检索结果-内蒙古大学图书馆

A numerical magnitude aware multi-channel hierarchical encoding network for math word problem solving

Neural Computing and Applications 2025年第3期37卷 1651-1672页

作者： Xu, Junjie Chen, Yuzhong Xiao, Lingsheng Liao, Hongmiao Zhong, Jiayuan Dong, Chen College of Computer and Data Science Fuzhou University Fujian Province Fuzhou350108 China Engineering Research Center of Big Data Intelligence Ministry of Education Fuzhou China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fujian Province Fuzhou350108 China

Math word problem (MWP) represents a critical research area within reading comprehension, where accurate comprehension of math problem text is crucial for generating math expressions. However, current approaches still grapple with unresolved challenges in grasping the sensitivity of math problem text and delineating distinct roles across various clause types, and enhancing numerical representation. To address these challenges, this paper proposes a Numerical Magnitude Aware Multi-Channel Hierarchical Encoding Network (NMA-MHEA) for math expression generation. Firstly, NMA-MHEA implements a multi-channel hierarchical context encoding module to learn context representations at three different channels: intra-clause channel, inter-clause channel, and context-question interaction channel. NMA-MHEA constructs hierarchical constituent-dependency graphs for different levels of sentences and employs a Hierarchical Graph Attention Neural Network (HGAT) to learn syntactic and semantic information within these graphs at the intra-clause and inter-clause channels. NMA-MHEA then refines context clauses using question information at the context-question interaction channel. Secondly, NMA-MHEA designs a number encoding module to enhance the relative magnitude information among numerical values and type information of numerical values. Experimental results on two public benchmark datasets demonstrate that NMA-MHEA outperforms other state-of-the-art models. © The Author(s), under exclusive licence to Springer-Verlag London Ltd., part of Springer Nature 2024.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Solving Multi-Objective Vehicle Routing Problems with Time Windows: A Decomposition-Based Multiform Optimization Approach

引用

Tsinghua Science and Technology 2024年第2期29卷 305-324页

作者： Yiqiao Cai Zifan Lin Meiqin Cheng Peizhong Liu Ying Zhou Xiamen Key Laboratory of Data Security and Blockchain Technology College of Computer Science and TechnologyHuaqiao UniversityXiamen361021China College of Engineering Huaqiao UniversityQuanzhou362000China School of Computer Sciences Shenzhen Institute of Information TechnologyShenzhen518000China

In solving multi-objective vehicle routing problems with time windows (MOVRPTW),most existing algorithms focus on the optimization of a single problem formulation. However,little effort has been devoted to exploiting valuable knowledge from the alternate formulations of MOVRPTW for better optimization performance. Aiming at this insufficiency,this study proposes a decomposition-based multi-objective multiform evolutionary algorithm (MMFEA/D),which performs the evolutionary search on multiple alternate formulations of MOVRPTW simultaneously to complement each other. In particular,the main characteristics of MMFEA/D are three folds. First,a multiform construction (MFC) strategy is adopted to construct multiple alternate formulations,each of which is formulated by grouping several adjacent subproblems based on the decomposition of MOVRPTW. Second,a transfer reproduction (TFR) mechanism is designed to generate offspring for each formulation via transferring promising solutions from other formulations,making that the useful traits captured from different formulations can be shared and leveraged to guide the evolutionary search. Third,an adaptive local search (ALS) strategy is developed to invest search effort on different alternate formulations as per their usefulness for MOVRPTW,thus facilitating the efficient allocation of computational resources. Experimental studies have demonstrated the superior performance of MMFEA/D on the classical Solomon instances and the real-world instances.

