HATR-I: Hierarchical Adaptive Temporal Relational Interaction for Stock Trend Prediction-Reference-Cited by-同舟云学术

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HATR-I: Hierarchical Adaptive Temporal Relational Interaction for Stock Trend Prediction

Published:2022 Issue: Volume: Page:1-14
ISSN:1041-4347
Container-title:IEEE Transactions on Knowledge and Data Engineering
language:
Short-container-title:IEEE Trans. Knowl. Data Eng.

Author:

Wang Heyuan¹^ORCID,Wang Tengjiao¹^ORCID,Li Shun²^ORCID,Guan Shijie¹^ORCID

Affiliation:

1. School of Computer Science, National Engineering Laboratory for Big Data Analysis and Applications, Peking University, and Institute of Computational Social Science, Peking University (Qingdao), China

2. University of International Relations, China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computational Theory and Mathematics,Computer Science Applications,Information Systems

Link

http://xplorestaging.ieee.org/ielx7/69/4358933/09815165.pdf?arnumber=9815165

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Relational Fusion-based Stock Selection with Neural Recursive Ordinary Differential Equation Networks;Information Fusion;2024-10

2. SSCDV: Social media document embedding with sentiment and topics for financial market forecasting;Expert Systems with Applications;2024-07

3. Learning Informative Representation for Fairness-aware Multivariate Time-series Forecasting: A Group-based Perspective;IEEE Transactions on Knowledge and Data Engineering;2023

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