信息科学将发表原创、创新和创造性的研究成果。将不时出版少量及时的教程和调查贡献。该杂志旨在为研究人员、开发人员、管理人员、战略规划人员、研究生和其他对信息、知识方面的最新研究活动感兴趣的人提供服务工程和智能系统。假定读者对信息科学有共同的兴趣，但在工程、数学、统计学、物理学、计算机科学、细胞生物学、分子生物学、管理科学、认知科学、神经生物学、行为科学和生物化学等领域具有不同的背景。

The journal "Information Sciences" is dedicated to publishing original, innovative, and creative research findings. We occasionally publish timely tutorials and survey contributions. This journal aims to serve researchers, developers, managers, strategic planners, graduate students, and others interested in the latest research activities in the fields of information and knowledge, particularly in service engineering and intelligent systems. We assume that readers share a common interest in information science, but come from diverse backgrounds in engineering, mathematics, statistics, physics, computer science, cell biology, molecular biology, management science, cognitive science, neurobiology, behavioral science, and biochemistry.

《Information Sciences》期刊致力于发表原创、创新和创造性的研究成果。我们不定期出版一些及时的教程和调查贡献。该期刊旨在为研究人员、开发人员、管理人员、战略规划人员、研究生及其他对信息和知识领域最新研究活动感兴趣的人士提供服务，尤其是工程和智能系统方面的研究。我们假定读者对信息科学有共同的兴趣，但在工程、数学、统计学、物理学、计算机科学、细胞生物学、分子生物学、管理科学、认知科学、神经生物学、行为科学和生物化学等领域具有不同的背景。

Information Sciences

Yang Zhang

Jiarui Chen

Zhe Cheng

Xiong Shen

Jiancheng Qin

Yingzheng Han

Yiqin Lu

Edge propagation for link prediction in requirement-cyber threat intelligence knowledge graph

Jie Xiong

Li Yu

Xi Niu

Youfang Leng

XRR: Extreme multi-label text classification with candidate retrieving and deep ranking

Lingli Li

Ao Han

Xiaotong Cui

Baohua Wu

FLEX: A fast and light-weight learned index for kNN search in high-dimensional space

Bo Zhao

Derong Liu

Yuanchun Li

Observer based adaptive dynamic programming for fault tolerant control of a class of nonlinear systems

基于观测器的自适应动态规划在非线性系统容错控制中的应用

Joseph Anderson

Lang Hong

Sensor Resource Management driven by threat projection and priorities

In social trust network group decision-making, experts typically show limited tolerance and compromise behaviors when modifying their opinions to reach consensus. The first behavior implies that an expert will change their opinion without cost if the suggested opinion closely aligns with that of trusted experts. The second behavior implies that an expert will accept the suggested opinion only if it falls within a predefined compromise boundary relative to trusted experts' opinions. However, existing maximum expert consensus models (MECMs) do not adequately consider these behaviors, limiting their practical applicability. To address this gap, this study proposes a social trust MECM with budget constraints. Budget constraints can lead to an insufficient number of experts within the consensus, underscoring the need for higher budget allocation to achieve consensus. To address this issue, a minimum cost consensus model (MCCM) considering network-dependent limited tolerance and compromise behaviors (NDLTCBs) was developed to provide a budget increment reference. Notably, network-dependent limited compromise behavior is crucial in the MCCM, especially when compromise values are small, as it may prevent feasible solutions. In such cases, a minimum compromise increment consensus model is created to determine the necessary increase in compromise values for a feasible MCCM solution. Subsequently, an interactive maximum expert consensus-reaching process is introduced. Simulation experiments demonstrate that consensus efficiency, in terms of the number of experts within the consensus, can be enhanced by considering NDLTCBs.

Hengjie Zhang

Shenghua Liu

Cong-Cong Li

Yucheng Dong

Francisco Chiclana

Enrique Herrera-Viedma

Addressing the influence of limited tolerance and compromise behaviors on the social trust network consensus-reaching process

解决有限容忍和妥协行为对社会信任网络共识达成过程的影响

Mengjie Li

Shaobao Li

Xiaoyuan Luo

Jianmei Wang

Xinping Guan

Adaptive event-triggered sliding mode control for platooning of heterogeneous vehicular systems and its <mml:math xmlns:mml="http://www.w3.org/1998/Math/MathML" altimg="si1.svg"><mml:msub><mml:mrow><mml:mi mathvariant="script">L</mml:mi></mml:mrow><mml:mrow><mml:mn>2</mml:mn></mml:mrow></mml:msub></mml:math> input-to-output string stability

异构车辆系统编队的自适应事件触发滑模控制及其L2输入-输出串稳定性

Yuehang Si

Xingchen Hu

Qing Cheng

Xinwang Liu

Shixuan Liu

Jincai Huang

Coherence mode: Characterizing local graph structural information for temporal knowledge graph

连贯模式：表征时序知识图谱的局部图结构信息

Bo-Wei Zhao

Xiao-Rui Su

Yue Yang

Dong-Xu Li

Guo-Dong Li

Peng-Wei Hu

Zhu-Hong You

Xin Luo

Lun Hu

Regulation-aware graph learning for drug repositioning over heterogeneous biological network

基于异构生物网络的药物重定位的监管感知图学习

Xuepeng Ren

Maocai Wang

Guangming Dai

Lei Peng

Xiaoyu Chen

Zhiming Song

Multi-objective evolutionary algorithm based on transfer learning and neural networks: Dual operator feature fusion and weight vector adaptation

基于迁移学习和神经网络的多目标进化算法：双操作符特征融合与权重向量自适应

Abbreviation	Inf. Sci.
Quartiles(Global)	COMPUTER SCIENCE, INFORMATION SYSTEMS(Q1)

ISSN	0020-0255, 1872-6291
h-index	227
Top Journals	Yes

Publication Information	Publisher: Elsevier Inc.，Publishing cycle: Semimonthly，Journal Type: journal，Open Access Journals: No
Basic data	Year of publication: 1968，Proportion of original research papers: 99.71%，Self Citation Rate:N.A.， Gold OA Rate: 6.63%
Average review cycle	网友分享经验：平均10.8个月来源Elsevier官网：平均16.8周
Average recruitment ratio	网友分享经验：约22.5%

Information Sciences

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