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arXiv 2025年

作者： Zhang, Jian Wei, Bifan Qi, Shihao Zhu, Haiping Liu, Jun Lin, Qika School of Computer Science and Technology Xi’an Jiaotong University Xi’an China School of Continuing Education Xi’an Jiaotong University Xi’an China Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi’an Jiaotong University Xi’an China National University of Singapore Singapore

The construction of Generalized knowledge Graph (GKG), including knowledge graph, event knowledge graph and commonsense knowledge graph, is fundamental for various natural language processing tasks. Current studies typically construct these types of graph separately, overlooking holistic insights and potential unification that could be beneficial in computing resources and usage perspectives. However, a key challenge in developing a unified framework for GKG is obstacles arising from task-specific differences. In this study, we propose a unified framework for constructing generalized knowledge graphs to address this challenge. First, we collect data from 15 sub-tasks in 29 datasets across the three types of graphs, categorizing them into in-sample, counter-task, and out-of-distribution (OOD) data. Then, we propose a three-stage curriculum learning fine-tuning framework, by iteratively injecting knowledge from the three types of graphs into the Large Language Models. Extensive experiments show that our proposed model improves the construction of all three graph types across in-domain, OOD and counter-task data. Copyright © 2025, The Authors. All rights reserved.

关键词： knowledge graph

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Experience report:investigating bug fixes in machine learning frameworks/libraries

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Frontiers of Computer Science 2021年第6期15卷 43-58页

作者： Xiaobing SUN Tianchi ZHOU Rongcun WANG Yucong DUAN Lili BO Jianming CHANG School of Information Engineering Yangzhou UniversityYangzhou 225100China State Key Laboratory for Novel Software Technology Nanjing UniversityNanjing 210023China Jiangsu Engineering Research Center of Knowledge Management and Intelligent Service Yangzhou University Yangzhou 225127China School of Computer Science and Technology China University of Mining and TechnologyXuzhou 221116China School of Computer Science and Cyberspace Security Hainan UniversityHaikou 570228China

Machine learning(ML)techniques and algorithms have been successfully and widely used in various areas including software engineering *** other software projects,bugs are also common in ML projects and *** order to more deeply understand the features related to bug fixing in ML projects,we conduct an empirical study with 939 bugs from five ML projects by manually examining the bug categories,fixing patterns,fixing scale,fixing duration,and types of *** results show that(1)there are commonly seven types of bugs in ML programs;(2)twelve fixing patterns are typically used to fix the bugs in ML programs;(3)68.80%of the patches belong to micro-scale-fix and small-scale-fix;(4)66.77%of the bugs in ML programs can be fixed within one month;(5)45.90%of the bug fixes belong to corrective activity from the perspective of software ***,we perform a questionnaire survey and send them to developers or users of ML projects to validate the results in our empirical *** results of our empirical study are basically consistent with the feedback from *** findings from the empirical study provide useful guidance and insights for developers and users to effectively detect and fix bugs in MLprojects.

关键词： bug fixing machine learning project empirical study questionnaire survey

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Deep Transformation Model

arXiv

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arXiv 2024年

作者： Wang, Tong Zhang, Shunqin Zhang, Sanguo Huang, Jian Ma, Shuangge Department of Biostatistics Yale School of Public Health New HavenCT United States School of Mathematical Sciences University of Chinese Academy of Sciences China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences China Department of Applied Mathematics The Hong Kong Polytechnic University Hong Kong

There has been a significant recent surge in deep neural network (DNN) techniques. Most of the existing DNN techniques have restricted model formats/assumptions. To overcome their limitations, we propose the nonparametric transformation model, which encompasses many popular models as special cases and hence is less sensitive to model mis-specification. This model also has the potential of accommodating heavy-tailed errors – a robustness property not broadly shared. Accordingly, a new loss function, which fundamentally differs from the existing ones, is developed. For computational feasibility, we further develop a double rectified linear unit (DReLU)based estimator. To accommodate the scenario with a diverging number of input variables and/or noises, we propose variable selection based on group penalization. We further expand the scope to coherently accommodate censored survival data. The estimation and variable selection properties are rigorously established. Extensive numerical studies, including simulations and data analyses, establish the satisfactory practical utility of the proposed methods. Copyright © 2024, The Authors. All rights reserved.

