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Efficient graph similarity join for information integration on graphs

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Frontiers of Computer Science 2016年第2期10卷 317-329页

作者： Yue wang hongzhi wang Jianzhong LI Hong GAO Department of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China

Graphs have been widely used for complex data representation in many real applications, such as social network, bioinformatics, and computer vision. Therefore, graph similarity join has become imperative for integrating noisy and inconsistent data from multiple data sources. The edit distance is commonly used to measure the similarity between graphs. The graph similarity join problem studied in this paper is based on graph edit distance constraints. To accelerate the similarity join based on graph edit distance, in the paper, we make use of a preprocessing strategy to remove the mismatching graph pairs with significant differences. Then a novel method of building indexes for each graph is proposed by grouping the nodes which can be reached in k hops for each key node with structure conservation, which is the k-hop tree based indexing method. As for each candidate pair, we propose a similarity computation algorithm with boundary filtering, which can be applied with good efficiency and effectiveness. Experiments on real and synthetic graph databases also confirm that our method can achieve good join quality in graph similarity join. Besides, the join process can be finished in polynomial time.

关键词： graph similarity join edit distance constraint khop tree based indexing structure conservation boundary filtering

Diversification on big data in query processing

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Frontiers of Computer Science 2020年第4期14卷 135-154页

作者： Meifan ZHANG hongzhi wang Jianzhong LI Hong GAO Department of Computer Science and Technology Harbin Institute of TechnologyHarbin150001China

Recently,in the area of big data,some popular applications such as web search engines and recommendation systems,face the problem to diversify results during query *** this sense,it is both significant and essential to propose methods to deal with big data in order to increase the diversity of the result *** this paper,we firstly define the diversity of a set and the ability of an element to improve the overall *** on these definitions,we propose a diversification framework which has good performance in terms of effectiveness and ***,this framework has theoretical guarantee on probability of ***,we design implementation algorithms based on this framework for both numerical and string ***,for numerical and string data respectively,we carry out extensive experiments on real data to verify the performance of our proposed framework,and also perform scalability experiments on synthetic data.

关键词： diversification query processing big data

A survey of uncertain data management

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Frontiers of Computer Science 2020年第1期14卷 162-190页

作者： Lingli LI hongzhi wang Jianzhong LI Hong GAO Department of Computer Science and Technology Heilongjiang UniversityHeilongjiang 150001China Department of Computer Science and Technology Harbin Institute of TechnologyHeilongjiang 150001China

Uncertain data are data with uncertainty information,which exist widely in database *** recent years,uncertainty in data has brought challenges in almost all database management areas such as data modeling,query representation,query processing,and data *** is no doubt that uncertain data management has become a hot research topic in the field of data *** this study,we explore problems in managing uncertain data,present state-of-the-art solutions,and provide future research directions in this *** discussed uncertain data management techniques include data modeling,query processing,and data mining in uncertain data in the forms of relational,XML,graph,and stream.

关键词： uncertain data probabilistic database probabilistic XML semi-structured data data stream

TEGDME Electrolyte Additive for High-performance Zinc Anodes

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Chemical Research in Chinese Universities 2023年第6期39卷 1037-1043页

作者： ZHANG Weiguo ZHANG Chong wang hongzhi wang huanhuan Department of Applied Chemistry School of Chemical Engineering and TechnologyTianjin UniversityTianjin 300350P.R.China

Aqueous zinc ion batteries(AZIBs)are expected to have a wide range of applications for large-scale electrochemical energy storage systems,but their practical application is severely limited by the presence of zinc dendrites,hydrogen evolution reactions(HER),corrosion reactions,and other *** optimization is considered to be one of the most effective methods for improving zinc anodes due to its simplicity,low production cost and remarkable effectiveness in suppressing zinc dendrite *** this paper,a tetra(ethylene glycol)dimethyl ether(TEGDME)electrolyte additive was used to improve the stability of the zinc anode by adding 0.1 g/L TEGDME to the conventional ZnSO_(4) electrolyte to prepare a mixed *** effect of TEGDME on the side reactions of zinc anode was first assessed by linear sweep voltammetry(LSV)and potentiodynamic *** effect of TEGDME on the structure and morphology of zinc surfaces was observed using an X-ray diffractometer(XRD)and a scanning electron microscope(SEM).And finally,the electrochemical performance of Zn|Zn symmetric cells,Zn||Ti asymmetric cells and Zn-MnO_(2) full cells with ZnSO_(4)+TEGDME electrolyte was tested by cyclic voltammetry(CV)and galvanostatic *** results show that the addition of TEGDME improves the surface wettability of the Zn anode and reduces the growth of dendrites through solvation structure modulation to suppress HER and zinc ***,TEGDME keeps the Zn anode to maintain a flat surface during charging and discharging,improving the reversibility of plating/*** cycle life of the Zn||Ti asymmetric cell was improved and the Coulombic efficiency was 100%after 100 *** Zn||Zn symmetric cells can be cycled stably for 1800 h at a current density of 1 mA/cm^(2) and a fixed capacity of 1 mA·h/cm^(2),while the capacity retention of the Zn-MnO_(2) full cell can be effectively improved from 51.46%to 68.29%at 100 *** using TEGDME electrolyte additives,the

