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IEEE International Conference on data mining (ICDM)

作者： Zhao Zhang Xianzhen Li Haijun Zhang Yi Yang Shuicheng Yan Meng Wang School of Computer Science and Information Engineering Hefei University of Technology Hefei China Key Laboratory of Knowledge Engineering with Big Data (Ministry of Education) & Intelligent Interconnected Systems Laboratory of Anhui Province Hefei University of Technology Hefei China School of Computer Science and Technology Soochow University Suzhou China Harbin Institute of Technology (Shenzhen) Shenzhen China Centre for Artificial Intelligence University of Technology Sydney Sydney NSW Australia Sea AI Lab (SAIL) & National University of Singapore Singapore

ISBN: (纸本)9781665423991

Deep subspace clustering (DSC) with the auto-encoder and self-expression layer is of great concern due to encouraging performance. However, existing methods usually adopt a “single-task” strategy based on a single dataset, without considering other related tasks or data. As such, they cannot discover other useful information to improve the clustering task. Besides, the local structure preservation of the latent codes in mapping is usually ignored. In this paper, we therefore present an effective “multi-task” strategy via the self-supervised data augmentation, and propose a new end-to-end trainable Triplet Deep Subspace Clustering Network (TDSC-net). Specifically, TDSC-net firstly generates triplet data (i.e., anchor, positive and negative data) from input data by a spectral clustering module and a self-supervised data augmentation module. This can enable it to inherit the merits of self-supervised learning and multitask learning implicitly. After that, TDSC-net builds a triplet deep autoencoder network with a self-expression layer, which takes the triplet data as input, where they share the common network layers (i.e., autoencoder and self-expression layers) over the triple tasks for complementary learning and mutual supervision. A triplet loss is also included to retain the local information of deep latent codes, which will also benefit the self-expression. Furthermore, TDSC-net separates the self-expression layer from decoding process to improve the efficiency of reconstruction. Extensive results on several public datasets demonstrate the effectiveness of our triplet-task DSC strategy.

关键词： Codes Conferences Multitasking Decoding data mining Task analysis

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knowledge graph enhanced neural collaborative recommendation

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Expert Systems with Applications 2021年 164卷 113992-113992页

作者： Sang, Lei Xu, Min Qian, Shengsheng Wu, Xindong Key Laboratory of Knowledge Engineering with Big Data (Hefei University of Technology) Ministry of Education Hefei 230009 China Faculty of Engineering and Information Technology University of Technology Sydney Sydney 2007 Australia School of Computer Science and Information Engineering Hefei University of Technology Hefei 230009 China Institute of Automation Chinese Academy of Sciences Beijing 100190 China Mininglamp Academy of Sciences Mininglamp Technology Beijing 100084 China

Existing neural collaborative filtering (NCF) recommendation methods suffer from severe sparsity problem. knowledge Graph (KG), which commonly consists of fruitful connected facts about items, presents an unprecedented opportunity to alleviate the sparsity problem. However, pure NCF models can hardly model the high-order connectivity in KG, and ignores complex pairwise correlations between user/item embedding dimensions. To address these problems, we propose a novel knowledge graph enhanced Neural Collaborative Recommendation (K-NCR) framework, which effectively combines user–item interaction information and auxiliary knowledge information for recommendation task into three parts: (1) For items, the proposed propagating model learns the representation of item entity. It recursively aggregates information from its multi-hop neighbours in KG, and employs an attention mechanism to discriminate the importance of the relation type to mine users’ potential preferences. (2) For users, another heterogeneous attention weights are leveraged to strengthen the embedding learning of users. (3) The user and item embeddings are then fed into a newly designed two-dimensional interaction map with convolutional hidden layers to model the complex pairwise correlations between their embedding dimensions explicitly. Extensive experimental results on three benchmark datasets demonstrate the effectiveness of our K-NCR framework. © 2020

关键词： Attention mechanism Graph convolutional networks knowledge graph Neural collaborative filtering Recommendation system

