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12th IEEE International Conference on big knowledge, ICBK 2021

作者： Wang, Ru Wu, Meng Ji, Shengwei Hefei University of Technology Key Laboratory of Knowledge Engineering With Big Data Ministry of Education School of Computer Science and Information Engineering Hefei China

ISBN: (纸本)9781665438582

knowledge Graph (KG) is a directed heterogeneous information network that contains a large number of entities and relations, which is widely used as effective side information in rec-ommender systems. Moreover, in recommender systems, the Graph Convolutional Network (GCN) model is introduced to mine the relatedness between entities in a KG because of its efficiency in extracting spatial features on topological graphs. The knowledge Graph Convolutional Network (KGCN) model up-dates the embedding of a currently positioned entity by aggregating the information of adjacent entities selected randomly. Never-theless, it has two limititations: 1) the information of neighbors se-lected randomly cannot accurately represent the current entity in the KG;2) the model is hard to converge as graph features (i.e. The spatial relation features and semantic information features of en-tities in the KG) grow. To solve these limitations, in this paper, a meta-path (i.e., a sequence of artificially constructed relationships) is introduced into the selection of neighbors in the KGCN model to enhance the representation of each entity. Furthermore, two construction methods of the meta-path - constructing a meta-path based on the same relation (KGCN-SP) and the characteris-tics of KG (KGCN-MP) -are proposed. The experiments based on three real-world datasets demonstrate that the neighbor selection based on the meta-path is able to collect more accurate infor-mation from a KG and improve the recommendation performance effectively. © 2021 IEEE.

关键词： knowledge graph

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Research of photon counting imaging detector based on delay line anode 10

Research of photon counting imaging detector based on delay ...

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10th Symposium on Novel Optoelectronic Detection Technology and Applications

作者： Liu, Yong'an Zhang, Yalong Yang, Xianghui Zhang, Ruili Liu, Zhe Sheng, Lizhi State Key Laboratory of Transient Optics and Photonics Xi'an Institute of Optics and Precision Mechanics Chinese Academy of Sciences Xi'an China National Engineering Laboratory for Integrated Aero-Space-Ground-Ocean Big Data Application Technology China University of Chinese Academy of Sciences Beijing China

ISBN: (数字)9781510688155

ISBN: (纸本)9781510688148

Photon counting imaging detector based on microchannel plate (MCP) and position-sensitive anode readout has the ability to detect single photon, and has been widely used in space detection, high-energy physics and bioluminescence imaging. Traditionally, the detector consists of photocathode, electron multiplication part and position decoding part, in which position decoding is accomplished by position sensitive anode. The delay line anode not only has high spatial resolution and large detection area, but also has high count rate. Based on the principle of delay line decoding, an induction readout cross delay line anode (XDL) is designed and fabricated. And the performance of the detector is tested by using the experimental system. The results show that the width of XDL anode output pulse (FWHM) is about 4ns, the spatial resolution of the detector is better than 100μm, and the dark count rate is 2s). © 2025 SPIE.

关键词： Photocathodes

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Interest Points Analysis for Internet Forum Based on Long-Short Windows Similarity

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Computers, Materials & Continua 2022年第8期72卷 3247-3267页

作者： Xinghai Ju Jicang Lu Xiangyang Luo Gang Zhou Shiyu Wang Shunhang Li Yang Yang State Key Laboratory of Mathematical Engineering and Advanced Computing Zhengzhou450001China School of Computing and Information Systems Singapore Management University188065Singapore College of Computer Science and Big Data Fuzhou UniversityFuzhou350116China

For Internet forum Points of Interest(PoI),existing analysis methods are usually lack of usability analysis under different conditions and ignore the long-term variation,which lead to blindness in method *** address this problem,this paper proposed a PoI variation prediction framework based on similarity analysis between long and short *** on the framework,this paper presented 5 PoI analysis algorithms which can be categorized into 2 types,i.e.,the traditional sequence analysis methods such as autoregressive integrated moving average model(ARIMA),support vector regressor(SVR),and the deep learning methods such as convolutional neural network(CNN),long-short term memory network(LSTM),Transformer(TRM).Specifically,this paper firstly divides observed data into long and short windows,and extracts key words as PoI of each ***,the PoI similarities between long and short windows are calculated for training and ***,series of experiments is conducted based on real Internet forum *** results show that,all the 5 algorithms could predict PoI variations well,which indicate effectiveness of the proposed *** the length of long window is small,traditional methods perform better,and SVR is the *** the contrary,the deep learning methods show superiority,and LSTM performs *** results could provide beneficial references for PoI variation analysis and prediction algorithms selection under different parameter configurations.

关键词： Point of interest(PoI)analysis long and short windows sequential analysis deep learning

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Detecting Ethereum Phishing Scams via Multi-transaction-view Graph Attention Network 29

Detecting Ethereum Phishing Scams via Multi-transaction-view...

