Information Sciences最新文献_第10页

Enabling efficient and accurate semantic search over encrypted cloud data 在加密的云数据上实现高效和准确的语义搜索

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-06-18 DOI: 10.1016/j.ins.2025.122437

Zixin Tang , Haihui Fan , Xiaoyan Gu , Jiang Zhou , Hui Ma , Athanasios V. Vasilakos , Bo Li

{"title":"Enabling efficient and accurate semantic search over encrypted cloud data","authors":"Zixin Tang , Haihui Fan , Xiaoyan Gu , Jiang Zhou , Hui Ma , Athanasios V. Vasilakos , Bo Li","doi":"10.1016/j.ins.2025.122437","DOIUrl":"10.1016/j.ins.2025.122437","url":null,"abstract":"<div><div>The privacy and security of cloud data have drawn much attention, leading to more data owners outsourcing encrypted data. However, the common practice of encryption can reduce data searchability. Semantic searchable encryption aims to support flexible queries over encrypted data and achieve efficient search while ensuring that search results match the user's search intent. Although semantic searchable encryption schemes have made progress, they still have limitations in properly balancing accuracy, efficiency, and security. In this paper, we propose a novel <strong>C</strong>ontext-<strong>E</strong>nhanced <strong>S</strong>emantic <strong>S</strong>earchable <strong>E</strong>ncryption (<strong>CESSE</strong>) scheme to achieve accurate and highly efficient secure semantic search over encrypted cloud data. To achieve it, we first adopt a context-enhanced pre-trained model component to mine the relevance between queries and documents by contrastive learning and obtain context-enhanced vector representations to improve search accuracy. Then, to ensure privacy protection, we utilize an optimized asymmetric scalar-product-preserving encryption (optimized ASPE) algorithm to encrypt vectors before outsourcing to the cloud. Additionally, we construct the approximate nearest neighbor (ANN) index to accelerate vector searching. At last, we give a formal definition of security and theoretically prove the safety of our scheme under a more practical threat model. Extensive experiments demonstrate that the CESSE outperforms state-of-the-art baselines with better accuracy and efficiency.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122437"},"PeriodicalIF":8.1,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144364906","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Neural network-based collision-free optimal formation control for unmanned surface vehicles with the gain iterative disturbance observer 基于增益迭代扰动观测器的无人水面车辆无碰撞最优编队控制

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-06-18 DOI: 10.1016/j.ins.2025.122438

Gengqi Li , Liang Cao , Wei Wang , Xiaomeng Li , Weiwei Bai

{"title":"Neural network-based collision-free optimal formation control for unmanned surface vehicles with the gain iterative disturbance observer","authors":"Gengqi Li , Liang Cao , Wei Wang , Xiaomeng Li , Weiwei Bai","doi":"10.1016/j.ins.2025.122438","DOIUrl":"10.1016/j.ins.2025.122438","url":null,"abstract":"<div><div>Current maritime operations require the application of unmanned surface vehicles (USVs), which have more reliable path tracking capabilities and can extend the mission duration. To address the practical needs of USV formation control, this paper proposes an intelligent collision-free optimal formation control scheme for USV systems with external disturbances. Firstly, an artificial potential field (APF) function with continuous partial derivatives is developed to avoid collisions between USVs and potential obstacles which include other vehicles and environmental obstacles. When the obstacle exits the detection range, the APF function with smooth and continuous partial derivatives avoids the rotation phenomenon. Secondly, a gain iterative disturbance observer (GIDO) with a gain iterative mechanism is designed under the unfavorable effects of external disturbances. Unlike conventional disturbance observers that employ fixed gain coefficients of the disturbance term, the gain of GIDO can be dynamically adjusted by an iterative mechanism to accurately estimate the disturbance and thus improve the robustness of the USV system. Moreover, an actor-critic reinforcement learning algorithm is employed to balance the control performance and costs, thereby to optimize the energy consumption during USV formation. Finally, the optimized backstepping control strategy is proposed to ensure that USVs move to the specified location without any collision. The feasibility and effectiveness of the proposed control approach are well illustrated by simulation results.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122438"},"PeriodicalIF":8.1,"publicationDate":"2025-06-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322747","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Efficient and secure image compression and encryption based on compressive sensing and four-dimensional hyperchaotic system 基于压缩感知和四维超混沌系统的高效安全图像压缩与加密

