Feature Extraction and Algorithm Analysis of Financial and Accounting Data in the Era of Big Data

Haiying Su

2025

Abstract

This study focuses on feature extraction and algorithm analysis of financial and accounting data in the era of big data, including key steps such as data preprocessing, feature selection and construction, data transformation and structuring, modeling and prediction. Through the application of big data analysis technologies such as machine learning and deep learning, the accuracy of financial forecasting and risk assessment is improved. The research results should focus on the practical application value, and verify the explanatory and operability of the model through case studies. Feature selection and data transformation are critical steps to reduce analysis complexity and improve model explanatory power. These findings and models will directly guide corporate financial management practices, improve operational efficiency, and reduce decision-making risk. In short, the extraction of financial and accounting data features and algorithm analysis in the era of big data is a transformation of technology application and way of thinking, which promotes the transformation of financial analysis from traditional qualitative description to quantitative forecasting, and finds the right direction for enterprises to achieve sustainable development in the complex and changeable market environment.

Paper Citation

in Harvard Style

Su H. (2025). Feature Extraction and Algorithm Analysis of Financial and Accounting Data in the Era of Big Data. In Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT; ISBN 978-989-758-763-4, SciTePress, pages 39-44. DOI: 10.5220/0013535000004664

in Bibtex Style

@conference{incoft25,
author={Haiying Su},
title={Feature Extraction and Algorithm Analysis of Financial and Accounting Data in the Era of Big Data},
booktitle={Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT},
year={2025},
pages={39-44},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013535000004664},
isbn={978-989-758-763-4},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 3rd International Conference on Futuristic Technology - Volume 1: INCOFT
TI - Feature Extraction and Algorithm Analysis of Financial and Accounting Data in the Era of Big Data
SN - 978-989-758-763-4
AU - Su H.
PY - 2025
SP - 39
EP - 44
DO - 10.5220/0013535000004664
PB - SciTePress