Leveraging Enterprise Knowledge Graphs for Efficient Bridging Between Business Data with Large-Scale Web Data

Abstract

The diversification of the web into social media and the Web of Data means that companies need to collect the necessary data to make the best-informed market decisions. To deal with this, the new concept of Enterprise Knowledge Graphs (EKGs) is emerging as a backbone for federating valuable open information on the web together with the information contained in internal enterprise documents and databases. This paper examines the current challenges in this area, discusses the limitations of some existing integration systems, and addresses them by proposing a set of tools for virtually integrating enterprise data with social and linked data at scale. The proposed framework’s implementation is a configurable middleware and user-friendly keyword faceted search web interface that retrieves its input data from internal enterprise data combined with popular SPARQL endpoints and social network web APIs. We conducted an evaluation study to test our approach’s effectiveness using various metrics and compare it to state-of-the-art systems. The evaluation results show a competitive accuracy and usability of the proposed approach, facilitating the integration of data into a knowledge graph.