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-06-17 DOI: 10.1016/j.ins.2025.122430

Ming Yao , Hongwei Deng , Zhong Chen , Pan Zhang

{"title":"Efficient and secure image compression and encryption based on compressive sensing and four-dimensional hyperchaotic system","authors":"Ming Yao , Hongwei Deng , Zhong Chen , Pan Zhang","doi":"10.1016/j.ins.2025.122430","DOIUrl":"10.1016/j.ins.2025.122430","url":null,"abstract":"<div><div>With the growing awareness of privacy protection, the security of image data during network transmission has become a focal point of concern. Reducing computational complexity and improving transmission efficiency while meeting high-security requirements has become a primary focus of current research. To address this, we propose a novel image privacy protection scheme that combines compressive sensing with chaotic encryption, aiming to ensure image privacy and security while enhancing transmission and storage efficiency. We employ compressive sensing technology to achieve efficient compression of image data. Unlike traditional compression and encryption schemes, the proposed method does not require explicit sparsification preprocessing, thereby avoiding the complex operations introduced by signal transformations and simplifying the signal recovery process. To enhance encryption security, a four-dimensional hyperchaotic system with stronger chaotic properties is designed to generate highly random and unpredictable key streams, ensuring the security of the encrypted data. Furthermore, this paper combines disjoint Latin squares with fractal generation strategies to design a new fractal index matrix, based on which a novel image permutation scheme is proposed. This scheme effectively eliminates the linear relationships and correlations between adjacent pixels, achieving global pixel permutation. Coupled with the proposed dual-channel bidirectional diffusion structure, the algorithm effectively diffuses pixel information across the entire image, increasing the complexity and unpredictability of the image encryption process. Experimental results indicate that the proposed algorithm exhibits excellent performance in terms of compression efficiency, encryption effectiveness, and resistance to attacks, providing a highly efficient and reliable solution in the field of image compression and encryption.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122430"},"PeriodicalIF":8.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144322751","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Fine-grained entity typing based on hyperbolic representation and label-context interaction 基于双曲表示和标签-上下文交互的细粒度实体类型

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-06-17 DOI: 10.1016/j.ins.2025.122434

Mingying Xu , Wenxuan Zhang , Jie Liu , Weiping Ding , Lei Shi , Kaiyang Zhong

{"title":"Fine-grained entity typing based on hyperbolic representation and label-context interaction","authors":"Mingying Xu , Wenxuan Zhang , Jie Liu , Weiping Ding , Lei Shi , Kaiyang Zhong","doi":"10.1016/j.ins.2025.122434","DOIUrl":"10.1016/j.ins.2025.122434","url":null,"abstract":"<div><div>Fine-grained entity typing (FET) is a crucial task in natural language processing (NLP), which aims to assign detailed type labels to entities based on context. Accurate entity typing is essential for many downstream applications, such as knowledge graph construction, information retrieval, and question answering. However, existing FET methods face significant challenges in capturing the hierarchical structure of entity types and effectively leveraging contextual information. Many prior approaches either rely on label co-occurrence statistics, which may introduce noise, or utilize hyperbolic space, which performs well for ultra-fine entities but struggles with coarse-grained entity types. Furthermore, the lack of effective label-context interaction limits the model's ability to filter out irrelevant type labels, leading to suboptimal entity typing performance. To address these issues, we propose a novel FET framework that integrates hyperbolic representation and label-context interaction. First, we map the hierarchical structure of entity labels into hyperbolic space, allowing for a more effective representation of type relationships. A graph convolutional network (GCN) is then employed to model label dependencies while filtering out noisy co-occurrence information. Additionally, we introduce a label-context interaction module using attention mechanism to refine type selection by modeling semantic correlations between context and labels. This mechanism dynamically enhances the relevance of selected type labels while mitigating noise. Experiments on multiple public datasets demonstrate the effectiveness of combining hyperbolic representation with label-context interaction for FET.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122434"},"PeriodicalIF":8.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144364909","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

