Information Processing & Management最新文献

筛选
英文 中文
Unsupervised Adaptive Hypergraph Correlation Hashing for multimedia retrieval 用于多媒体检索的无监督自适应超图相关性哈希算法
IF 7.4 1区 管理学
Information Processing & Management Pub Date : 2024-11-18 DOI: 10.1016/j.ipm.2024.103958
Yunfei Chen , Yitian Long , Zhan Yang , Jun Long
{"title":"Unsupervised Adaptive Hypergraph Correlation Hashing for multimedia retrieval","authors":"Yunfei Chen ,&nbsp;Yitian Long ,&nbsp;Zhan Yang ,&nbsp;Jun Long","doi":"10.1016/j.ipm.2024.103958","DOIUrl":"10.1016/j.ipm.2024.103958","url":null,"abstract":"<div><div>Cross-modal hashing has attracted widespread attention from researchers due to its capabilities to handle large volumes of heterogeneous multimedia information with fast retrieval speed and low storage cost. However, current cross-modal hashing methods still face issues such as incomplete embedding of semantic correlation information and long parameter tuning cycles. To address these problems, we propose a method called Unsupervised Adaptive Hypergraph Correlation Hashing (UAHCH). First, the hypergraph-based correlation enhanced hashing constructs a hypergraph based on semantic information and correlation information, leveraging a hypergraph neural network to integrate the hypergraph information into the hash codes, ensuring the richness of the semantics and the integrity of correlation relationships. Next, the fast parameter adaptive strategy is designed for the automated optimization of neural network parameters for the UAHCH method and various neural network models, achieving optimal performance more efficiently. Finally, comprehensive experiments are conducted on widely used datasets. The results show that the proposed UAHCH method achieves superior performance, with average improvements of 3.06% on MIRFlickr, 1.45% on NUS-WIDE, and 4.65% on MSCOCO compared to the latest baseline methods. The code has been made publicly available at <span><span>https://github.com/YunfeiChenMY/UAHCH</span><svg><path></path></svg></span>.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 2","pages":"Article 103958"},"PeriodicalIF":7.4,"publicationDate":"2024-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142652917","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhancing robustness in implicit feedback recommender systems with subgraph contrastive learning 利用子图对比学习增强隐式反馈推荐系统的鲁棒性
IF 7.4 1区 管理学
Information Processing & Management Pub Date : 2024-11-16 DOI: 10.1016/j.ipm.2024.103962
Yi Yang , Shaopeng Guan , Xiaoyang Wen
{"title":"Enhancing robustness in implicit feedback recommender systems with subgraph contrastive learning","authors":"Yi Yang ,&nbsp;Shaopeng Guan ,&nbsp;Xiaoyang Wen","doi":"10.1016/j.ipm.2024.103962","DOIUrl":"10.1016/j.ipm.2024.103962","url":null,"abstract":"<div><div>Contrastive learning operates by distinguishing differences between various nodes to facilitate item recommendations. However, current graph contrastive learning (GCL) methods suffer from insufficient robustness. To mitigate the impact of noise and accurately capture user preferences, we propose a subgraph-based GCL method: SubGCL. Firstly, we devise a dynamic perceptual signal extractor that leverages node degree and neighborhood information to model subgraphs corresponding to nodes and compute mutual information scores. This approach enhances view adaptivity, thereby improving data augmentation robustness against noise perturbations. Secondly, we develop an association graph self-attention propagation mechanism. This mechanism constructs node clusters by randomly sampling nodes and edges, facilitating self-attention propagation on the graph to learn cluster associations and enhance recommendation accuracy. Finally, we reconstruct graph structures through recommendation loss and update node embeddings via contrastive learning to bolster the model’s accuracy and robustness in implicit feedback data. We conducted experiments on three publicly available real-world datasets. Results demonstrate that, compared to existing contrastive learning recommendation approaches, SubGCL achieves an average improvement of 4.96% and 3.98% in Recall and NDCG metrics, respectively.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 1","pages":"Article 103962"},"PeriodicalIF":7.4,"publicationDate":"2024-11-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657713","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Patients' cognitive and behavioral paradoxes in the process of adopting conflicting health information: A dynamic perspective 患者在接受相互矛盾的健康信息过程中的认知和行为悖论:动态视角
IF 7.4 1区 管理学
Information Processing & Management Pub Date : 2024-11-15 DOI: 10.1016/j.ipm.2024.103939
Yan Jin , Di Zhao , Zhuo Sun , Chongwu Bi , Ruixian Yang , Shengli Deng