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29th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2023

作者： Zhuo, Shaoxuan Li, Guang Wu, Weigang Bian, Jing Sun Yat-Sen University School of Computer Science and Engineering Guangzhou China Guangdong Province Key Laboratory of Big Data Analysis and Processing China Sun Yat-Sen University Guangdong Province Key Laboratory of Computational Science Guangzhou China

ISBN: (纸本)9798350330717

Cryptocurrency phishing scams is a significant treat to Ethereum, one of the most popular blockchain platforms. Most of existing Ethereum phishing detection methods are based on traditional machine learning or graph representation learning, which mostly rely on only statistical and structural features in local scope. In this paper, we propose Multi-transaction-view Graph Attention Network (MTvGAT), a novel phishing scam detection model that can make use of transaction patterns of different scopes. To obtain global-view information, we apply graph clustering and construct the global-view graph with multiple clusters, including all the nodes of the original transaction network. To obtain local view information, we apply neighborhood sampling, and construct local-view graphs with target nodes and their neighborhood nodes. Then, node features, edge features, and attention coefficients are aggregated to merge multi-view information into representation of nodes. We further combine global-view and local-view representations to finally identify phishing addresses from target nodes. Extensive experiments demonstrate that the proposed method can outperform existing ones with significant improvement. © 2023 IEEE.

关键词： Ethereum Graph neural network Phishing scams

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Research on key technologies of edge cache in virtual data space across WAN

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Frontiers of Computer Science 2023年第1期17卷 15-34页

作者： Jiantong HUO Yaowen XU Zhisheng HUO Limin XIAO Zhenxue HE State Key Laboratory of Software Development Environment Beihang UniversityBeijing 100191China School of Computer Science and Engineering Beihang UniversityBeijing 100191China High Performance Computing Center Beihang UniversityBeijing 100191China College of Software Beihang UniversityBeijing 100191China Hebei Key Laboratory of Agricultural Big Data Hebei Agricultural UniversityBaoding 071001China College of Computer Science and Technology Zhejiang UniversityHangZhou 310013China

The authors of this paper have previously proposed the global virtual data space system (GVDS) to aggregate the scattered and autonomous storage resources in China’s national supercomputer grid (National Supercomputing Center in Guangzhou, National Supercomputing Center in Jinan, National Supercomputing Center in Changsha, Shanghai Supercomputing Center, and Computer Network Information Center in Chinese Academy of Sciences) into a storage system that spans the wide area network (WAN), which realizes the unified management of global storage resources in China. At present, the GVDS has been successfully deployed in the China National Grid environment. However, when accessing and sharing remote data in the WAN, the GVDS will cause redundant transmission of data and waste a lot of network bandwidth resources. In this paper, we propose an edge cache system as a supplementary system of the GVDS to improve the performance of upper-level applications accessing and sharing remote data. Specifically, we first designs the architecture of the edge cache system, and then study the key technologies of this architecture: the edge cache index mechanism based on double-layer hashing, the edge cache replacement strategy based on the GDSF algorithm, the request routing based on consistent hashing method, and the cluster member maintenance method based on the SWIM protocol. The experimental results show that the edge cache system has successfully implemented the relevant operation functions (read, write, deletion, modification, etc.) and is compatible with the POSIX interface in terms of function. Further, it can greatly reduce the amount of data transmission and increase the data access bandwidth when the accessed file is located at the edge cache system in terms of performance, i.e., its performance is close to the performance of the network file system in the local area network (LAN).

关键词： virtual data space system wide area network edge cache redundant data transmission

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Unsupervised Statistical Text Simplification

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IEEE Transactions on knowledge and data engineering 2021年第4期33卷 1802-1806页

作者： Qiang, Jipeng Wu, Xindong Department of Computer Science Yangzhou University Yangzhou Jiangsu225127 China Key Laboratory of Knowledge Engineering with Big Data Hefei University of Technology Ministry of Education Hefei Anhui10084 China

Most recent approaches for Text Simplification (TS) have drawn on insights from machine translation to learn simplification rewrites from the monolingual parallel corpus of complex and simple sentences, yet their effectiveness strongly relies on large amounts of parallel sentences. However, there has been a serious problem haunting TS for decades, that is, the availability of parallel TS corpora is scarce or not fit for the learning task. In this paper, we will focus on one especially useful and challenging problem of unsupervised TS without a single parallel sentence. To the best of our knowledge, we present the first unsupervised text simplification system based on phrase-based machine translation system, which leverages a careful initialization of phrase tables and language models. On the widely used WikiLarge and WikiSmall benchmarks, our system respectively obtains 39.08 and 25.12 SARI points, even outperforms some supervised baselines. © 1989-2012 IEEE.

关键词： Machine translation

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Ordering Results on Largest Order Statistics from Multiple-Outlier Gamma Variables

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Communications in Mathematics and Statistics 2023年第2期11卷 257-282页

作者： Yiying Zhang Yanni Hu Peng Zhao School of Statistics and Data Science LPMC and KLMDASRNankai UniversityTianjin 300071People’s Republic of China SpeakIn Technologies Co. Ltd.Shanghai 200000People’s Republic of China School of Mathematics and Statistics and RIMS Jiangsu Provincial Key Laboratory of Educational Big Data Science and EngineeringJiangsu Normal UniversityXuzhou 221116People’s Republic of China

In this article,we carry out stochastic comparisons on the maximum order statistics arising from two batches of multiple-outlier gamma random variables with different shape and scale *** is proved that,under certain conditions,the majorization order between the vectors of shape parameters together with the weak majorization order[p-larger order]between the vectors of scale parameters implies the likelihood ratio order[hazard rate order]between the largest order *** results established here strengthen and generalize some known ones in the literature.

