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58th Annual Meeting of the Association for Computational Linguistics, ACL 2020

作者： Guan, Saiping Jin, Xiaolong Guo, Jiafeng Wang, Yuanzhuo Cheng, Xueqi School of Computer Science and Technology University of Chinese Academy of Sciences CAS Key Laboratory of Network Data Science and Technology Institute of Computing Technology Chinese Academy of Sciences

ISBN: (纸本)9781952148255

Knowledge inference on knowledge graph has attracted extensive attention, which aims to find out connotative valid facts in knowledge graph and is very helpful for improving the performance of many downstream applications. However, researchers have mainly poured attention to knowledge inference on binary facts. The studies on n-ary facts are relatively scarcer, although they are also ubiquitous in the real world. Therefore, this paper addresses knowledge inference on n-ary facts. We represent each n-ary fact as a primary triple coupled with a set of its auxiliary descriptive attribute-value pair(s). We further propose a neural network model, NeuInfer, for knowledge inference on n-ary facts. Besides handling the common task to infer an unknown element in a whole fact, NeuInfer can cope with a new type of task, flexible knowledge inference. It aims to infer an unknown element in a partial fact consisting of the primary triple coupled with any number of its auxiliary description(s). Experimental results demonstrate the remarkable superiority of NeuInfer. © 2020 Association for Computational Linguistics

关键词： Knowledge graph

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On the Security of Smart Home Systems:A Survey

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Journal of Computer science & technology 2023年第2期38卷 228-247页

作者：袁斌万俊吴宇晗邹德清金海 School of Cyber Science and Engineering Huazhong University of Science and TechnologyWuhan 430074China Hubei Key Laboratory of Distributed System Security Huazhong University of Science and Technology Wuhan 430074China Hubei Engineering Research Center on Big Data Security Huazhong University of Science and Technology Wuhan 430074China National Engineering Research Center for Big Data Technology and System Huazhong University of Science and TechnologyWuhan 430074China Services Computing Technology and System Lab Huazhong University of Science and TechnologyWuhan 430074China Shenzhen Huazhong University of Science and Technology Research Institute Shenzhen 518057China School of Computer Science and Technology Huazhong University of Science and TechnologyWuhan 430074China Cluster and Grid Computing Lab Huazhong University of Science and TechnologyWuhan 430074China

Among the plethora of IoT(Internet of Things)applications,the smart home is one of the ***,the rapid development of the smart home has also made smart home systems a target for ***,researchers have made many efforts to investigate and enhance the security of smart home *** a more secure smart home ecosystem,we present a detailed literature review on the security of smart home ***,we categorize smart home systems’security issues into the platform,device,and communication *** exploring the research and specific issues in each of these security areas,we summarize the root causes of the security flaws in today's smart home systems,which include the heterogeneity of internal components of the systems,vendors'customization,the lack of clear responsibility boundaries and the absence of standard security ***,to better understand the security of smart home systems and potentially provide better protection for smart home systems,we propose research directions,including automated vulnerability mining,vigorous security checking,and data-driven security analysis.

关键词： IoT(Internet of Things) smart home IoT security smart home security

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UNDERSTANDING ONLINE SHOPPING AND OFFLINE MOBILITY BEHAVIOR IN URBAN AREA FROM THE VIEW OF MULTILAYER networkS 5

UNDERSTANDING ONLINE SHOPPING AND OFFLINE MOBILITY BEHAVIOR ...

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2016 5th IEEE International Conference on network Infrastructure and Digital Content(IC-NIDC 2016)

作者： Yuanyuan Qiao Yanting Zhang Anders Lindgren Jie Yang Beijing Key Laboratory of Network System Architecture and Convergence BUPT Center for Data Science BUPT SICS Swedish ICT Lulea University of Technology

ISBN: (纸本)9781509012473

The interactive nature of the Internet offers many opportunities to increase the efficiency of online shopping by improving availability of product information,enabling direct multi-attribute comparisons,and reducing buyer search costs.A great body of research focuses on how consumers shop online or why and how online shopping impacts urban development,but the understanding of mutual influence between online and offline behavior of consumers remains somewhat *** paper bridges that gap by quantifying the relationship between consumers' online shopping and offline mobility *** results of the study give insights to further understand human behavior from both a cyber and real world point of view,which may help to place location based targeted advertisements,and plan commercial & retail centers in urban areas.

关键词： Online shopping behavior Mobility behavior Multilayer networks Mobile traffic

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A Performance Comparison Study of Parallel Clustering Algorithms in Cluster Environments 2

A Performance Comparison Study of Parallel Clustering Algori...