{"title":"Patients' cognitive and behavioral paradoxes in the process of adopting conflicting health information: A dynamic perspective","authors":"Yan Jin ,&nbsp;Di Zhao ,&nbsp;Zhuo Sun ,&nbsp;Chongwu Bi ,&nbsp;Ruixian Yang ,&nbsp;Shengli Deng","doi":"10.1016/j.ipm.2024.103939","DOIUrl":"10.1016/j.ipm.2024.103939","url":null,"abstract":"<div><div>Diversified access to health information has increased the likelihood of encountering conflicting health messages, making it more difficult for patients to adopt information rationally. Prior research has primarily focused on the outcomes of patients' information adoption and responded to concerns by exploring the influences that led to these outcomes, overlooking a crucial aspect. Specifically, patients' cognitive and behavioral responses are continuously fluctuating during the process of information adoption. A total of 336 subjects (valid sample) participated in this study. A combination of situational experiments, grounded theory, and questionnaires was employed to develop a model of patients' adoption of conflicting health information. The concept of \"trans-theory\" was introduced to explain how patients' cognitive and behavioral responses changed at different segments of adoption. In contrast to prior studies viewing information adoption as a whole, we propose that the process can be divided into four distinct segments: information attention, comprehension, evaluation, and decision. Moreover, the sequential influence of information, ability, psychological, and environmental factors in the adoption process produces three common paradoxes in patients' cognitive and behavioral responses, affecting their ability to make rational adoption decisions. This study explores the dynamics of information adoption from the patient's perspective, providing novel insights into the study of conflicting health information adoption and offering guidance for designing more effective interventions for facilitating rational adoption by patients. Additionally, it can help the healthcare system better understand patients' cognitive and behavioral responses to deliver more effective healthcare services.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 1","pages":"Article 103939"},"PeriodicalIF":7.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657712","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Domain disentanglement and fusion based on hyperbolic neural networks for zero-shot sketch-based image retrieval 基于双曲神经网络的基于零镜头草图的图像检索的域分解和融合
IF 7.4 1区 管理学
Information Processing & Management Pub Date : 2024-11-15 DOI: 10.1016/j.ipm.2024.103963
Qing Zhang , Jing Zhang , Xiangdong Su , Yonghe Wang , Feilong Bao , Guanglai Gao
{"title":"Domain disentanglement and fusion based on hyperbolic neural networks for zero-shot sketch-based image retrieval","authors":"Qing Zhang ,&nbsp;Jing Zhang ,&nbsp;Xiangdong Su ,&nbsp;Yonghe Wang ,&nbsp;Feilong Bao ,&nbsp;Guanglai Gao","doi":"10.1016/j.ipm.2024.103963","DOIUrl":"10.1016/j.ipm.2024.103963","url":null,"abstract":"<div><div>With the advancement of zero-shot sketch-based image retrieval (ZS-SBIR) tasks, existing methods still encounter two major challenges: Euclidean space fails to effectively represent data with hierarchical structures, leading to non-discriminative retrieval features; relying solely on visual information is insufficient to align cross-domain features and maximize their domain generalization capabilities. To tackle these issues, this paper designs a hyperbolic neural networks based ZS-SBIR framework that considers domain disentanglement and fusion learning, called “DDFUS”. Specifically, we present a contrastive cross-modal learning method that guides the alignment of multi-domain visual representations with semantic representations in the hyperbolic space. This approach ensures that each visual representation possesses rich semantic hierarchical structure information. Furthermore, we propose a domain disentanglement method based on hyperbolic neural networks that employs paired hyperbolic encoders to decompose the representation of each domain into domain-invariant and domain-specific features to reduce information disturbance between domains. Moreover, we design an advanced cross-domain fusion method that promotes the fusion and exchange of multi-domain information through the reconstruction and generation of cross-domain samples. It significantly enhances the representation and generalization capabilities of domain-invariant features. Comprehensive experiments demonstrate that the mAP@all of our DDFUS model surpasses CNN-based models by 18.99 % on the Sketchy dataset, 1.93 % on the more difficult TU-Berlin dataset, and 11.4 % on the more challenging QuickDraw dataset.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 1","pages":"Article 103963"},"PeriodicalIF":7.4,"publicationDate":"2024-11-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657711","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Enhancing video rumor detection through multimodal deep feature fusion with time-sync comments 通过多模态深度特征融合与时间同步评论加强视频谣言检测
