FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis-Reference-Cited by-同舟云学术

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FinXABSA: Explainable Finance through Aspect-Based Sentiment Analysis

Published:2023-12-04 Issue: Volume:6 Page:773-782
ISSN:
Container-title:2023 IEEE International Conference on Data Mining Workshops (ICDMW)
language:
Short-container-title:

Author:

Ong Keane¹,van der Heever Wihan²,Satapathy Ranjan³,Cambria Erik²,Mengaldo Gianmarco⁴

Affiliation:

1. Asian Institute of Digital Finance National University of Singapore,Singapore,117602

2. School of Computer Science and Engineering Nanyang Technological University,Singapore,639798

3. Institute of High Performance Computing (IHPC) Agency for Science, Technology and Research (A*STAR),Singapore,138632

4. College of Design & Engineering National University of Singapore,Singapore,117575

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10411504/10411508/10411537.pdf?arnumber=10411537

Reference50 articles.

1. Stop explaining black box machine learning models for high stakes decisions and use interpretable models instead

2. Aspect-based sentiment analysis via affective knowledge enhanced graph convolutional networks

3. Statistical Learning Theory and ELM for Big Social Data Analysis

4. Common Sense Computing: From the Society of Mind to Digital Intuition and beyond

5. Cognitive-inspired domain adaptation of sentiment lexicons

Cited by 2 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. Causal Inference and Prefix Prompt Engineering Based on Text Generation Models for Financial Argument Analysis;Electronics;2024-05-01

2. Financial Sentiment Analysis: Techniques and Applications;ACM Computing Surveys;2024-04-24

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