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2017 IEEE 2nd International Conference on Big data Analysis（ICBDA 2017）

作者： Mo Hai School of Information Central University of Finance and Economics Network and Data Security Key Laboratory of Sichuan Province University of Electronic Science and Technology of China

ISBN: (纸本)9781509036202

We compare the performance of three parallel clustering algorithms:Canopy,K-means and fuzzy K-means in real cluster *** constructing cluster platform of different scale,we compare these algorithms from three metrics:run time,speedup and *** results show that:(1) if both the data set and the number of nodes in the cluster are the same,both the runtime and the sizeup of Canopy is the smallest,and the speedup of Canopy is the largest among these three algorithms;(2) when the number of nodes is larger than 2,for each algorithm,the difference between the sizeup on different data set becomes more and more smaller as the number of nodes increases;at the same time,when the number of nodes is larger than 2 and the data set is the same,the sizeup of Canopy has the maximum decrease with the increase of the number of nodes;(3) when the number of nodes keeps the same,the difference between the sizeup of these three algorithms becomes more and more apparent as the size of the data set increases.

关键词： Canopy K-means Fuzzy K-means Cluster platform Run time Speedup Sizeup

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A cross-lingual joint aspect/sentiment model for sentiment analysis 14

A cross-lingual joint aspect/sentiment model for sentiment a...

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23rd ACM International Conference on Information and Knowledge Management, CIKM 2014

作者： Lin, Zheng Jin, Xiaolong Xu, Xueke Wang, Yuanzhuo Wang, Weiping Cheng, Xueqi Minzhuang Road Beijing China Key Lab. of Network Data Science and Technology ICT CAS No. 6 Kexueyuan South Road Beijing China

ISBN: (纸本)9781450325981

Sentiment analysis in various languages has been a research hotspot with many applications. However, sentiment resources (e.g., labeled corpora, sentiment lexicons) of different languages are unbalanced in terms of quality and quantity, which arouses interests in cross-lingual sentiment analysis aiming at using the resources in a source language to improve sentiment analysis in a target language. Nevertheless, many existing cross-lingual related works rely on a certain machine translation system to directly adapt the labeled data from the source language to the target language, which usually suffers from inaccurate results generated by the machine translation system. On the other hand, most sentiment analysis studies focus on document-level sentiment classification that cannot solve the aspect dependency problem of sentiment words. For instance, in the reviews on a cell phone, long is positive for the lifespan of its battery, but negative for the response time of its operating system. To solve these problems, this paper develops a novel Cross-Lingual Joint Aspect/Sentiment (CLJAS) model to carry out aspect-specific sentiment analysis in a target language using the knowledge learned from a source language. Specifically, the CLJAS model jointly detects aspects and sentiments of two languages simultaneously by incorporating sentiments into a cross-lingual topic model framework. Extensive experiments on different domains and different languages demonstrate that the proposed model can significantly improve the accuracy of sentiment classification in the target language. Copyright 2014 ACM.

关键词： Sentiment analysis

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Conditional Generative Modeling for Amorphous Multi-Element Materials

arXiv

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arXiv 2025年

作者： Li, Honglin Liu, Chuhao Guo, Yongfeng Luo, Xiaoshan Chen, Yijie Liu, Guangsheng Li, Yu Wang, Ruoyu Wang, Zhenyu Wu, Jianzhuo Ma, Cheng Xie, Zhuohang Lv, Jian Ding, Yufei Zhang, Huabin Luo, Jian Zhong, Zhicheng Li, Mufan Wang, Yanchao Li, Wan-Lu Key Laboratory of Material Simulation Methods and Software Ministry of Education College of Physics Jilin University Changchun China Aiiso Yufeng Li Family Department of Chemical and Nano Engineering University of California La Jolla San DiegoCA United States Institute of Molecular Engineering Plus College of Chemistry Fuzhou University Fuzhou China College of Chemistry and Molecular Engineering Peking University Beijing China School of Physics Nankai University Tianjin China Institute of Modern Physics Fudan University Shanghai China Program in Materials Science and Engineering University of California La Jolla San DiegoCA United States School of Artificial Intelligence and Data Science University of Science and Technology of China Hefei230026 China Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China International Center of Future Science Jilin University Changchun China Department of Computer Science and Engineering University of California La Jolla San DiegoCA United States Center for Renewable Energy and Storage Technologies Physical Science and Engineering Division King Abdullah University of Science and Technology Thuwal Saudi Arabia Suzhou Lab Suzhou215123 China

Amorphous multi-element materials offer unprecedented tunability in composition and properties, yet their rational design remains challenging due to the lack of predictive structure-property relationships and the vast configurational space. Traditional modeling struggles to capture the intricate short-range order that dictates their stability and functionality. We here introduce ApolloX, a pioneering predictive framework for amorphous multi-element materials, establishing a new paradigm by integrating physics-informed generative modeling with particle swarm optimization, using chemical short-range order as an explicit constraint. By systematically navigating the disordered energy landscape, ApolloX enables the targeted design of thermodynamically stable amorphous configurations. It accurately predicts atomic-scale arrangements, including composition-driven metal clustering and amorphization trends, which are well-validated by experiments, while also guiding synthesis by leveraging sluggish diffusion to control elemental distribution and disorder. The resulting structural evolution, governed by composition, directly impacts catalytic performance, leading to improved activity and stability with increasing amorphization. This predictive-experimental synergy transforms the discovery of amorphous materials, unlocking new frontiers in catalysis, energy storage, and functional disordered systems. Copyright © 2025, The Authors. All rights reserved.