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Disentangled Representation Learning with Transmitted Information Bottleneck

arXiv

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arXiv 2023年

作者： Dang, Zhuohang Luo, Minnan Jia, Chengyou Dai, Guang Wang, Jihong Chang, Xiaojun Wang, Jingdong The School of Computer Science and Technology The Ministry of Education Key Laboratory of Intelligent Networks and Network Security The Shaanxi Province Key Laboratory of Big Data Knowledge Engineering Xi'an Jiaotong University Shaanxi Xi’an710049 China The SGIT AI Laboratory Xi’an710048 China The State Grid Shaanxi Electric Power Company Ltd. State Grid Corporation of China Xi’an710048 China The School of Information Science and Technology University of Science and Technology of China Hefei230026 China Abu Dhabi United Arab Emirates Baidu Inc Beijing100085 China

Encoding only the task-related information from the raw data, i.e., disentangled representation learning, can greatly contribute to the robustness and generalizability of models. Although significant advances have been made by regularizing the information in representations with information theory, two major challenges remain: 1) the representation compression inevitably leads to performance drop;2) the disentanglement constraints on representations are in complicated optimization. To these issues, we introduce Bayesian networks with transmitted information to formulate the interaction among input and representations during disentanglement. Building upon this framework, we propose DisTIB (Transmitted Information Bottleneck for Disentangled representation learning), a novel objective that navigates the balance between information compression and preservation. We employ variational inference to derive a tractable estimation for DisTIB. This estimation can be simply optimized via standard gradient descent with a reparameterization trick. Moreover, we theoretically prove that DisTIB can achieve optimal disentanglement, underscoring its superior efficacy. To solidify our claims, we conduct extensive experiments on various downstream tasks to demonstrate the appealing efficacy of DisTIB and validate our theoretical analyses. Copyright © 2023, The Authors. All rights reserved.

关键词： Information theory

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Research on Pre-view Method of Safety Level of Cascading Trip for Power Grid 6th

Research on Pre-view Method of Safety Level of Cascading Tri...

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6th International Conference on Advanced Machine Learning Technologies and Applications, AMLTA 2021

作者： Deng, Huiqiong Li, Qinbin Zheng, Rongjin Li, Peiqiang Chang, Kuo-Chi School of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou Fujian350118 China Fujian Provincial University Engineering Research Center of Smart Grid Simulation Analysis and Integrated Control Fuzhou Fujian350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou Fujian350118 China College of Mechanical & Electrical Engineering National Taipei University of Technology No. 1 Section 3 Zhongxiao East Road Taipei10608 Taiwan Department of Business Administration North Borneo University College Lot 47 Block-F Alamesra Permai Plaza 2 Jln Sulaman Kota Kinabalu Sabah88400 Malaysia

ISBN: (纸本)9783030697167

This article introduces a method by which the power grid's security level can be observed in advance based on the expected initial failure. Firstly, based on the general form of cascading trip, this paper gives a mathematical expression of grid tripping based on cascading trip relay protection action behavior. According to the mathematical expression, the relationship between grid tripping and grid node injection power is discussed. According to this relationship, the distance between the node injection power under the current operation state and the nearest critical state node injection power is taken as the index to measure the power grid's security for cascading trip. According to this index, combined with various power grid constraints before and after the initial fault, a mathematical model for obtaining this safety index is given. This model is an optimized mathematical model. For the model, this paper gives a solution idea based on particle swarm. Finally, a few cases are performed in the IEEE-14 node system, and the calculations of the cases proved the accuracy of the proposed model and method. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Electric load flow

