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A Generative Approach for Financial Causality Extraction
Companion Proceedings of the Web Conference 2022, 2022 Causality represents the foremost relation between events in financial documents such as financial news articles, financial reports. Each financial causality contains a cause span and an effect span. Previous works proposed sequence labeling approaches to solve this task.
Tapas Nayak +5 more
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Frontiers in Computational Neuroscience, 2021 In recent years, affective computing based on electroencephalogram (EEG) data has attracted increased attention. As a classic EEG feature extraction model, Granger causality analysis has been widely used in emotion classification models, which construct ...
Dongwei Chen +5 more
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Causal graph extraction from news: a comparative study of time-series causality learning techniques [PDF]
PeerJ Computer Science, 2022 Causal graph extraction from news has the potential to aid in the understanding of complex scenarios. In particular, it can help explain and predict events, as well as conjecture about possible cause-effect connections.
Mariano Maisonnave +4 more
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Mining Causality via Information Bottleneck [PDF]
Jisuanji kexue, 2022 Causal discovery from observational data is a fundamental problem in many disciplines.However,existing methods such as constraint-based methods and causal function-based methods have strong assumptions on the causal mechanism of data,and are only ...
QIAO Jie, CAI Rui-chu, HAO Zhi-feng
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Exploratory Modeling: Extracting Causality From Complexity [PDF]
Eos, Transactions American Geophysical Union, 2014 On 22 May 2011 a massive tornado tore through Joplin, Mo., killing 158 people. With winds blowing faster than 200 miles per hour, the tornado was the most deadly in the United States since modern record keeping began in the 1950s.
Coulthard, Tom +4 more
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Extracting Causal Visual Features For Limited Label Classification [PDF]
2021 IEEE International Conference on Image Processing (ICIP), 2021 Neural networks trained to classify images do so by identifying features that allow them to distinguish between classes. These sets of features are either causal or context dependent. Grad-CAM is a popular method of visualizing both sets of features. In this paper, we formalize this feature divide and provide a methodology to extract causal features ...
Mohit Prabhushankar, Ghassan AlRegib
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Urban Rail Transit, 2023 With the promotion of the major strategy of national transportation power, the super-large-scale metro operation network has become an inevitable trend, and operation safety has become increasingly prominent.
Ding Xiaobing +3 more
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Tactical mission event logic graph construction for Network-Centric Warfare
Alexandria Engineering Journal, 2022 Constructing a Tactical Mission Event Logic Graph (TMELG) can assist military staff to analyze the composition and evolution process of tactical missions.
Hui Li +4 more
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Deep Learning for Human Activity Recognition Based on Causality Feature Extraction
IEEE Access, 2021 We propose a novel data-driven feature extraction approach based on direct causality and fuzzy temporal windows (FTWs) to improve the precision of human activity recognition and mitigate the problems of easily-confused activities and unlabeled data ...
Yu Min Hwang +4 more
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Event Causality Extraction with Event Argument Correlations
CoRR, 2023 Accepted to ...
Shiyao Cui +5 more
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