CNLA: Collaborative noisy label adaptive learning for facial expression recognition CNLA：面部表情识别的协同噪声标签自适应学习

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-06-17 DOI: 10.1016/j.ins.2025.122436

Jihua Ye , Dong Liu , Chao Wang , Huiyuan Huang , Liang Ying , Lei Zhang , Aiwen Jiang

{"title":"CNLA: Collaborative noisy label adaptive learning for facial expression recognition","authors":"Jihua Ye , Dong Liu , Chao Wang , Huiyuan Huang , Liang Ying , Lei Zhang , Aiwen Jiang","doi":"10.1016/j.ins.2025.122436","DOIUrl":"10.1016/j.ins.2025.122436","url":null,"abstract":"<div><div>Existing in-the-wild facial expression recognition (FER) methods rely heavily on predefined labels to achieve high performance. However, in-the-wild FER datasets contain numerous noisy labels, as the uncertainty of facial expressions arises from ambiguous annotations or inter-similarity. Noisy labels provide misleading supervision for learning, leading to decreased generalization. We propose a Collaborative Noisy Label Adaptive Learning (CNLA) method for FER from a new perspective of sample selection to mitigate label inconsistency. CNLA generates perturbed and mixed samples, using Mixed Samples Correction Loss to capture more precise information from various perturbed samples while learning rich representations. Additional information from the perturbed samples is then used for collaborative training, categorizing samples into learnable and relabeled ones. Finally, CNLA constrains the semantic consistency of facial expressions, allowing the model to focus on expression-related regions. Extensive experiments on synthetic noise and original datasets validate the effectiveness of CNLA, demonstrating performance that surpasses state-of-the-art methods.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122436"},"PeriodicalIF":8.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313040","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

SecMeanshift: FSS-based privacy-preserving mean-shift clustering SecMeanshift：基于fss的隐私保护mean-shift聚类

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-06-17 DOI: 10.1016/j.ins.2025.122435

Min Ma , Yu Fu , Fei Zheng , Zhihong Zhang , Taotao Liu , Kai Huang

{"title":"SecMeanshift: FSS-based privacy-preserving mean-shift clustering","authors":"Min Ma , Yu Fu , Fei Zheng , Zhihong Zhang , Taotao Liu , Kai Huang","doi":"10.1016/j.ins.2025.122435","DOIUrl":"10.1016/j.ins.2025.122435","url":null,"abstract":"<div><div>Clustering is an unsupervised learning method that groups data based on similar characteristics. They have broad applications in various fields, such as image processing, text clustering, and recommendation systems. However, in practical scenarios, clustering often involves sensitive data from multiple data owners, which raises significant privacy concerns. Therefore, addressing the challenge of performing efficient clustering while preserving data privacy is critical. Existing privacy-preserving clustering methods often encounter challenges such as high computational overhead or reliance on auxiliary information. Consequently, we propose SecMeanshift, a privacy-preserving mean-shift framework based on function secret sharing. SecMeanshift leverages an offline–online paradigm to enhance efficiency by offloading some operations to the offline phase. We design basic protocols, including secure negative exponential, secure select, and secure sampling for the proposed framework, and design private protocols for each phase of the mean-shift. Theoretical analysis confirms the security and correctness of the proposed protocols. Furthermore, extensive experiments on diverse datasets demonstrate that SecMeanshift achieves significantly higher efficiency than HE-Meanshift, making it a promising solution for privacy-preserving clustering.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122435"},"PeriodicalIF":8.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313042","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Chaos-based broadcast encryption with authenticated secure message transmission scheme 基于混沌的广播加密认证安全消息传输方案