关键词： MOVRPTW multiform optimization multiform construction knowledge transfer adaptive local search

来源：评论

学校读者我要写书评

暂无评论

The Mass Assembly History for Galaxies with MaNGA

引用

Research in Astronomy and Astrophysics 2024年第3期24卷 58-69页

作者： Xue Ge Hong-Tao Wang Cheng-Long Lei Yun-Jun Guo Yi-Long Jiang Xiao-Xiao Cao School of Physics and Information Engineering Jiangsu Second Normal University Jiangsu Province Engineering Research Center of Basic Education Big Data Application Jiangsu Second Normal University Key Laboratory of Modern Astronomy and Astrophysics Nanjing UniversityMinistry of Education School of Science Langfang Normal University

How galaxies assemble masses through their own star formation or interaction with the external environment is still an important topic in the field of galaxy formation and *** use Value Added Catalogs with galaxy features that are spatially and temporally resolved from Sloan Digital Sky Survey data Release 17 to investigate the mass growth histories of early-type galaxies(ETGs)and late-type galaxies(LTGs).We find that the mass growth of ETGs is earlier than that of LTGs for massive galaxies(M_(*)>10^(10)M_⊙),while low-mass(M_(*)≤10^(10)M_⊙)ETGs have statistically similar mass assembly histories as low-mass *** stellar metallicity of all massive galaxies shows a negative gradient and basically does not change with ***,in low-mass galaxies,the stellar metallicity gradient of elliptical galaxies is negative,and the stellar metallicity gradient of lenticular and spiral galaxies evolves from positive to *** are not all in a high-density environment,but exhibit mass *** the tidal strength increases,the star formation rate of low-mass ETGs rapidly *** results support a picture where massive galaxies exhibit inside-out quenching mode,while low-mass galaxies show outside-in quenching *** effects play an important role in regulating the mass assembly histories of low-mass ETGs.

关键词： Galaxy evolution-galaxies star formation-Galaxy formation

来源：评论

学校读者我要写书评

暂无评论

Efficient protocols for heavy hitter identification with local differential privacy

引用

Frontiers of computer Science 2022年第5期16卷 193-203页

作者： Dan ZHAO Suyun ZHAO Hong CHEN Ruixuan LIU Cuiping LI Wenjuan LIANG Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education Renmin University of ChinaBeijing 100872China School of Information Renmin University of ChinaBeijing 100872China

Local differential privacy(LDP),which is a technique that employs unbiased statistical estimations instead of real data,is usually adopted in data collection,as it can protect every user’s privacy and prevent the leakage of sensitive *** segment pairs method(SPM),multiple-channel method(MCM)and prefix extending method(PEM)are three known LDP protocols for heavy hitter identification as well as the frequency oracle(FO)problem with large ***,the low scalability of these three LDP algorithms often limits their ***,communication and computation strongly affect their ***,excessive grouping or sharing of privacy budgets makes the results *** address the abovementioned problems,this study proposes independent channel(IC)and mixed independent channel(MIC),which are efficient LDP protocols for FO with a large *** design a flexible method for splitting a large domain to reduce the number of ***,we employ the false positive rate with interaction to obtain an accurate *** experiments demonstrate that IC outperforms all the existing solutions under the same privacy guarantee while MIC performs well under a small privacy budget with the lowest communication cost.

关键词： local differential privacy frequency oracle heavy hitter

来源：评论

学校读者我要写书评

暂无评论

Improving Parameter Estimation and Defensive Ability of Latent Dirichlet Allocation Model Training Under Rényi Differential Privacy

引用

Journal of computer Science & Technology 2022年第6期37卷 1382-1397页

作者： Tao Huang Su-Yun Zhao Hong Chen Yi-Xuan Liu Key Laboratory of Data Engineering and Knowledge Engineering(Renmin University of China) Ministry of Education Beijing 100087China School of Information Renmin University of ChinaBeijing 100087China

Latent Dirichlet allocation(LDA)is a topic model widely used for discovering hidden semantics in massive text *** Gibbs sampling(CGS),as a widely-used algorithm for learning the parameters of LDA,has the risk of privacy ***,word count statistics and updates of latent topics in CGS,which are essential for parameter estimation,could be employed by adversaries to conduct effective membership inference attacks(MIAs).Till now,there are two kinds of methods exploited in CGS to defend against MIAs:adding noise to word count statistics and utilizing inherent *** two kinds of methods have their respective *** sampled from the Laplacian distribution sometimes produces negative word count statistics,which render terrible parameter estimation in *** inherent privacy could only provide weak guaranteed privacy when defending against *** is promising to propose an effective framework to obtain accurate parameter estimations with guaranteed differential *** key issue of obtaining accurate parameter estimations when introducing differential privacy in CGS is making good use of the privacy budget such that a precise noise scale is *** is the first time that R′enyi differential privacy(RDP)has been introduced into CGS and we propose RDP-LDA,an effective framework for analyzing the privacy loss of any differentially private ***-LDA could be used to derive a tighter upper bound of privacy loss than the overestimated results of existing differentially private CGS obtained byε-*** RDP-LDA,we propose a novel truncated-Gaussian mechanism that keeps word count statistics *** we propose distribution perturbation which could provide more rigorous guaranteed privacy than utilizing inherent *** validate that our proposed methods produce more accurate parameter estimation under the JS-divergence metric and obtain lower precision and recall when defending against MIAs.

