期刊名： Big Data and Cognitive Computing

期刊主页：https://www.mdpi.com/journal/BDCC

大数据与认知计算的深度融合，正在重塑从数据采集、智能建模到决策优化的全链条技术范式。Big Data and Cognitive Computing 作为面向这一交叉领域的国际性、跨学科开放获取期刊，致力于探索大数据处理与分析、云计算与物联网架构，以及模拟人类感知与决策的认知计算等前沿方向。本期文献清单精选了2025年度备受关注的高浏览文章，所涉研究涵盖大数据智能处理框架、认知计算模型与算法、分布式系统与边缘智能架构，以及数据驱动的实证分析与应用探索等多个层面，同时兼顾了数据治理、区块链融合等基础设施议题。这些成果从不同维度呼应了期刊在大数据与认知计算交叉领域的前沿定位，集中展现了该领域方法创新与场景拓展的蓬勃活力，以期为相关领域学者提供有益的参考与启发。

1. LLM Fine-Tuning: Concepts, Opportunities, and Challenges

大语言模型微调：概念、机遇与挑战

https://www.mdpi.com/2504-2289/9/4/87

Wu, X.-K.; Chen, M.; Li, W.; Wang, R.; Lu, L.; Liu, J.; Hwang, K.; Hao, Y.; Pan, Y.; Meng, Q.; et al. LLM Fine-Tuning: Concepts, Opportunities, and Challenges. Big Data Cogn. Comput. 2025, 9, 87.

2. Toward the Mass Adoption of Blockchain: Cross-Industry Insights from DeFi, Gaming, and Data Analytics

迈向区块链的大规模应用：来自去中心化金融、游戏与数据分析的跨行业洞察

https://www.mdpi.com/2504-2289/9/7/178

Mohammed Abdul, S.S.; Shrestha, A.; Yong, J. Toward the Mass Adoption of Blockchain: Cross-Industry Insights from DeFi, Gaming, and Data Analytics. Big Data Cogn. Comput. 2025, 9, 178.

3. State of the Art and Future Directions of Small Language Models: A Systematic Review

小语言模型的研究现状与未来方向：系统性综述

https://www.mdpi.com/2504-2289/9/7/189

Corradini, F.; Leonesi, M.; Piangerelli, M. State of the Art and Future Directions of Small Language Models: A Systematic Review. Big Data Cogn. Comput. 2025, 9, 189.

4. The Importance of AI Data Governance in Large Language Models

大语言模型中AI数据治理的重要性

https://www.mdpi.com/2504-2289/9/6/147

Pahune, S.; Akhtar, Z.; Mandapati, V.; Siddique, K. The Importance of AI Data Governance in Large Language Models. Big Data Cogn. Comput. 2025, 9, 147.

5. A Comparison of Data Quality Frameworks: A Review

数据质量框架比较研究：综述

https://www.mdpi.com/2504-2289/9/4/93

Miller, R.; Chan, S.H.M.; Whelan, H.; Gregório, J. A Comparison of Data Quality Frameworks: A Review. Big Data Cogn. Comput. 2025, 9, 93.

6. Survey on the Role of Mechanistic Interpretability in Generative AI

机制可解释性在生成式人工智能中的作用研究综述

https://www.mdpi.com/2504-2289/9/8/193

Ranaldi, L. Survey on the Role of Mechanistic Interpretability in Generative AI. Big Data Cogn. Comput. 2025, 9, 193.

7. A Data Mining Approach to Identify NBA Player Quarter-by-Quarter Performance Patterns

基于数据挖掘方法的NBA球员逐节表现模式识别

https://www.mdpi.com/2504-2289/9/4/74

Iatropoulos, D.; Sarlis, V.; Tjortjis, C. A Data Mining Approach to Identify NBA Player Quarter-by-Quarter Performance Patterns. Big Data Cogn. Comput. 2025, 9, 74.

8. Fusion of Sentiment and Market Signals for Bitcoin Forecasting: A SentiStack Network Based on a Stacking LSTM Architecture

融合情绪信号与市场信号的比特币预测：基于堆叠LSTM架构的SentiStack网络

https://www.mdpi.com/2504-2289/9/6/161

Zhang, Z.; Jiang, C.; Lu, M. Fusion of Sentiment and Market Signals for Bitcoin Forecasting: A SentiStack Network Based on a Stacking LSTM Architecture. Big Data Cogn. Comput. 2025, 9, 161.