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-06-17 DOI: 10.1016/j.ins.2025.122433

Zhongwang Fu , Yunqi Liu , Xiaohui Cui

{"title":"Chaos-based broadcast encryption with authenticated secure message transmission scheme","authors":"Zhongwang Fu , Yunqi Liu , Xiaohui Cui","doi":"10.1016/j.ins.2025.122433","DOIUrl":"10.1016/j.ins.2025.122433","url":null,"abstract":"<div><div>In scenarios requiring high security and frequent data exchange, such as multi-agent intelligence gathering, researchers are primarily concerned with ensuring robust security measures. While encryption methods are currently employed for data protection, there is a notable lack of research focusing on secure data transmission. Consequently, there is an immediate necessity for an information transmission architecture that is anonymous, tamper-proof, and untraceable, in order to bolster the security of data itself and data exchange. To address this need, this paper proposes Chaos-based Broadcast Encryption with Authenticated Secure Message Transmission scheme (CBENAU). The proposed method devises a secure broadcast encryption algorithm founded on chaos theory, which effectively encrypts messages and dispatches them to multiple authorized recipients. This approach ensures both data protection and a reduction in communication overhead associated with message transmission. Furthermore, the inclusion of content publisher authentication serves as a deterrent against spam dissemination in broadcast encryption systems. A relay transmission network is constructed for message transmission to ensure the untraceability of senders and recipients. Through rigorous security analysis, the proposed CBENAU scheme demonstrates its resilience against ciphertext attacks, surpassing the security levels provided by traditional RSA and ElGamal. Moreover, the scheme is anonymity, public verifiability, confidentiality, and non-repudiation.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122433"},"PeriodicalIF":8.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144489993","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Identification of switched Boolean networks 交换布尔网络的识别

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-06-17 DOI: 10.1016/j.ins.2025.122431

Chunfeng Jiang , Biao Wang , Carmen Del Vecchio , Jun-e Feng

{"title":"Identification of switched Boolean networks","authors":"Chunfeng Jiang , Biao Wang , Carmen Del Vecchio , Jun-e Feng","doi":"10.1016/j.ins.2025.122431","DOIUrl":"10.1016/j.ins.2025.122431","url":null,"abstract":"<div><div>This paper addresses the identification problem of switched Boolean networks (SBNs). The model considered here is more general than conventional SBNs, which allows each subnetwork to exhibit distinct state and output dynamics, simultaneously governed by switching signals. The switching mechanism influences not only the evolution of system states but also the associated output behaviors, rendering existing identification techniques for traditional Boolean (control) networks inapplicable. In this paper, the reachability and observability properties of SBNs are first analyzed, and corresponding detection conditions are proposed. Building on these properties, criteria for identifying SBNs in both single-sample and multiple-sample scenarios are derived. The exact correspondence between states and outputs is found by incorporating temporal information and then valid algorithms are developed to facilitate this identification process. A new finding is that even if some subnetworks in an SBN are unidentifiable, the entire SBN may still be identifiable. Finally, several examples are provided to demonstrate the effectiveness of the proposed methods.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122431"},"PeriodicalIF":8.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144313043","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Extended mean field game theoretical optimal distributed control for large scale multi-agent systems: An efficiency-complexity tradeoff 大规模多智能体系统的扩展平均场博弈理论最优分布式控制：效率-复杂性权衡

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-06-17 DOI: 10.1016/j.ins.2025.122432

