TY - GEN
T1 - Construction of Financial Event Knowledge Big Graph
T2 - 18th International Society for Knowledge Organization Conference, ISKO 2024
AU - Liu, Zhenghao
AU - Chen, Shuaipu
AU - Zhang, Zhijian
PY - 2024
Y1 - 2024
N2 - The escalating intricacy and interconnected nature of modern financial markets engender formidable challenges in the realms of risk analysis and prediction. Within this scholarly inquiry, we present an innovative knowledge-organizational framework, denoted as the Financial Event Knowledge Big Graph (FEKBG), meticulously crafted to confront these challenges by harnessing the synergistic potency of extensive data reservoirs and sophisticated artificial intelligence techniques. To construct a multi-layer financial event knowledge big graph, the core elements of the event are extracted, and the relationship is extracted, and then the event evolution relationship is modeled and analyzed. By virtue of operationalizing the FEBG model, stakeholders and decision-makers are imbued with a timely and meticulously accurate informational arsenal, thereby capacitating preemptive measures against, and amelioration, financial vicissitudes. As the vanguard of intellectual inquiry, we also deliberate upon prospective avenues for further scholarly pursuit, encompassing an expansive exploration of supplementary correlation paradigms, concomitantly enriching the landscape of risk prognostication and analysis. © 2024 International Society for Knowledge Organization. All rights reserved.
AB - The escalating intricacy and interconnected nature of modern financial markets engender formidable challenges in the realms of risk analysis and prediction. Within this scholarly inquiry, we present an innovative knowledge-organizational framework, denoted as the Financial Event Knowledge Big Graph (FEKBG), meticulously crafted to confront these challenges by harnessing the synergistic potency of extensive data reservoirs and sophisticated artificial intelligence techniques. To construct a multi-layer financial event knowledge big graph, the core elements of the event are extracted, and the relationship is extracted, and then the event evolution relationship is modeled and analyzed. By virtue of operationalizing the FEBG model, stakeholders and decision-makers are imbued with a timely and meticulously accurate informational arsenal, thereby capacitating preemptive measures against, and amelioration, financial vicissitudes. As the vanguard of intellectual inquiry, we also deliberate upon prospective avenues for further scholarly pursuit, encompassing an expansive exploration of supplementary correlation paradigms, concomitantly enriching the landscape of risk prognostication and analysis. © 2024 International Society for Knowledge Organization. All rights reserved.
UR - http://www.scopus.com/inward/record.url?scp=85185714708&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85185714708&origin=recordpage
U2 - 10.5771/9783987400476-89
DO - 10.5771/9783987400476-89
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 978-3-98740-046-9
T3 - Advances in Knowledge Organization
SP - 89
EP - 100
BT - Knowledge Organization for Resilience in Times of Crisis: Challenges and Opportunities
A2 - Lu, Wei
A2 - Barros, Thiago Henrique Bragato
A2 - An, Lu
A2 - Martínez-Ávila, Daniel
PB - Nomos Verlagsgesellschaft mbH und Co KG
Y2 - 20 March 2024 through 22 March 2024
ER -