Enabling roll-up and drill-down operations in news exploration with knowledge graphs for due diligence and risk management

• Main Authors: WANG, Sha, LI, Yuchen, XIAO, Hanhua, BAO, Zhifeng, DONG, Yanfei
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2024
• Subjects: News exploration; Knowledge graphs; Online analytical processing; Computer Sciences; Databases and Information Systems
• Online Access: https://ink.library.smu.edu.sg/sis_research/9787; https://ink.library.smu.edu.sg/context/sis_research/article/10787/viewcontent/2405.04929v1.pdf
• Institution: Singapore Management University

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 keyword-based 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.