期刊名：Big Data and Cognitive Computing (BDCC)

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

Big Data and Cognitive Computing （大数据和认知计算）是一个国际性、跨学科的开放获取期刊，主要关注大数据与认知计算在计算机科学中的理论发展与技术应用。期刊研究方向涵盖大规模数据的存储、处理与分析，以及基于机器学习与数据挖掘的智能建模方法，同时强调认知计算在模拟人类感知、学习与决策过程中的作用。此外，期刊还关注云计算、物联网与高性能计算环境下的智能系统构建。整体而言，其研究重点体现为大数据技术与人工智能方法的融合发展。

本文选取多篇发表于2025年的代表性研究成果进行推荐，以期为相关研究提供有益参考与启发。

LLM Fine-Tuning: Concepts, Opportunities, and Challenges

大语言模型微调：概念、应用机遇与技术挑战

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. https://doi.org/10.3390/bdcc9040087

Artificial Intelligence in Digital Marketing: Towards an Analytical Framework for Revealing and Mitigating Bias

数字营销中的人工智能：偏差识别与缓解的分析框架构建

https://www.mdpi.com/2504-2289/9/2/40

Reed, C.; Wynn, M.; Bown, R. Artificial Intelligence in Digital Marketing: Towards an Analytical Framework for Revealing and Mitigating Bias. Big Data Cogn. Comput. 2025, 9, 40. https://doi.org/10.3390/bdcc9020040

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

基于数据挖掘的NBA球员分节表现模式识别方法研究

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. https://doi.org/10.3390/bdcc9040074

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

认知计算与商业智能在会计、金融及管理中的应用研究

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. https://doi.org/10.3390/bdcc9030054

Labeling Network Intrusion Detection System (NIDS) Rules with MITRE ATT&CK Techniques: Machine Learning vs. Large Language Models

基于MITRE ATT&CK技术的网络入侵检测规则标注：机器学习与大语言模型方法对比

https://www.mdpi.com/2504-2289/9/2/23

Daniel, N.; Kaiser, F.K.; Giladi, S.; Sharabi, S.; Moyal, R.; Shpolyansky, S.; Murillo, A.; Elyashar, A.; Puzis, R. Labeling Network Intrusion Detection System (NIDS) Rules with MITRE ATT&CK Techniques: Machine Learning vs. Large Language Models. Big Data Cogn. Comput. 2025, 9, 23. https://doi.org/10.3390/bdcc9020023

Generation Z’s Travel Behavior and Climate Change: A Comparative Study for Greece and the UK

Z世代出行行为与气候变化：基于希腊与英国的比较研究

https://www.mdpi.com/2504-2289/9/3/70

Demiris, A.; Fountas, G.; Fonzone, A.; Basbas, S. Generation Z’s Travel Behavior and Climate Change: A Comparative Study for Greece and the UK. Big Data Cogn. Comput. 2025, 9, 70. https://doi.org/10.3390/bdcc9030070

Enhancing Recommendation Systems with Real-Time Adaptive Learning and Multi-Domain Knowledge Graphs

融合实时自适应学习与多领域知识图谱的推荐系统优化方法

https://www.mdpi.com/2504-2289/9/5/124

Shahbazi, Z.; Jalali, R.; Shahbazi, Z. Enhancing Recommendation Systems with Real-Time Adaptive Learning and Multi-Domain Knowledge Graphs. Big Data Cogn. Comput. 2025, 9, 124. https://doi.org/10.3390/bdcc9050124

Trustworthy AI for Whom? GenAI Detection Techniques of Trust Through Decentralized Web3 Ecosystems

面向何种主体的可信人工智能？基于去中心化Web3生态的生成式AI信任检测技术研究

https://www.mdpi.com/2504-2289/9/3/62

Calzada, I.; Németh, G.; Al-Radhi, M.S. Trustworthy AI for Whom? GenAI Detection Techniques of Trust Through Decentralized Web3 Ecosystems. Big Data Cogn. Comput. 2025, 9, 62. https://doi.org/10.3390/bdcc9030062

Quantum-Cognitive Neural Networks: Assessing Confidence and Uncertainty with Human Decision-Making Simulations

量子认知神经网络：基于人类决策模拟的置信度与不确定性评估方法

https://www.mdpi.com/2504-2289/9/1/12

Maksimovic, M.; Maksymov, I.S. Quantum-Cognitive Neural Networks: Assessing Confidence and Uncertainty with Human Decision-Making Simulations. Big Data Cogn. Comput. 2025, 9, 12. https://doi.org/10.3390/bdcc9010012

Exploring Predictive Modeling for Food Quality Enhancement: A Case Study on Wine

食品质量提升的预测建模研究：以葡萄酒为例

https://www.mdpi.com/2504-2289/9/3/55

Yavas, C.E.; Kim, J.; Chen, L.; Kadlec, C.; Ji, Y. Exploring Predictive Modeling for Food Quality Enhancement: A Case Study on Wine. Big Data Cogn. Comput. 2025, 9, 55. https://doi.org/10.3390/bdcc9030055

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

小型语言模型的研究现状与发展趋势：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. https://doi.org/10.3390/bdcc9070189

Polarity of Yelp Reviews: A BERT–LSTM Comparative Study

Yelp评论情感极性分析：基于BERT与LSTM的比较研究

https://www.mdpi.com/2504-2289/9/5/140

Belaroussi, R.; Noufe, S.C.; Dupin, F.; Vandanjon, P.-O. Polarity of Yelp Reviews: A BERT–LSTM Comparative Study. Big Data Cogn. Comput. 2025, 9, 140. https://doi.org/10.3390/bdcc9050140

