Citation

Goh, Kun Shun and Tan, Ian Kim Teck and Goh, Hui Ngo (2024) Towards automated financial market knowledge graph construction. In: 3rd International Conference on Computer, Information Technology, and Intelligent Computing (CITIC2023), 26–28 July 2023, Virtual Conference.

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Abstract

The prevalence of financial news on the internet has made it easier for investors to access information. However, the fast-changing nature of the financial market and the time-consuming task of sifting through articles can be overwhelming. To address this issue, a framework has been developed and is proposed to automatically construct and update a knowledge graph (KG) for financial market information. The KG stores relational information between entities in a directed graph format, providing a graphical visualization that allows investors to examine complex relationships between entities that play a role in the stock market. The framework involves five main phases: scrapping online articles, triples extraction, coreference resolution, predicate linking, and entity linking. The precision rate achieved by the framework is 27.69%, with a recall rate of 7.14% and an F-1 score of 0.1136 in extracting correct information from articles and integrating it properly into the KG.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	H Social Sciences > HG Finance > HG4001-4285 Finance management. Business finance.
Divisions:	Faculty of Computing and Informatics (FCI)
Depositing User:	Ms Nurul Iqtiani Ahmad
Date Deposited:	01 Aug 2024 08:18
Last Modified:	01 Aug 2024 08:18
URII:	http://shdl.mmu.edu.my/id/eprint/12738

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