Offline Data-Driven Recommender Systems for Improving Small Business Marketing Strategies [0.03%]
用于改进小型企业营销策略的离线数据驱动推荐系统
Hwijae Son,Sung Woong Cho,Hyung Ju Hwang
Hwijae Son
Recommender systems play a crucial role in enhancing user engagement across domains such as e-commerce, social media, entertainment, and education. Recently, they have also been used in marketing to identify high-value customers and persona...
Advancing Dysarthric Speech-to-Text Recognition with LATTE: A Low-Latency Acoustic Modeling Approach for Real-Time Communication [0.03%]
用于实时通信的低延迟声学建模方法推动失语症语音转文本识别的发展LATTE
Qurat Ul Ain,Hammad Afzal,Fazli Subhan et al.
Qurat Ul Ain et al.
Dysarthria, a motor speech disorder characterized by slurred and often unintelligible speech, presents substantial challenges for effective communication. Conventional automatic speech recognition systems frequently underperform on dysarthr...
Perceived Usefulness, Trust, and Behavioral Intention: A Study on College Student User Adoption Behaviors of Artificial Intelligence Generated News Based on Technology Acceptance Model [0.03%]
基于技术接受模型的人工智能生成新闻的高校用户采纳行为研究——感知有用性、信任与行为意向的影响分析
Xianfeng Gong,Mingyang Mao
Xianfeng Gong
This study intends to identify the critical factors that shape college students' adoption of AI-generated news, with a specific focus on integrating Big Data methodologies into the Technology Acceptance Model (TAM) framework. Building on TA...
Real-Time Named Entity Recognition from Textual Electronic Clinical Records in Cancer Therapy Using Low-Latency Neural Networks [0.03%]
基于低延迟神经网络的实时文本电子临床记录命名实体识别以进行癌症治疗
Pir Noman Ahmad,Muhammad Shahid Anwar,Saleha Masood et al.
Pir Noman Ahmad et al.
Named entity recognition (NER) is a core task in natural language processing that identifies and classifies entities, such as people, organizations, and locations within text. It has traditionally been applied in areas like text summarizati...
Does Context Matter? The Role of Fine-Tuned Contextual Augmentation in Online Ad Delivery on Social Media [0.03%]
上下文很重要吗？社交网络上在线广告投放中精细调整的上下文增强的作用
Saifullah Jan,Iftikhar Alam,Inayat Khan
Saifullah Jan
This study presents a real-time, context-adaptive advertisement (ad in short) recommendation framework that dynamically updates user context and utilizes a multistage ranking and filtering pipeline to deliver highly relevant and personalize...
Enhancing NEV Brand Equity Through Big Data Analytics: An LDA-LSTM Approach to Mining Online Consumer Reviews [0.03%]
基于大数据分析的新能源汽车品牌资产研究：在线消费者评论的LDA-LSTM挖掘方法研究
Qiong He,Zhenwei Yang,Yijia Li
Qiong He
Enhancing brand value is critical for new energy vehicle (NEV) enterprises amid fierce competition. This study leverages online consumer reviews as core big data to drive brand equity improvement via advanced big data analytics. A large-sca...
Victor Chang,Péter Kacsuk,Gary Wills et al.
Victor Chang et al.
Editorial
Big data. 2025 Dec 22. DOI:10.1177/2167647X251406211 2025
The Two Worlds of Emergency Law: A Comparative Study of International and Chinese Scholarship Through Knowledge Domain Mapping [0.03%]
应急法的两个世界——基于知识图谱的国际与国内学术比较研究
Zhaodi Yu,Zhenxiang Xu,Jiangang Qi
Zhaodi Yu
In the context of a global risk society, emergency law has become a critical field for balancing the expansion of state power with the protection of civil rights during crises. Despite its growing importance, a systematic, quantitative comp...
Prediction of Remaining Life of Aircraft Engines Based on BiLSTM-GRU-Attention Model [0.03%]
基于BiLSTM-GRU-注意力模型的航空发动机剩余寿命预测
Qiong He,Xueqing Guo
Qiong He
This study aims to enhance the prediction precision of aircraft engine remaining useful life (RUL) by overcoming common challenges in current models, such as ineffective feature extraction and insufficient modeling of long-term temporal dep...
Method for Power Grid Digital Operation Data Integration Based on K-Medoids Clustering with Support for Real-Time Cross-Modal Applications [0.03%]
基于K-medoids聚类的电网数字运营数据集成方法及实时跨模态应用支持技术
Yuping Yan,Hanyang Xie,Liang Chen et al.
Yuping Yan et al.
Data in power grid digital operation exhibit multisource heterogeneous characteristics, resulting in low integration efficiency and slow anomaly detection response. To address this, this paper proposes a method for power grid digital operat...