IF 7.4 1区 管理学
Information Processing & Management Pub Date : 2024-11-14 DOI: 10.1016/j.ipm.2024.103935
Ming Yin , Wei Chen , Dan Zhu , Jijiao Jiang
{"title":"Enhancing video rumor detection through multimodal deep feature fusion with time-sync comments","authors":"Ming Yin ,&nbsp;Wei Chen ,&nbsp;Dan Zhu ,&nbsp;Jijiao Jiang","doi":"10.1016/j.ipm.2024.103935","DOIUrl":"10.1016/j.ipm.2024.103935","url":null,"abstract":"<div><div>Rumors in videos have a stronger propagation compared to traditional text or image rumors. Most current studies on video rumor detection often rely on combining user and video modal information while neglecting the internal multimodal aspects of the video and the relationship between user comments and local segment of the video. To address this problem, we propose a method called Time-Sync Comment Enhanced Multimodal Deep Feature Fusion Model (TSC-MDFFM). It introduces time-sync comments to enhance the propagation structure of videos on social networks, supplementing missing contextual or additional information in videos. Time-sync comments focus on expressing users' views on specific points in time in the video, which helps to obtain more valuable segments from videos with high density information. The time interval from one keyframe to the next in a video is defined as a local segment. We thoroughly described this segment using time-sync comments, video keyframes, and video subtitle texts. The local segment sequences are ordered based on the video timeline and assigned time information, then fused to create the local feature representation of the video. Subsequently, we fused the text features, video motion features, and visual features of video comments at the feature level to represent the global features of the video. This feature not only captures the overall propagation trend of video content, but also provides a deep understanding of the overall features of the video. Finally, we will integrate local and global features for video rumor classification, to combine the local and global information of the video. We created a dataset called TSC-VRD, which includes time-sync comments and encompasses all visible information in videos. Extensive experimental results have shown superior performance of our proposed model compared to existing methods on the TSC-VRD dataset.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 1","pages":"Article 103935"},"PeriodicalIF":7.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657710","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Study of technology communities and dominant technology lock-in in the Internet of Things domain - Based on social network analysis of patent network 物联网领域的技术社群和主导技术锁定研究--基于专利网络的社会网络分析
IF 7.4 1区 管理学
Information Processing & Management Pub Date : 2024-11-14 DOI: 10.1016/j.ipm.2024.103959
Xueting Yang , Bing Sun , Shilong Liu
{"title":"Study of technology communities and dominant technology lock-in in the Internet of Things domain - Based on social network analysis of patent network","authors":"Xueting Yang ,&nbsp;Bing Sun ,&nbsp;Shilong Liu","doi":"10.1016/j.ipm.2024.103959","DOIUrl":"10.1016/j.ipm.2024.103959","url":null,"abstract":"<div><div>The evolution of technology communities and the lock-in process of dominant technologies influence the advancement of the Internet of Things (IoT) in achieving its goal of connecting everything. This study aims to identify and analyze IoT technology communities and main technology trajectories, and to trace and explore the lock-in and unlocking process of IoT dominant technologies. A directed citation network was constructed using 9,464 IoT patent families as nodes and 23,604 inter-patent citation relationships as directed links. We used the Louvain algorithm and Latent Dirichlet Allocation (LDA) modeling technique to divide the communities and extract their themes, and the SPLC algorithm and key-route global main path search method to identify the dominant technology trajectories. The results show that first, technologies that emerged during the embryonic stage of IoT exhibit a declining trend as the standardization process of IoT progresses; technologies introduced during IoT's growing stage continue to increase, benefiting from the positive cyclical effect of application and integrated innovation. Second, major developments in IoT involve device risk assessment, machine learning, and machine-to-machine technologies. Third, the lock-in of IoT dominant technologies is accompanied by a 'learning by using' effect and an incremental succession of innovations. The novelty of this study lies in the combination of both community analysis and main path analysis methods, which help researchers and participators grasp the IoT technology development holistically from both horizontal - technology categorization and vertical - time perspectives. Meanwhile, we also analyzed the lock-in and unlocking process of IoT dominant technologies to provide a reference for participators to develop technological strategies.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 1","pages":"Article 103959"},"PeriodicalIF":7.4,"publicationDate":"2024-11-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657709","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Metaverse-based distance learning as a transactional distance mitigator and memory retrieval stimulant 基于元数据的远程学习是一种交易距离缓解剂和记忆检索刺激剂