Benchmarking of Anomaly Detection Methods for Industry 4.0: Evaluation, Ranking, and Practical Recommendations

面向工业4.0的异常检测方法基准评估与应用建议

https://www.mdpi.com/2504-2289/9/5/128

Cools, A.; Belarbi, M.A.; Mahmoudi, S.A. Benchmarking of Anomaly Detection Methods for Industry 4.0: Evaluation, Ranking, and Practical Recommendations. Big Data Cogn. Comput. 2025, 9, 128. https://doi.org/10.3390/bdcc9050128

Evaluating Deep Learning Architectures for Breast Tumor Classification and Ultrasound Image Detection Using Transfer Learning

基于迁移学习的乳腺肿瘤分类与超声图像检测深度学习模型评估

https://www.mdpi.com/2504-2289/9/5/111

Kormpos, C.; Zantalis, F.; Katsoulis, S.; Koulouras, G. Evaluating Deep Learning Architectures for Breast Tumor Classification and Ultrasound Image Detection Using Transfer Learning. Big Data Cogn. Comput. 2025, 9, 111. https://doi.org/10.3390/bdcc9050111

Leveraging Open Big Data from R&D Projects with Large Language Models

基于大语言模型的研发项目开放大数据挖掘方法研究

https://www.mdpi.com/2504-2289/9/2/26

Ruiz, D.; Cardinale, Y.; Casas, A.; Moscardó, V. Leveraging Open Big Data from R&D Projects with Large Language Models. Big Data Cogn. Comput. 2025, 9, 26. https://doi.org/10.3390/bdcc9020026

A Web-Based Platform for Hand Rehabilitation Assessment

基于Web的手部康复评估平台设计与实现

https://www.mdpi.com/2504-2289/9/3/52

Soumis, D.N.; Tselikas, N.D. A Web-Based Platform for Hand Rehabilitation Assessment. Big Data Cogn. Comput. 2025, 9, 52. https://doi.org/10.3390/bdcc9030052

Towards the Adoption of Recommender Systems in Online Education: A Framework and Implementation

在线教育中推荐系统应用的框架设计与实现

https://www.mdpi.com/2504-2289/9/10/259

Martínez-Martínez, A.; Gómez-Cambronero, Á.; Montoliu, R.; Remolar, I. Towards the Adoption of Recommender Systems in Online Education: A Framework and Implementation. Big Data Cogn. Comput. 2025, 9, 259. https://doi.org/10.3390/bdcc9100259

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

区块链规模化应用路径研究：来自DeFi、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. https://doi.org/10.3390/bdcc9070178

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

教育领域生成式人工智能的元综述：发展趋势、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. https://doi.org/10.3390/bdcc9090237

Chinese Financial News Analysis for Sentiment and Stock Prediction: A Comparative Framework with Language Models

中文财经新闻情感分析与股票预测：基于语言模型的比较框架

https://www.mdpi.com/2504-2289/9/10/263

Chuang, H.-M.; He, H.-C.; Hu, M.-C. Chinese Financial News Analysis for Sentiment and Stock Prediction: A Comparative Framework with Language Models. Big Data Cogn. Comput. 2025, 9, 263. https://doi.org/10.3390/bdcc9100263

The Use of Large Language Models in Ophthalmology: A Scoping Review on Current Use-Cases and Considerations for Future Works in This Field

大语言模型在眼科领域的应用：现状综述与未来研究方向

https://www.mdpi.com/2504-2289/9/6/151

See, Y.K.C.; Lim, K.S.A.; Au, W.Y.; Chia, S.Y.C.; Fan, X.; Li, Z.K. The Use of Large Language Models in Ophthalmology: A Scoping Review on Current Use-Cases and Considerations for Future Works in This Field. Big Data Cogn. Comput. 2025, 9, 151. https://doi.org/10.3390/bdcc9060151

A Verifiable, Privacy-Preserving, and Poisoning Attack-Resilient Federated Learning Framework

一种可验证、隐私保护且抗投毒攻击的联邦学习框架

https://www.mdpi.com/2504-2289/9/4/85

Mbonu, W.E.; Maple, C.; Epiphaniou, G.; Panchev, C. A Verifiable, Privacy-Preserving, and Poisoning Attack-Resilient Federated Learning Framework. Big Data Cogn. Comput. 2025, 9, 85. https://doi.org/10.3390/bdcc9040085

期刊简介： 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。

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

陈敏，华南理工大学计算机科学与工程学院，琶洲实验室长聘教授、博导，人工智能领域专家，IEEE Fellow，全球人工智能领域高被引科学家。现任嵌入与普适计算（EPIC）实验室主任，IET Fellow、AAIA Fellow。2012年入选高层次人才计划，教育部新世纪优秀人才，2014年入选湖北省杰青。曾任湖北省智能认知技术国际合作基地主任。2020年（40岁以下）当选为IEEE Fellow（国际电气电子工程师学会会士），并自2018年至2025年连续八次入选科睿唯安全球高被引科学家榜。长期专注于认知计算、大模型、人工智能、脑科学交叉研究，现已出版学术专著或教材12部，谷歌学术总引用超过5.2万次，H指数101（中国H指数100或以上的计算机方向学者不到30人，占全球相关研究人员的 0.0016%）。发表SCI论文200余篇，发表 CCF A类会议、IEEE-ACM Trans./Magazine论文80余篇，34篇ESI高被引论文，12篇ESI热点论文，单篇最高引用超过5200次。