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2020 COLING COLING 2020

NITK NLP at FinCausal-2020 Task 1 Using BERT and Linear models.

Abstract

AbstractFinCausal-2020 is the shared task which focuses on the causality detection of factual data for financial analysis. The financial data facts donโ€™t provide much explanation on the variability of these data. This paper aims to propose an efficient method to classify the data into one which is having any financial cause or not. Many models were used to classify the data, out of which SVM model gave an F-Score of 0.9435, BERT with specific fine-tuning achieved best results with F-Score of 0.9677.

๐ŸŒ‰ Interdisciplinary Bridge โ€” Artificial Intelligence and Machine Learning
๐Ÿ Cross-Pollinator โ€” Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio

Authors

Hariharan R L , Anand Kumar M

Topics

Artificial Intelligence > Core AI > Causal Inference Machine Learning > Core Methods > Classification Machine Learning > Optimization & Theory > Neural Network Optimization

Keywords

text classification financial analysis support vector machine causality detection
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