Enabling Roll-up and Drill-down Operations in News Exploration with Knowledge Graphs for Due Diligence and Risk Management

TL;DR

This paper presents NCEXPLORER, a framework that enhances news exploration in finance by enabling roll-up and drill-down operations through integration with knowledge graphs, improving efficiency and depth of analysis.

Contribution

Introduction of NCEXPLORER, a novel framework that incorporates knowledge graphs to facilitate OLAP-like news exploration operations for better risk assessment.

Findings

NCEXPLORER outperforms existing news search methods in accuracy and efficiency.

Empirical evaluations show improved exploration capabilities across multiple domains.

Knowledge graph integration significantly enhances news content understanding.

Abstract

Efficient news exploration is crucial in real-world applications, particularly within the financial sector, where numerous control and risk assessment tasks rely on the analysis of public news reports. The current processes in this domain predominantly rely on manual efforts, often involving keywordbased searches and the compilation of extensive keyword lists. In this paper, we introduce NCEXPLORER, a framework designed with OLAP-like operations to enhance the news exploration experience. NCEXPLORER empowers users to use roll-up operations for a broader content overview and drill-down operations for detailed insights. These operations are achieved through integration with external knowledge graphs (KGs), encompassing both fact-based and ontology-based structures. This integration significantly augments exploration capabilities, offering a more comprehensive and efficient approach to unveiling the underlying structures and nuances embedded in news content. Extensive empirical studies through master-qualified evaluators on Amazon Mechanical Turk demonstrate NCEXPLORER's superiority over existing state-of-the-art news search methodologies across an array of topic domains, using real-world news datasets.