关键词： Deep neural networks

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The K-Step H Indices in Citation Networks at the Paper, Author, and Institution Levels

SSRN

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SSRN 2023年

作者： Yang, Alex Jie Wu, Linwei Zhang, Qi Wang, Hao Deng, Sanhong School of Information Management Nanjing University 22 Hankou Rd. Nanjing210093 China Jiangsu Key Laboratory of Data Engineering and Knowledge Service Nanjing University Nanjing210093 China International Joint Informatics Laboratory Nanjing University China

From the viewpoint of high-generation citation networks, h indices can be extended to global metrics at both basic and aggregated levels. To accomplish this, three types of networks are designed: the paper-paper network, the author-paper-paper network, and the institution-paper-paper network. The k-step h index is then proposed at the level of papers, authors, and institutions, respectively. Through a comprehensive empirical study based on the APS dataset, it is found that the k-step h index extends the depth and dimensionality of the Hirsh core, allowing for more global information. The consistency and convergent validity of the k-step h indices are quantitatively assessed. The results indicate that the k-step h index demonstrates a high degree of consistency and focuses on the potential for further research, and is capable of measuring the long-term reputation rather than short-term popularity. The convergent validity of the k-step h indices is rigorously tested using benchmark examples such as Nobel laureates and their publications, and they demonstrate superior performance in identifying seminal papers and prominent scientists compared to traditional metrics at the paper and author levels. The k-step h index also excels in ranking institutions, offering a promising new approach for evaluating the impact and influence of scientific entities at both the basic and aggregate levels. This opens up exciting avenues for future research. © 2023, The Authors. All rights reserved.

关键词： Benchmarking

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A virtual geographic environment for dynamic simulation and analysis of tailings dam failure

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International Journal of Digital Earth 2021年第9期14卷 1194-1212页

作者： Dayu Yu Liyu Tang Fan Ye Chongcheng Chen Key Laboratory of Spatial Data Mining&Information Sharing Ministry of Education of ChinaFuzhou UniversityFuzhouPeople’s Republic of China National Engineering Research Center of Geospatial Information Technology Fuzhou UniversityFuzhouPeople’s Republic of China School of Remote Sensing and Information Engineering Wuhan UniversityWuhanPeople’s Republic of China

It is of great significance for disaster prevention and mitigation to carry out disaster simulations for dam failure accidents in advance,but at present,there are few professional systems for disaster simulations of tailings *** this paper,we focused on the construction of a virtual geographic environment(VGE)system that provides an effective tool for visualizing the dam-break process of a tailings *** dam-break numerical model of the tailings dam based on computational fluid dynamics(CFD)was integrated into the VGE *** infrastructure of the VGE was supported by a 3-D geographic information system(GIS)with a user-friendly interface for the initiation,visualization,and analysis of the dynamic process of tailings dam *** technologies,including the integration of numerical models,rendering of large-scale scenes,and optimizations of disaster simulation and visualization,were discussed in *** the prototype system,information on the run-out path,travel distance,*** be obtained to visually describe the flow motion released by two dam failure *** simulation results showed that the VGE can be used for the multidimensional,dynamic and interactive visualization of dam-break disasters,and can also be useful for assessing the risk associated with tailings dams.

关键词： Vitrual geographic environment tailings dam break computational fluid dynamics spatiotemporal process simulation visualization analysis

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Spatiotemporal Evolution of West Africa's Urban Landscape Characteristics Applying Harmonized DMSP-OLS and NPP-VIIRS Nighttime Light(NTL)data

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Chinese Geographical Science 2022年第6期32卷 933-945页

作者： SONO Douglas WEI Ye CHEN Zuoqi JIN Ying School of Geographical Sciences Northeast Normal UniversityChangchun 130024China Natural Resources Institute of Jilin Province Changchun 130024China Key Laboratory of Spatial Data Mining and Information Sharing of Ministry of Education National&Local Joint Engineering Research Center of Satellite Geospatial Information TechnologyFuzhou UniversityFuzhou 35002China The Academy of Digital China Fuzhou UniversityFuzhou 350002China School of Humanities and Law Northeastern UniversityShenyang 110169China