关键词： latent Dirichlet allocation parameter estimation membership inference attack Rényi differential privacy

来源：评论

学校读者我要写书评

暂无评论

IGED:Towards Intelligent DDoS Detection Model Using Improved Generalized Entropy and DNN

引用

computers, Materials & Continua 2024年第8期80卷 1851-1866页

作者： Yanhua Liu Yuting Han HuiChen Baokang Zhao XiaofengWang Ximeng Liu College of Computer and Data Science Fuzhou UniversityFuzhou350108China Engineering Research Center of Big Data Intelligence Ministry of EducationFuzhou350108China Fujian Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou UniversityFuzhou350108China College of Computer National University of Defense TechnologyChangsha410073China

As the scale of the networks continually expands,the detection of distributed denial of service(DDoS)attacks has become increasingly *** propose an intelligent detection model named IGED by using improved generalized entropy and deep neural network(DNN).The initial detection is based on improved generalized entropy to filter out as much normal traffic as possible,thereby reducing data *** the fine detection is based on DNN to perform precise DDoS detection on the filtered suspicious traffic,enhancing the neural network’s generalization *** results show that the proposed method can efficiently distinguish normal traffic from DDoS *** with the benchmark methods,our method reaches 99.9%on low-rate DDoS(LDDoS),flooded DDoS and CICDDoS2019 datasets in terms of both accuracy and efficiency in identifying attack flows while reducing the time by 17%,31%and 8%.

关键词： DDoS real-time improved generalized entropy DNN

来源：评论

学校读者我要写书评

暂无评论

Hierarchical All-Pairs SimRank Calculation 28th

Hierarchical All-Pairs SimRank Calculation

引用

28th International Conference on database Systems for Advanced Applications, DASFAA 2023

作者： Zhang, Liangfu Li, Cuiping Zhang, Xue Chen, Hong Key Laboratory of Data Engineering and Knowledge Engineering of Ministry of Education School of Information Renmin University of China Beijing China

ISBN: (纸本)9783031306747

All-pairs SimRank calculation is a classic SimRank problem. However, all-pairs algorithms suffer from efficiency issues and accuracy issues. In this paper, we convert the non-linear simrank calculation into a new simple closed formulation of linear system. And we come up with a sequence of novel algorithms to efficiently solve the linear system with accuracy guarantees. To reduce the memory consumption and improve the computational efficiency, we build a hierarchical framework to calculate the all-pairs SimRank scores, which includes locally coarse calculation and globally refine calculation. We first solve the local linear systems generated from the subgraphs, then we refine the SimRank scores on the full graph from the residuals of the local structures. We also show that our algorithms outperform the state-of-the-art all-pairs SimRank computation algorithms on real graphs. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Computational efficiency

来源：评论

学校读者我要写书评

暂无评论

Resolution-Adaptive Representation Learning via Eliminating Abnormal Features for Cross-Resolution Person Re-Identification 14

Resolution-Adaptive Representation Learning via Eliminating ...

引用

14th International Conference on information Technology in Medicine and Education, ITME 2024

作者： Lu, Xing Lai, Fengshan Cao, Zhixiang Xia, Daoxun Guizhou Normal University School of Big Data and Computer Science Guiyang China Guizhou Normal University Key Laboratory of Information and Computing Science Guizhou Province Guiyang China Guizhou Normal University Engineering Laboratory for Applied Technology of Big Data in Education Guiyang China