9. A Systematic Literature Review of Retrieval-Augmented Generation: Techniques, Metrics, and Challenges

检索增强生成的系统文献综述：技术、指标与挑战

https://www.mdpi.com/2504-2289/9/12/320

Brown, A.; Roman, M.; Devereux, B. A Systematic Literature Review of Retrieval-Augmented Generation: Techniques, Metrics, and Challenges. Big Data Cogn. Comput. 2025, 9, 320.

10. ChatGPT’s Impact Across Sectors: A Systematic Review of Key Themes and Challenges

ChatGPT的跨行业影响：关键主题与挑战的系统性综述

https://www.mdpi.com/2504-2289/9/3/56

Hussein, H.; Gordon, M.; Hodgkinson, C.; Foreman, R.; Wagad, S. ChatGPT’s Impact Across Sectors: A Systematic Review of Key Themes and Challenges. Big Data Cogn. Comput. 2025, 9, 56.

11. Efficient Data Augmentation Methods for Crop Disease Recognition in Sustainable Environmental Systems

面向可持续环境系统的作物病害识别高效数据增强方法

https://www.mdpi.com/2504-2289/9/1/8

Lee, S.; Lee, S. Efficient Data Augmentation Methods for Crop Disease Recognition in Sustainable Environmental Systems. Big Data Cogn. Comput. 2025, 9, 8.

12. AI-Driven Mental Health Surveillance: Identifying Suicidal Ideation Through Machine Learning Techniques

AI驱动的心理健康监测：基于机器学习技术的自杀意念识别

https://www.mdpi.com/2504-2289/9/1/16

Allam, H.; Davison, C.; Kalota, F.; Lazaros, E.; Hua, D. AI-Driven Mental Health Surveillance: Identifying Suicidal Ideation Through Machine Learning Techniques. Big Data Cogn. Comput. 2025, 9, 16.

13. A Meta-Survey of Generative AI in Education: Trends, Challenges, and Research Directions

生成式人工智能在教育领域的元综述：趋势、挑战与研究方向

https://www.mdpi.com/2504-2289/9/9/237

Bouguettaya, S.; Pupo, F.; Chen, M.; Fortino, G. A Meta-Survey of Generative AI in Education: Trends, Challenges, and Research Directions. Big Data Cogn. Comput. 2025, 9, 237.

14. An Expected Goals On Target (xGOT) Model: Accounting for Goalkeeper Performance in Football

预期射正进球（xGOT）模型：足球守门员表现的量化评估

https://www.mdpi.com/2504-2289/9/3/64

De-la-Cruz-Torres, B.; Navarro-Castro, M.; Ruiz-de-Alarcón-Quintero, A. An Expected Goals On Target (xGOT) Model: Accounting for Goalkeeper Performance in Football. Big Data Cogn. Comput. 2025, 9, 64.

15. A Systematic Literature Review of Artificial Intelligence in Prehospital Emergency Care

人工智能在院前急救中的应用：系统文献综述

https://www.mdpi.com/2504-2289/9/9/219

Elfahim, O.; Edjinedja, K.L.; Cossus, J.; Youssfi, M.; Barakat, O.; Desmettre, T. A Systematic Literature Review of Artificial Intelligence in Prehospital Emergency Care. Big Data Cogn. Comput. 2025, 9, 219.

16. Transitioning from TinyML to Edge GenAI: A Review

从TinyML到边缘生成式AI的演进：综述

https://www.mdpi.com/2504-2289/9/3/61

Giorgetti, G.; Pau, D.P. Transitioning from TinyML to Edge GenAI: A Review. Big Data Cogn. Comput. 2025, 9, 61.

17. Cognitive Computing and Business Intelligence Applications in Accounting, Finance and Management

认知计算与商业智能在会计、金融与管理中的应用

https://www.mdpi.com/2504-2289/9/3/54

Ao, S.-I.; Hurwitz, M.; Palade, V. Cognitive Computing and Business Intelligence Applications in Accounting, Finance and Management. Big Data Cogn. Comput. 2025, 9, 54.

期刊介绍

主编：Min Chen, South China University of Technology, China

Big Data and Cognitive Computing (ISSN: 2504-2289)创刊于2017年，是面向计算机科学大数据与认知计算的国际性、跨学科、开放获取的学术期刊，主要发表与大数据、云计算、认知计算、人工智能通信、数据分析、移动大数据、认知学习、机器学习等相关主题的原创研究论文。期刊旨在将大数据理论与智能云新兴技术结合起来，并探索超级计算机的新应用。目前已被 Scopus, ESCI (Web of Science), dblp, Inspec, Ei Compendex等多个数据库收录。

2025 Impact Factor：5.3

2025 CiteScore：11.4

Time to First Decision：23.3 Days

Acceptance to Publication：4.8 Days