Abstract

Competitor relationships are integral to many important financial applications. Example use cases include understanding regulatory impacts, investing in new business areas, and building economic models. Competitor relationships can be defined based on several aspects, including valuations and asset returns, industrial processes, or offerings of products and services. Determining these relationships is often challenging due to the diverse and complex interactions between companies which must be mined from vast datasets with varying degrees of credibility. In this paper, we approach this problem by constructing a hybrid knowledge graph capturing financial relationships and applying a link prediction model to identify missing competitor relationships.
Knowledge graphs are a popular knowledge representation choice for capturing entities and the relationships between them. Knowledge graph construction …

Date

June 15, 2018

Authors

Jay Pujara

Conference

Proceedings of the Fourth International Workshop on Data Science for Macro-Modeling with Financial and Economic Datasets

Pages

14

Publisher

ACM