Investigating urban expansion patterns aids in the management of urbanization and in ameliorating the socioeconomic and environmental issues associated with economic transformation and sustainable *** Harmonized Defense Meteorological Satellite Program-Operational Line-scan System(DMSP-OLS)and the Suomi National Polar-Orbiting Partnership-Visible Infrared Imagery Radiometer Suite(NPP-VIIRS)Nighttime Light(NTL)data,this paper investigated the characteristics of urban landscape in West *** the harmonized NTL data,spatial comparison and empirical threshold methods were employed to detect urban changes from 1993 to *** examined the rate of urban change and calculated the direction of the urban expansion of West Africa using the center-of-gravity method for urban *** addition,we used the landscape expansion index method to assess the processes and stages of urban growth in West *** accuracy of urban area extraction based on NTL data were R^(2)=0.8314 in 2000,R^(2)=0.8809 in 2006,R^(2)=0.9051 in 2012 for the DMSP-OLS and the simulated NPP-VIIRS was R^(2)=0.8426 in 2018,by using Google Earth images as *** results indicated that there was a high rate and acceleration of urban landscapes in West Africa,with rates of 0.0160,0.0173,0.0189,and 0.0686,and accelerations of 0.31,0.42,0.54,and 0.90 for the periods of 1998–2003,2003–2008,2008–2013,and 2013–2018,*** expansion direction of urban agglomeration in West Africa during 1993–2018 was mainly from the coast to ***,cities located in the Sahel Region of Africa and in the middle zone expanded from north to ***,the results showed that the urban landscape of West Africa was mainly in a scattered and disordered’diffusion’process,whereas only a few cities located in coastal areas experiencing the process of’coalescence’according to urban growth phase *** study provides urban planners with relevant insights for the urban expansion character

关键词： urban expansion nighttime light remote sensing DMSP-OLS(Defense Meteorological Satellite Program-Operational Line-scan System) NPP-VIIRS(Suomi National Polar-Orbiting Partnership-Visible Infrared Imagery Radiometer Suite) spatiotemporal evolution West Africa

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An anonymous authentication and key exchange protocol in smart grid

Journal of Network Intelligence

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Journal of Network Intelligence 2021年第2期6卷 206-215页

作者： Luo, Yi Zheng, Wei-Min Chen, Yeh-Cheng Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou350100 China College of Computer Science and Engineering Shandong University of Science and Technology Qingdao266590 China Department of Computer Science University of California DavisCA95616 United States

With the use of a large number of digital devices in smart grid, how to protect the security of communication in Advanced Metering Infrastructure (AMI) has become a difficult problem. AMI plays an important role in smart grid, which is used two-way communication between users and electricity companies. AMI includes smart meters(SM), data collectors, AMI Head-End(AHE), etc. In this paper, we present an authentication and key exchange protocol between the smart meter and the AMI Head-End in smart grid. The security of proposed scheme is proved by random oracle model and BAN logic. At the end of the paper, the performance analysis shows that the scheme is efficient and suitable for AMI. © 2021, Taiwan Ubiquitous Information. All rights reserved.

关键词： Authentication

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BBA-NET: A BI-BRANCH ATTENTION NETWORK FOR CROWD COUNTING

arXiv

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arXiv 2022年

作者： Houyi, Yi Hou Li, Chengyang Yang, Fan Ma, Cong Zhu, Liping Li, Yuan Jia, Huizhu Xie, Xiaodong National Engineering Laboratory for Video Technology Peking University China Key Lab of Petroleum Data Mining China University of Petroleum Beijing China

In the field of crowd counting, the current mainstream CNN-based regression methods simply extract the density information of pedestrians without finding the position of each person. This makes the output of the network often found to contain incorrect responses, which may erroneously estimate the total number and not conducive to the interpretation of the algorithm. To this end, we propose a Bi-Branch Attention Network (BBA-NET) for crowd counting, which has three innovation points. i) A two-branch architecture is used to estimate the density information and location information separately. ii) Attention mechanism is used to facilitate feature extraction, which can reduce false responses. iii) A new density map generation method combining geometric adaptation and Voronoi split is introduced. Our method can integrate the pedestrian's head and body information to enhance the feature expression ability of the density map. Extensive experiments performed on two public datasets show that our method achieves a lower crowd counting error compared to other state-of-the-art methods. © 2022, CC BY.

