Results 31 to 40 of about 39,390 (254)

A Review of Dataset and Labeling Methods for Causality Extraction [PDF]

Proceedings of the 28th International Conference on Computational Linguistics, 2020
Causality represents the most important kind of correlation between events. Extracting causali-ty from text has become a promising hot topic in NLP. However, there is no mature research systems and datasets for public evaluation. Moreover, there is a lack of unified causal sequence label methods, which constitute the key factors that hinder the ...
Jinghang Xu, Wanli Zuo, Shining Liang, Xianglin Zuo   +3 more
openaire   +1 more source

Hybrid Decision-Making-Method-Based Intelligent System for Integrated Bogie Welding Manufacturing

Applied System Innovation, 2023
To address the challenges of incomplete knowledge representation, independent decision ranges, and insufficient causal decisions in bogie welding decisions, this paper proposes a hybrid decision-making method and develops a corresponding intelligent ...
Kainan Guan, Yang Sun, Guang Yang, Xinhua Yang   +3 more
doaj   +1 more source

Extracting the Multiscale Causal Backbone of Brain Dynamics

CoRR, 2023
The bulk of the research effort on brain connectivity revolves around statistical associations among brain regions, which do not directly relate to the causal mechanisms governing brain dynamics. Here we propose the multiscale causal backbone (MCB) of brain dynamics, shared by a set of individuals across multiple temporal scales, and devise a ...
Gabriele D'Acunto, Francesco Bonchi, Gianmarco De Francisci Morales, Giovanni Petri   +3 more
openaire   +4 more sources

Causal games of work extraction with indefinite causal order

Physical Review A, 2022
6 pages, 1 figure.
openaire   +2 more sources

A Data Feature Extraction Method Based on the NOTEARS Causal Inference Algorithm

Applied Sciences, 2023
Extracting effective features from high-dimensional datasets is crucial for determining the accuracy of regression and classification models. Model predictions based on causality are known for their robustness.
Hairui Wang, Junming Li, Guifu Zhu
doaj   +1 more source

Unravelling the dynamics of human development and economic growth on crude oil production based on ARDL and NARDL models

MethodsX, 2023
This paper estimates and establishes the causality between the Human Development Index (HDI), Gross Domestic Product (GDP), inflation and CO2 emissions on crude oil production (COP) in Cameroon from 1977 to 2019.
Jean Marie Stevy Sama, Flavian Emmanuel Sapnken, Inoussah Moungnutou Mfetoum, Jean Gaston Tamba   +3 more
doaj   +1 more source

Event-Conditioned Causal Extraction in Saudi Dialect: A Comparative Study of Dialect-Trained BERTs and LLM Prompting

Informatics
Causality extraction is an important task in natural language processing, yet it remains underexplored in informal Arabic social media text, particularly in dialectal contexts.
Mariam Elhussein, Samiha Brahimi, Reem Osman, Suhier Elfaki   +3 more
doaj   +1 more source

Improving Causality Induction with Category Learning

The Scientific World Journal, 2014
Causal relations are of fundamental importance for human perception and reasoning. According to the nature of causality, causality has explicit and implicit forms. In the case of explicit form, causal-effect relations exist at either clausal or discourse
Yi Guo, Zhihong Wang, Zhiqing Shao
doaj   +1 more source

End-to-end multi-granulation causality extraction model

Digital Communications and Networks
Causality extraction has become a crucial task in natural language processing and knowledge graph. However, most existing methods divide causality extraction into two subtasks: extraction of candidate causal pairs and classification of causality.
Miao Wu, Qinghua Zhang, Chengying Wu, Guoyin Wang   +3 more
doaj   +1 more source

Causal-INSIGHT: Probing Temporal Models to Extract Causal Structure

CoRR
Accepted at IJCNN ...
Benjamin Redden, Hui Wang, Shuyan Li
openaire   +2 more sources