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Biomarker-guided heterogeneity analysis of genetic regulations via multivariate sparse fusion

arXiv

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arXiv 2022年

作者： Zhang, Sanguo Hu, Xiaonan Luo, Ziye Jiang, Yu Sun, Yifan Ma, Shuangge No. 59 Zhongguancun Street Haidian District Beijing100872 China School of Mathematical Sciences Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Science Beijing China Center of Applied Statistics School of Statistics Renmin University of China Beijing China School of Public Health University of Memphis Tennessee United States Department of Biostatistics Yale University Connecticut United States 60 College ST New HavenCT06520 United States

Heterogeneity is a hallmark of many complex diseases. There are multiple ways of defining heterogeneity, among which the heterogeneity in genetic regulations, for example GEs (gene expressions) by CNVs (copy number variations) and methylation, has been suggested but little investigated. Heterogeneity in genetic regulations can be linked with disease severity, progression, and other traits and is biologically important. However, the analysis can be very challenging with the high dimensionality of both sides of regulation as well as sparse and weak signals. In this article, we consider the scenario where subjects form unknown subgroups, and each subgroup has unique genetic regulation relationships. Further, such heterogeneity is "guided" by a known biomarker. We develop an MSF (Multivariate Sparse Fusion) approach, which innovatively applies the penalized fusion technique to simultaneously determine the number and structure of subgroups and regulation relationships within each subgroup. An effective computational algorithm is developed, and extensive simulations are conducted. The analysis of heterogeneity in the GE-CNV regulations in melanoma and GE-methylation regulations in stomach cancer using the TCGA data leads to interesting findings. Copyright © 2022, The Authors. All rights reserved.

关键词： Biomarkers

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Optimizing multiple ontology alignments through hybrid evolutionary algorithm based on a new elitist strategy

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ICIC Express Letters, Part B: Applications 2016年第6期7卷 1241-1248页

作者： Jiang, Li Tsai, Pei-Wei Xue, Xingsi Computer Department Fuzhou Polytechnic No. 8 Lianrong Road University Town Minhou Fuzhou350108 China College of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou350118 China

In this paper, we propose a hybrid evolutionary algorithm based on a new elitist strategy to address the problem of optimizing the multiple ontology alignments simultaneously. Comparing with the conventional approach, our method is able to deal with multiple pair of ontologies at a time, and through a new elitist strategy, avoid the bias improvement caused by f-measure. Experimental results show that our approach is effective. © 2016 ICIC International.

关键词： Ontology

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Deep well construction of big data platform based on multi-source heterogeneous data fusion

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International Journal of Internet Manufacturing and Services 2019年第4期6卷 371-388页

作者： Zhang, Yu Wang, Yange Ding, Hongwei Li, Yongzhen Bai, Yanping School of Electrical and Information Engineering Beijing Key Laboratory of Intelligent Processing for Building Big Data Beijing University of Civil Engineering and Architecture No. 1 Zhanlanguan Road Xicheng District Beijing100044 China China University of Mining and Technology No. 16 Qinghua Road Haidian District Beijing100083 China School of Software Beijing University of Technology Beijing100124 China Network Information Center Beijing University of Civil Engineering and Architecture Beijing100044 China College of Management Capital Normal University Beijing100048 China

At present, energy saving and emission reduction had become a problem of great concern for mankind. At the same time, there were some problems in the mining industry, such as waste of resources, low efficiency and easy occurrence of industrial accidents. Therefore, this paper had designed a deep well construction big data platform. The high precision and bear great pressure sensors were added to the system to solve the difficult problem of collecting information in deep wells by ordinary sensors. The multi-source heterogeneous data fusion algorithm was added to the system to solve the problem that the format of the data acquisition was different. In conclusion, the completion of the platform could achieve data monitoring in the process of mines. It not only helps to enhance the safety of mine construction, but also provides data analytical tools for further theoretical research of mine construction. © 2019 Inderscience Enterprises Ltd.

关键词： Big data

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A Three-Step Underwater Moving Target Location Algorithm Based on FDOA

A Three-Step Underwater Moving Target Location Algorithm Bas...