关键词： Gamma distribution Stochastic orders Largest order statistics Majorization p-Larger order

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Multi-Quadrotor Cooperative Encirclement and Capture Approach in Obstacle Environments

Multi-Quadrotor Cooperative Encirclement and Capture Approac...

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2025 IEEE International Conference on Mechatronics, ICM 2025

作者： Li, Zhenyu Wu, Ruixin Wang, Jin Hu, Chuanqi Zheng, Zhi Meng, Jun Lu, Guodong Zhejiang University State Key Laboratory of Fluid Power and Mechatronic Systems Hangzhou310058 China Zhejiang University Zhejiang Key Laboratory of Industrial Big Data and Robot Intelligent Systems Hangzhou310058 China Robotics Research Center of Yuyao City Ningbo315400 China College of Electrical Engineering Zhejiang University Hangzhou310027 China Center for Data Mining and Systems Biology College of Electrical Engineering Zhejiang University Hangzhou310027 China

ISBN: (纸本)9798331533892

This article proposes an algorithm designed for autonomous quadrotors to capture target quadrotors in complex obstacle environments, enabling multiple pursuers to perform distributed capture while simultaneously avoiding obstacles and collisions. We first introduce a 3D obstacle space representation method based on safety-priority reachable region (SPRR) and implement real-time construction for general point cloud maps. Subsequently, leveraging SPRR, we employ an area minimization approach to ensure the effective capture of the evader within a limited time. The outcomes are then integrated into a MINCO-based trajectory planning framework to ensure their practical execution by real quadrotors. Relying on SPRR, the optimization problem is simplified and the solution efficiency is improved. In the scenario of simulating the dynamics of real quadrotors, we compare the proposed algorithm with state-of-the-art evasion and pursuit methods, validating its effectiveness and advancements. This work presents a practical solution for multi-quadrotor collaborative capture. © 2025 IEEE.

关键词： Motion planning

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Glacial Lake Area Changes in High Mountain Asia during 1990-2020 Using Satellite Remote Sensing

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Research 2023年第2期2022卷 1-23页

作者： Meimei Zhang Fang Chen Huadong Guo Lu Yi Jiangyuan Zeng Bin Li International Research Center of Big Data for Sustainable Development Goals Beijing 100094China Key Laboratory of Digital Earth Science Aerospace Information Research InstituteChinese Academy of SciencesNo.9 Dengzhuang South RoadBeijing 100094China University of Chinese Academy of Sciences Beijing 100049China Key Laboratory of Coastal Environment and Resources Research of Zhejiang Province School of EngineeringWestlake UniversityHangzhou 310024China State Key Laboratory of Remote Sensing Science Aerospace Information Research InstituteChinese Academy of Sciences Beijing 100094China

Changes in a large-scale glacial lake area directly reflect the regional glacier status and climate ***,long time series of glacial lake dataset and comprehensive investigation of the spatiotemporal changes in the gla... 详细信息

关键词： glacial glacier lake

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knowledge-Guided Cross-Topic Visual Question Generation 30

Knowledge-Guided Cross-Topic Visual Question Generation

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Joint 30th International Conference on Computational Linguistics and 14th International Conference on Language Resources and Evaluation, LREC-COLING 2024

作者： Liu, Hongfei Wang, Guohua Xie, Jiayuan Chen, Jiali Fang, Wenhao Cai, Yi School of Software Engineering South China University of Technology China Key Laboratory of Big Data and Intelligent Robot South China University of Technology Ministry of Education China Department of Computing The Hong Kong Polytechnic University Hong Kong

ISBN: (纸本)9782493814104

Visual question generation (VQG) task aims to generate high-quality questions based on the input image. Current methods primarily focus on generating questions containing specified content utilizing answers or question types as constraints. However, these constraints make it challenging to control the topic of generated questions (e.g., conversation or test subject topics) for various applications. Thus, it is necessary to utilize topics as constraints to guide question generation. Considering that there are many topics and it is almost impossible for human annotations to cover them, we propose the cross-topic learning VQG (CTL-VQG) task, which aims to generate questions related to unseen topics in cross-topic scenarios. In this paper, we propose a knowledge-guided cross-topic visual question generation (KC-VQG) model to extract unseen topic-related information for question generation. Specifically, an image-topic feature extractor is introduced in our model to extract topic-related intuitive visual features;an image-topic knowledge extractor is used to extract and select the most appropriate topic-related implicit knowledge from large language models for generating questions. Extensive experiments show that our model outperforms baselines and can effectively generate unseen topic-related questions in cross-topic scenarios. © 2024 ELRA Language Resource Association: CC BY-NC 4.0.

关键词： data mining

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