关键词： Convolutional neural networks

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Echo of Neighbors: Privacy Amplification for Personalized Private Federated Learning with Shuffle Model

arXiv

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arXiv 2023年

作者： Liu, Yixuan Zhao, Suyun Xiong, Li Liu, Yuhan Chen, Hong Key Laboratory of Data Engineering and Knowledge Engineering Ministry of Education Renmin University of China China Engineering Research Center Ministry of Education on Database and BI China Information School Renmin University of China China Department of Computer Science Emory University United States

Federated Learning, as a popular paradigm for collaborative training, is vulnerable against privacy attacks. Different privacy levels regarding users’ attitudes need to be satisfied locally, while a strict privacy guarantee for the global model is also required centrally. Personalized Local Differential Privacy (PLDP) is suitable for preserving users’ varying local privacy, yet only provides a central privacy guarantee equivalent to the worst-case local privacy level. Thus, achieving strong central privacy as well as personalized local privacy with a utility-promising model is a challenging problem. In this work, a general framework (APES) is built up to strengthen model privacy under personalized local privacy by leveraging the privacy amplification effect of the shuffle model. To tighten the privacy bound, we quantify the heterogeneous contributions to the central privacy user by user. The contributions are characterized by the ability of generating "echos" from the perturbation of each user, which is carefully measured by proposed methods Neighbor Divergence and Clip-Laplace Mechanism. Furthermore, we propose a refined framework (S-APES) with the post-sparsification technique to reduce privacy loss in high-dimension scenarios. To the best of our knowledge, the impact of shuffling on personalized local privacy is considered for the first time. We provide a strong privacy amplification effect, and the bound is tighter than the baseline result based on existing methods for uniform local privacy. Experiments demonstrate that our frameworks ensure comparable or higher accuracy for the global model. © 2023, CC BY.

关键词： Learning systems

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Collaborative Ontology Matching With Dual Population Genetic Programming and Active Meta-Learning

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IEEE Transactions on Evolutionary Computation 2025年

作者： Xue, Xingsi Lin, Jerry Chun-Wei Jiang, Zhaohang Fujian University of Technology Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian Fuzhou350118 China Silesian University of Technology Department of Distributed Systems and IT Devices Akademicka Gliwice44-100 Poland Taiyuan University of Technology School of Electrical and Power Engineering Shanxi Taiyuan030024 China

Ontology provides a structured language to encapsulate domain-specific knowledge and harmonize diverse data. Ontology matching identifies similar entities in distinct ontologies, facilitating knowledge integration and information exchange. Similarity features are crucial for ontology matching by measuring entity resemblance, but noisy and redundant features can obscure relevant ones, reducing matching quality. To improve the accuracy of matching results, we propose a dual population genetic programming with an active meta-learning to build a high-quality similarity feature, which owns three novel components. First, a dual population genetic programming is developed to construct high-level similarity feature with a two-layer individual representation, a dual population based co-evolutionary mechanism, and a novel fitness function based on partial standard alignment. Second, a new active learning model is presented to update the partial standard alignment through an efficient interactive procedure, guiding the algorithm towards building more reliable similarity features. Finally, a weighted random forest meta-learning model is designed to train the expert vote aggregation model with their historical behaviors, and fine-tunes the model's performance with a compact genetic algorithm. Experimental results on the Ontology Alignment Evaluation Initiative's interactive matching tasks demonstrate that our method consistently achieves higher accuracy and better efficiency compared to advanced matching techniques across various expert error rates. © 1997-2012 IEEE.

关键词： Procedure oriented languages

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