关键词： Amorphization

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DBKEM-AACS: a distributed key escrow model in blockchain with anonymous authentication and committee selection

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science China(Information sciences) 2023年第3期66卷 289-290页

作者： Axin XIANG Hongfeng GAO Youliang TIAN Liang WAN College of Computer Science and Technology Guizhou University Institute of Cryptography and Data Security Guizhou University Network and Information Management Center Guizhou University State Key Laboratory of Public Big Data Guizhou University Institute of Computer Software and Theory Guizhou University

Dear editor, key security is of great practical significance and demand to guarantee the security of digital assets in the blockchain system. At present, users prefer to escrow their assets on centralized institutions, but this phenomenon has gone against the unique characteristics of decentralization and anonymity in the blockchain. Among them, the suspense incidents of assets lock or lost are enough to prove that the security of escrowed keys on the exchanges is questionable.

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An enhanced genetic algorithm for computation task offloading in MEC scenario

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International Journal of Wireless and Mobile Computing 2023年第2期25卷 118-127页

作者： Zhao, Jiacheng Li, Wenzao Liu, Hantao Yu, Peizhen Li, Hanyun Wen, Zhan School of Communication Engineering Chengdu University of Information Technology Sichuan Chengdu China Chengdu University of Information Technology Sichuan Chengdu China Network and Data Security Key Lab of Sichuan Pro. University of Electronic Science and Technology of China Sichuan Chengdu China Educational Informationisation and Big Data Centre Education Department of Sichuan Province Sichuan Chengdu China

The explosive growth of Internet of Things (IoT) and 5G communication technologies has driven the increasing computing demands for wireless devices. Mobile edge computing in the 5G scenario is a promising solution for energy-efficient and low latency applications. However, due to limited bandwidth, the selection of appropriate computing tasks greatly affects the user experience and system performance. Under the wireless bandwidth constraint, the reasonable choice of offloading objects is an NP-hard problem. The genetic algorithm has a great ability to solve this problem, but the performance of the algorithm varies with different scenarios. This paper proposes a task offloading strategy based on an enhanced genetic algorithm for small-scale computing tasks with an ultra-dense terminal distribution. Numerical experiments show that the convergence speed and optimisation effect of the enhanced genetic algorithm are significantly improved compared to the conventional genetic algorithm. © 2023 Inderscience Enterprises Ltd.

关键词： Genetic algorithms

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Navigation Route Based Stable Clustering for Vehicular Ad Hoc networks

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China Communications 2018年第3期15卷 42-56页

作者： Zhiwei Yang Weigang Wu Yishun Chen Xiaola Lin Xiang Chen School of Data and Computer Science and School of Electronics and Information TechnologySun Yat-sen Univ. Key Lab of EDA Research Institute of Tsinghua University in Shenzhen(RITS)

Due to high node mobility, stability has been always one of the major concerns of vehicle clustering algorithms in vehicular ad hoc networks. In this paper, we propose a novel clustering algorithm based on the information of routes planned by vehicular navigation systems. In the clustering algorithm, we design a residual route time function to quantitatively calculate the overlapping time among vehicles based on route information, with which a novel clusterhead selection metric is presented. We further design a mechanism of future-clusterhead, which can help avoid message exchanges at intersections and reduce the overhead of cluster maintenance. The simulation results show that, compared with previous works, our clustering algorithm can achieve higher stability and at the same time lower communication cost.

关键词： VANET clustering mobile com-puting navigation route ad hoc networks

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Trajectory Tracking of Mobile Robots Based on Model Predictive Control Using Primal Dual Neural network 33

Trajectory Tracking of Mobile Robots Based on Model Predicti...

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第三十三届中国控制会议

作者： DENG Jun LI Zhijun SU Chun-Yi The Key Lab of Autonomous System and Network Control College of Automation Science and Engineering South China University of Technology

ISBN: (纸本)9781479947249

Mobile robots' motion is constrained by the maximum velocity its actuators can provide,when it tracks a reference trajectory which imposes demanding requirements on the robot's driving *** this paper,a model predictive control(MPC) scheme is proposed for trajectory tracking control of two-wheel mobile *** on the derived tracking-error kinematics of the robot,the proposed MPC approach can be iteratively formulated as a quadratic programming(QP) problem,which can be solved using a linear variable inequality based primal-dual neural network(LVI-PDNN) over a finite receding *** applied neural networks are both stable in the sense of Lyapunov and globally convergent to the exact optimal solutions of reformulated convex programming *** smoothness of the robot motion is improved,a reasonable magnitudes of the robot velocities and a better tracking performance are *** and experimental results are provided to demonstrate the effectiveness and characteristics of the proposed LVI-PDNN based MPC approaches to trajectory tracking control.

关键词： Model Predictive Control(MPC),Quadratic Programming(QP) Problem,LVI-based Primal-dual Neural network(LVI-PDNN),Trajectory Tracking

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