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The Financial Institution Text Data Mining and Value Analysis Model Based on Big Data and Natural Language Processing

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Publicado no:Journal of Organizational and End User Computing vol. 37, no. 1 (2025), p. 1-41
Autor principal: Yang, Juan
Outros Autores: Bai, Yu, Gong, Jie, Han, Menghui
Publicado em:
IGI Global
Assuntos:
Data processing
Time dependence
Data mining
Deep learning
Big Data
Trends
Artificial neural networks
Social networks
Value
Prices
Financial institutions
Sentiment analysis
Knowledge representation
Learning
Language attitudes
Value analysis
Time
Knowledge
Securities markets
Natural language processing
Volatility
Unstructured data
Financial analysis
Information retrieval
Real time
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Resumo:Financial markets are inherently complex and influenced by a variety of factors, making it challenging to predict trends and detect key events. Traditional models often struggle to integrate both structured, or numerical, and unstructured, or textual, data; additionally, they fail to capture temporal dependencies or the dynamic relationships between financial entities. To address this, the multidimensional integrated model for financial text mining and value analysis (MI-FinText), was proposed. MI-FinText integrated multi-task learning, temporal graph convolutional networks and dynamic knowledge graph construction. MI-FinText simultaneously performed sentiment analysis, event detection, and value prediction by learning shared representations across tasks and modeling time-dependent relationships between financial events. MI-FinText continuously updated a dynamic knowledge graph to reflect the evolving financial landscape, enabling real-time insights.
ISSN:1546-2234
1546-5012
1043-6464
1063-2239
DOI:10.4018/JOEUC.374213
Fonte:ABI/INFORM Global