ISBN: (纸本)9798350356670

Cross-resolution person re-identification(CR-ReID) seeks to overcome the challenge of retrieving and matching specific person images across cameras with varying resolutions. Numerous existing studies utilize established CNNs and ViTs models to resize captured low-resolution (LR) images and align them with high-resolution (HR) image features. However, these methods overlook the potential feature connections between LR and HR images. Consequently, CNNs or ViTs tend to highlight outliers rather than the intended characteristics in LR image attention maps. In this work, we propose the abnormal feature elimination and reconfiguration transformer (ART) network, a novel network architecture, for robust cross-resolution person re-identification tasks. Our proposed method uses a resolution feature discriminator to learn resolution invariant features and outputs feature matrices of images with different resolutions. We utilize output feature matrices to model LR and HR image interactions through cross-resolution landmark agent attention. We aim to mitigate abnormal image features and prioritize the attention on the target person by learning representations from input images of various resolutions. Extensive evaluations on three real-world datasets confirm the excellent results of our approach. © 2024 IEEE.

关键词： Contrastive Learning

来源：评论

学校读者我要写书评

暂无评论

SINN: A structural information-based neural network for traffic flow forecasting in large-scale road networks 4

SINN: A structural information-based neural network for traf...

引用

4th International Conference on Internet of Things and Smart City, IoTSC 2024

作者： Zhu, Weiguo Liu, Caiyuan Zhang, Xingyu Sun, Yongqi Key Laboratory of Big Data & Artificial Intelligence in Transportation Ministry of Education School of Computer and Information Technology Beijing Jiaotong University Beijing100044 China

ISBN: (纸本)9781510681767

Current traffic flow forecasting is a crucial component within intelligent transportation systems (ITSs). However, most existing studies still cannot be employed on large-scale data flow forecasting in real-world scenarios. In this paper, we design a spatiotemporal neural network called SINN for large-scale traffic flow forecasting tasks in real-world scenarios. First, we propose a transformer-based neural network to integrate the historical traffic flow into further traffic flow. Second, we propose a structural information-based hierarchical graph neural network module suitable for large-scale network structures, which can capture relevant node features within large-scale road networks for forecasting future traffic flow. Finally, we collect a large-scale traffic flow dataset and execute evaluation experiments. The experimental results indicate that SINN is capable of processing datasets with thousands of nodes. Compared with the methods that can execute the same scale datasets, SINN can make significant improvements by 44.29%, 26.54%, and 25.23% in the metrics of MAE, RMSE, and MAPE. © 2024 SPIE.

关键词： Graph neural networks

来源：评论

学校读者我要写书评

暂无评论

Using analytic hierarchy process to evaluate deep learning for infrared target recognition

引用

Multimedia Tools and Applications 2024年第38期83卷 86229-86245页

作者： Xu, Laixiang Cao, Bingxu Wei, Xinhong Li, Bei Su, Jingfeng Ning, Shiyuan Zhao, Junmin School of Computer and Data Science Henan University of Urban Construction Pingdingshan467036 China School of Information Engineering Luohe Vocational Technology College Henan University of Technology Luohe Institute of Technology Luohe462000 China School of Computer and Data Science Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Pingdingshan467036 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Henan University of Urban Construction Pingdingshan467036 China Department of Software Information China Electronics Technology Group Corporation 36-th Research Institute Jiaxing314033 China School of Computer and Data Science Research Center of Smart City and Big Data Engineering of Henan Province Research Center of Intelligent Campus Application Engineering of Henan Province Innovation Laboratory of Smart Traffic and Big Data Development of Hainan Province Henan University of Urban Construction Pingdingshan467036 China

In order to promote the evaluation performance of deep learning infrared automatic target recognition (ATR) algorithms in the complex environment of air-to-air missile research, we proposed an analytic hierarchy process (AHP) evaluation system consisting of the target recognition ability, the generalization recognition ability, the anti-interference ability, the background suppression ability, and the cost metrics ability. According to detailed quantitative analysis and experimental results, we establish probability evaluation models and get their probability values. Compared with traditional evaluation systems, our proposed method implementation is showing high reliability. Similar superior performances are also achieved, such as quick, comprehensive, and scientific. Through the above research, the key technology of deep learning performance evaluation in automatic target recognition has been broken through, which provides some basis and guidance for the analysis of infrared imaging-guided weapon systems. © The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024.

关键词： Infrared imaging

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：