IF 7.4 1区 管理学
Information Processing & Management Pub Date : 2024-11-11 DOI: 10.1016/j.ipm.2024.103957
Cheong Kim , Francis Joseph Costello , Jungwoo Lee , Kun Chang Lee
{"title":"Metaverse-based distance learning as a transactional distance mitigator and memory retrieval stimulant","authors":"Cheong Kim ,&nbsp;Francis Joseph Costello ,&nbsp;Jungwoo Lee ,&nbsp;Kun Chang Lee","doi":"10.1016/j.ipm.2024.103957","DOIUrl":"10.1016/j.ipm.2024.103957","url":null,"abstract":"<div><div>This present study explores Metaverse-based Distance Learning (MDL) as a mitigative strategy of transactional distance (TD) and an enhancer of memory retrieval in an educational setting. We conducted two experimental studies. In the first study (<em>n</em> = 367 participants), we found that MDL significantly reduced perceived TD, leading to positive learner attitudes and increased intentions for repeat learning. The second study utilized functional Near-Infrared Spectroscopy (fNIRS) to assess hemodynamic responses in the prefrontal cortex of 30 participants, comparing brain activity during lectures in MDL and e-learning environments. Results indicated that MDL elicited higher oxy-Hb activation in the prefrontal cortex, particularly during cognitively challenging tasks, correlating with improved memory retrieval. Grounded in both Transactional Distance Theory (TDT) and context-dependent memory (CDM) frameworks, we found that the technological and educational potential of MDL not only reduces psychological barriers in distance learning but also shows how it can improve cognitive engagement and retention. These findings underscore the potential of MDL in distance education and suggest pathways for future research to explore its implications further, particularly in conjunction with other emerging technologies.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 1","pages":"Article 103957"},"PeriodicalIF":7.4,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657708","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Detecting and regulating sentiment reversal and polarization in online communities 检测和调节网络社区中的情绪逆转和两极分化
IF 7.4 1区 管理学
Information Processing & Management Pub Date : 2024-11-11 DOI: 10.1016/j.ipm.2024.103965
Yuqi Tao , Bin Hu , Zilin Zeng , Xiaomeng Ma
{"title":"Detecting and regulating sentiment reversal and polarization in online communities","authors":"Yuqi Tao ,&nbsp;Bin Hu ,&nbsp;Zilin Zeng ,&nbsp;Xiaomeng Ma","doi":"10.1016/j.ipm.2024.103965","DOIUrl":"10.1016/j.ipm.2024.103965","url":null,"abstract":"<div><div>Sentiment reversals and polarizations can disrupt the harmony within a legitimate and peaceful online communication environment. To fill the research gaps, this paper introduces detection methods grounded in catastrophe theory and proposes two innovative regulatory strategies: reversal control strategy (RCS) and polarization control strategy (PCS). Experiments and empirical analysis are conducted on a self-built dataset encompassing approximately 50,000 user groups from Baidu Tieba. In the detection phase, the stochastic catastrophe model achieves an <span><math><msup><mrow><mi>R</mi></mrow><mn>2</mn></msup></math></span> of 0.57, a reversal index of 0.18 and a polarization index of 0.29, indicating the existence of sentiment reversal and polarization. In the regulation phase, RCS outperforms control groups by up to 53% and PCS outperforms control groups by up to 63%. Our empirical analysis reveals two insights. Firstly, an excessive regulation intensity does not proportionally increase benefits but instead diminishes the effectiveness of regulation. Secondly, strategies aim to preventing sentiment reversals can lead to sentiment polarizations and vice versa. This study holds theoretical and practical significance for the decision-making of online communities’ regulation, and also contributes to the management application of catastrophe theory.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 1","pages":"Article 103965"},"PeriodicalIF":7.4,"publicationDate":"2024-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657717","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Spatial network disintegration based on ranking aggregation 基于排序聚合的空间网络分解
IF 7.4 1区 管理学
Information Processing & Management Pub Date : 2024-11-09 DOI: 10.1016/j.ipm.2024.103955