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Wireless Communications and Applications (ICWCAPP), International Conference on

作者： Shengrong Zhang Kun Zhang Chuan Tian Ju Huang Chong Shen Sansha Guohai Communication Technology Development Co.Ltd. Sansha Hainan China School of Information Science and Technology Hainan Normal University Haikou China State Key Laboratory of Marine Resources Utilization in South China Sea Hainan University Haikou Hainan China Key Laboratory of Island Tourism Resource Data Mining and Monitoring Ministry of Culture and Tourism Hainan Tropical Ocean University Sanya Hainan China Institute of Deep-sea Science and Engineering Chinese Academy of Sciences Sanya Hainan China

The position and velocity estimation of underwater moving targets is an important part of the application of underwater sensor networks. The commonly used fusion of time difference of arrival (TDOA) and angle of arrival (AOA) can only roughly estimate the target position, but also has some limitations for nonlinear problems. So in order to overcome the nonlinear problem and improve the accuracy of underwater target *** on TDOA and AOA, this paper adopts a three-step location method which combines frequency difference of arrival (FDOA).At the same time, the whale algorithm is used to optimize the measurement error based on the weighted least square method (Tswls). Finally, the experimental results show that compared with TDOA location method and tdoa/aoa hybrid location algorithm, this method is superior to the above methods in the accuracy and bias of position and velocity estimation.

关键词：

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Research on Intelligent Frequency Control of Permanent Magnet Synchronous Motor

Research on Intelligent Frequency Control of Permanent Magne...

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International Conference on Intelligent Computing, Automation and Systems (ICICAS)

作者： Kuo-Chi Chang Zhongxin Hu Kai-Chun Chu Fu-Hsiang Chang Hsiao-Chuan Wang Tsui-Lien Hsu Yuh-Chung Lin Yuwen Zhou Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology Fuzhou China College of Mechanical & Electrical Engineering National Taipei University of Technology Taipei Taiwan North Borneo University College Sabah Malaysia Fujian University of Technology Fuzhou China Shih-Hsin University Taipei Taiwan Institute of Environmental Engineering National Taiwan University Taipei Taiwan Institute of Construction Engineering and Management National Central University Taoyuan Taiwan

The development of PMSM is inseparable from the continuous improvement of the performance-to-price ratio of permanent magnet materials and the development of power electronic equipment. This is exactly the study of PMSM. Entered a new stage, PMSM plays an important role in military, industry and daily life. Dating vector control theory to the field of PMSM speed regulation is also a major breakthrough. Researchers combined the mathematical model of PMSM with the vector control model. It is based on this that the PMSM vector control double closed-loop model was established. Simulate in MATLAB software. There are current module, speed module and PMSM main module in the simulation diagram, and then analyze the simulation results.

关键词： Computational modeling Simulation Software Regulation Power electronics Mathematical model Machine vector control

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Cluster based hybrid key management scheme for ad hoc networks

引用

ICIC Express Letters, Part B: Applications 2016年第6期7卷 1329-1334页

作者： Zhang, Jing Xu, Li Tang, Rongmei Zhang, Shunmiao School of Information Science and Engineering Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou350118 China Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No. 3 Xueyuan Road University Town Minhou Fuzhou350118 China School of Mathematics and Computer Science Fujian Normal University Fuzhou University Town Minhou Fuzhou350118 China

Secure communication is part of the most important aspects for ad hoc networks. One cluster based Hybrid key Management Scheme is proposed in this paper for ad hoc networks. The clusters are constructed by the R-hop connected dominating sets based Partition Algorithm, which is only with the knowledge of local connectivity information. Furthermore, Hybrid key Management Scheme can be seen as an integration of both the asymmetric key and symmetric key cryptography. The asymmetric one is based on the elliptic curve cryptosystem, which is an asymmetric one. However, inter cluster key management is based on symmetric key encryption. Experimental results show this scheme is reliable and it is able to achieve higher success of landing ratio than other comparable algorithms. © 2016 ICIC International.

关键词： Ad hoc networks

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