Shawon Dey, Hao Xu

{"title":"Extended mean field game theoretical optimal distributed control for large scale multi-agent systems: An efficiency-complexity tradeoff","authors":"Shawon Dey, Hao Xu","doi":"10.1016/j.ins.2025.122432","DOIUrl":"10.1016/j.ins.2025.122432","url":null,"abstract":"<div><div>This paper investigates the tradeoff between optimal efficiency and computational complexity in the emerging mean-field game (MFG) theory and further develops a novel reconfigurable decomposition approach that can balance the efficiency-complexity of MFG theoretical optimal distributed control for large-scale multi-agent systems (LS-MAS). Generally, the MFG has the potential to overcome the “Curse of Dimensionality” in LS-MAS control by simplifying all agents' interactions into ones between individual agents and the collective average effects captured by the group's probability density function (PDF). However, the social cost associated with MFG Nash equilibria is generally inefficient compared to the centralized optimal cost associated with the McKean-Vlasov control problem. To enhance the efficiency of MFG theoretical control without significantly increasing complexity, a novel extended MFG (EMFG) is developed to efficiently balance the MFG efficiency and computational complexity through a decomposed mean field PDF term. Specifically, LS-MAS is divided into multiple groups based on desired terminal PDF constraints. Then, an actor-critic-decomposed mass (ACDM) algorithm is developed to attain the optimal control for LS-MAS by solving the coupled MFG forward-backward partial differential equation (PDE) system. While the PDF decomposition expands the neural network structure, it escalates computational complexity. However, the developed algorithm evaluates and balances LS-MAS optimal control efficiency and complexity. In addition, an induction-based proof is provided to demonstrate the reduction of the inefficiency bound between the optimal cost associated with McKean-Vlasov control and the social cost associated with the extended MFG equilibrium. After that, the Lyapunov stability analysis is presented to illustrate the convergence of the ACDM algorithm. Eventually, numerical simulations are provided to validate the proposed approach.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122432"},"PeriodicalIF":8.1,"publicationDate":"2025-06-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144364907","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Utilizing Universal Information Extraction based on Generative Large Language Model to mine online reviews for navigating online health consultation 基于生成式大语言模型的通用信息提取挖掘在线评论，为在线健康咨询导航

IF 8.1 1区计算机科学

Information Sciences Pub Date : 2025-06-16 DOI: 10.1016/j.ins.2025.122428

Yanfang Ma , Lina Liu , Yu Gong , Yan Tu , Zibiao Li

{"title":"Utilizing Universal Information Extraction based on Generative Large Language Model to mine online reviews for navigating online health consultation","authors":"Yanfang Ma , Lina Liu , Yu Gong , Yan Tu , Zibiao Li","doi":"10.1016/j.ins.2025.122428","DOIUrl":"10.1016/j.ins.2025.122428","url":null,"abstract":"<div><div>Given the limited medical resources and the increasing healthcare demand, mobile health applications (mHealth apps) have become an important complement to enhance medical accessibility. As the number of mHealth apps is booming, it is difficult for patients to select an ideal application, particularly for the critical function, online health consultation services, which are seldom concerned. This study proposes a method to select a suitable application for online health consultation. First, we employ the Octopus crawler software to collect online reviews about online health consultation from Little Red Book and Weibo, popular content sharing platforms. Then, Universal Information Extraction based on Generative Large Language Model (UIE-GLLM) is introduced to process online reviews, which can automatically identify the evaluation attributes that patients really care about. And then, linguistic hesitant Z-number (LHZN), a preference expression method enabling decision makers to convey ambiguity in evaluation information, is introduced to express the applications based on the attributes learned by UIE-GLIM. Finally, an optimal application is obtained using large-scale group decision-making method. Comparative analysis indicates that LHZN significantly improve consensus degree. Compared with LDA and TF-IDF, UIE-GLLM can extract more comprehensive attributes from reviews without complex preprocessing.</div></div>","PeriodicalId":51063,"journal":{"name":"Information Sciences","volume":"719 ","pages":"Article 122428"},"PeriodicalIF":8.1,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"144307243","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0