Zhigang Wang , Ye Deng , Yu Dong , Jürgen Kurths , Jun Wu
{"title":"Spatial network disintegration based on ranking aggregation","authors":"Zhigang Wang ,&nbsp;Ye Deng ,&nbsp;Yu Dong ,&nbsp;Jürgen Kurths ,&nbsp;Jun Wu","doi":"10.1016/j.ipm.2024.103955","DOIUrl":"10.1016/j.ipm.2024.103955","url":null,"abstract":"<div><div>Disintegrating harmful networks presents a significant challenge, especially in spatial networks where both topological and geospatial features must be considered. Existing methods that rely on a single metric often fail to capture the full complexity of such networks. To address these limitations, we propose a novel ranking aggregation-based algorithm for spatial network disintegration. Our approach integrates multiple region centrality metrics, providing a comprehensive evaluation of region importance. The algorithm operates in two stages: first, multiple rankings based on different centrality metrics are aggregated into a composite ranking to refine the candidate regions for disintegration. In the second stage, an exact target enumeration method is applied within this candidate set to determine the optimal combination of regions that maximizes disintegration impact. This interconnected approach effectively combines ranking aggregation with targeted enumeration to ensure both efficiency and accuracy. Extensive experiments are conducted on synthetic and real-world spatial networks of different network configurations. The results demonstrate that our method consistently achieves superior disintegration performance compared to traditional approaches, effectively addressing the challenges associated with spatial network disintegration. This study provides a contribution to understanding and improving spatial network disintegration strategies by leveraging a comprehensive, multi-criteria approach.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 1","pages":"Article 103955"},"PeriodicalIF":7.4,"publicationDate":"2024-11-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657716","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
Embracing the power of ensemble forecasting: A novel hybrid approach for advanced predictive modeling 利用集合预测的力量:先进预测模型的新型混合方法
IF 7.4 1区 管理学
Information Processing & Management Pub Date : 2024-11-07 DOI: 10.1016/j.ipm.2024.103954
Isha Malhotra, Nidhi Goel
{"title":"Embracing the power of ensemble forecasting: A novel hybrid approach for advanced predictive modeling","authors":"Isha Malhotra,&nbsp;Nidhi Goel","doi":"10.1016/j.ipm.2024.103954","DOIUrl":"10.1016/j.ipm.2024.103954","url":null,"abstract":"<div><div>Amidst the persistent threat of epidemics, effectively managing their complexities requires accurate forecasting to anticipate their trajectory, thus enabling the preparation and implementation of effective mitigation strategies. With a special emphasis on COVID-19, the present work focuses on the Omicron variant, recognizing its significance in the global context of infectious diseases. The proposed research evaluates the effectiveness of both univariate and multivariate frameworks utilizing statistical and deep learning approaches to forecast the spread of the epidemic. Forecasting robustness is boosted by effectively correlating linear and non-linear components with the original series. To improve the performance, correlation is facilitated using correlation-driven weights within the statistically enforced deep learning model (WD-ensemble framework). The modeling process utilizes 493 data points and multivariate time-series records, including infected cases, vaccinated cases, and stringency index. The training dataset spans from November 1, 2021, to January 17, 2023, while the testing dataset covers the period from January 18, 2023, to March 8, 2023. The proposed WD-ensemble framework, incorporating stochasticity, outperforms all other state-of-the-art models, yielding highly reliable forecasts with remarkably low RMSE of 907.54, MAPE of 0.0008, and MAE of 670.78. It demonstrates a reduction in error percentages compared to the top-performing existing model, with decreases of 30.0267% in RMSE, 20% in MAPE, and 24.9411% in MAE. A pivotal revelation in this research is the robust negative correlation (-0.86) between vaccinated and confirmed cases as compared to the stringency index, implying that widespread vaccination could warrant the relaxation of stringent measures, including business and school closures.</div></div>","PeriodicalId":50365,"journal":{"name":"Information Processing & Management","volume":"62 1","pages":"Article 103954"},"PeriodicalIF":7.4,"publicationDate":"2024-11-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142657714","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
引用次数: 0
0
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
相关产品
×
本文献相关产品
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信