. This study introduces a K-Pop knowledge graph, which is the basis for describing various objects and their relationships. All contents of the knowledge graph can be distributed and shared across various applications. To do so, this study proposes a semantic data model to represent a comprehensive profile for singers and groups, their activities, organisations and entertainment content. The knowledge graph is created by aggregating a set of relevant datasets from various data sources. In addition, Gnosis, which is a news application, demonstrates how this knowledge graph can be used in a real-world service.

Keywords:

• Knowledge graph
• Ontology
• Linked data
• K-Pop