Construction of a relevance knowledge graph with application to the LOCAL news angle

Abstract

News angles are approaches to journalism content often used to provide a way to present a new report from an event. One particular type of news angle is the LOCAL news angle where a local news outlet focuses on an event by emphasising a local connection. Knowledge graphs are most often used to represent knowledge about a particular entity in the form of relationships to other entities. In this paper we see how we can extract a knowledge sub graph containing entities and relevant relationships that are connected to the locality of a news outlet. The purpose of this graph is to use it for automated journalism or as an aid for the journalist to find local connections to an event, as well as how the local connection relate to the event. We call such a graph a relevance knowledge graph. An algorithm for extracting such a graph from a linked data source like DBpedia is presented and examples of the use of a relevance graph in a LOCAL news angle context are provided.