关键词： Aqueous zinc ion battery Zinc dendrite Hydrogen evolution reaction Solvation structure Cycle life

Effective Density-Based Clustering Algorithms for Incomplete Data

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Big Data Mining and Analytics 2021年第3期4卷 183-194页

作者： Zhonghao Xue hongzhi wang USC Viterbi School of Engineering University of Southern CaliforniaLos AngelesCA 90007USA Department of Computer Science and Technology Harbin Institute of TechnologyHarbin 150001China

Density-based clustering is an important category among clustering algorithms. In real applications, many datasets suffer from incompleteness. Traditional imputation technologies or other techniques for handling missing values are not suitable for density-based clustering and decrease clustering result quality. To avoid these problems,we develop a novel density-based clustering approach for incomplete data based on Bayesian theory, which conducts imputation and clustering concurrently and makes use of intermediate clustering results. To avoid the impact of low-density areas inside non-convex clusters, we introduce a local imputation clustering algorithm, which aims to impute points to high-density local areas. The performances of the proposed algorithms are evaluated using ten synthetic datasets and five real-world datasets with induced missing values. The experimental results show the effectiveness of the proposed algorithms.

关键词： density-based clustering incomplete data clustering algorihtm

Truth Discovery on Inconsistent Relational Data

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Tsinghua Science and Technology 2018年第3期23卷 288-302页

作者： Jizhou Sun Jianzhong Li Hong Gao hongzhi wang School of Computer Science and Technology Harbin Institute of Technology

In this era of big data, data are often collected from multiple sources that have different reliabilities, and there is inevitable conflict with respect to the various information obtained when it relates to the the same *** important task is to identify the most trustworthy value out of all the conflicting claims, and this is known as truth discovery. Existing truth discovery methods simultaneously identify the most trustworthy information and source reliability degrees and are based on the idea that more reliable sources often provide more trustworthy information,and vice versa. However, there are often semantic constrains defined upon relational database, which can be violated by a single data source. To remove violations, an important task is to repair data to satisfy the constrains,and this is known as data cleaning. The two problems above may coexist, but considering them together can provide some benefits, and to the authors knowledge, this has not yet been the focus of any research. In this paper, therefore, a schema-decomposing based method is proposed to simultaneously discover the truth and to clean the data, with the aim of improving accuracy. Experimental results using real world data sets of notebooks and mobile phones, as well as simulated data sets, demonstrate the effectiveness and efficiency of our proposed method.

关键词： inconsistent data truth discovery data cleaning

Efficient histogram-based range query estimation for dirty data

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Frontiers of Computer Science 2018年第5期12卷 984-999页

作者： Yan ZHANG hongzhi wang Long YANG Jianzhong LI Department of Computer Science and Technology Harbin Institute of Technology Harbin 150001 China

In recent years, data quality issues have attracted wide attentions. Data quality problems are mainly caused by dirty data. Currently, many methods for dirty data management have been proposed, and one of them is entity-based relational database in which one tuple represents an entity. The traditional query optimizations are not suitable for the new entity-based model. Then new query optimizations need to be developed. In this paper, we propose a new query selectivity estimation strategy based on histogram, and focus on solving the overestimation which traditional methods lead to. We prove our approaches are unbiased. The experimental results on both real and synthetic data sets show that our approaches can give good estimates with low error.

关键词： query estimation data quality histogram dirtydata management

Mining Conditional Functional Dependency Rules on Big Data

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Big Data Mining and Analytics 2020年第1期3卷 68-84页

作者： Mingda Li hongzhi wang Jianzhong Li the Department of Computer Science University of CaliforniaLos AnglesCA 90095USA the Department of Computer Science and Technology Harbin Institute of TechnologyHarbin 150000China

Current Conditional Functional Dependency(CFD)discovery algorithms always need a well-prepared training *** condition makes them difficult to apply on large and low-quality *** handle the volume issue of big data,we develop the sampling algorithms to obtain a small representative training *** design the fault-tolerant rule discovery and conflict-resolution algorithms to address the low-quality issue of big *** also propose parameter selection strategy to ensure the effectiveness of CFD discovery *** results demonstrate that our method can discover effective CFD rules on billion-tuple data within a reasonable period.

关键词： data mining conditional functional dependency big data data quality

Preparation of Fe_(3)O_(4) Film by in-situ Oxidative Hydrolysis on Chitosan

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Journal of Materials Science & Technology 2006年第3期22卷 329-332页

作者： Suwei YAO Zhaohui ZHAO Weiguo ZHANG hongzhi wang SUGIYAMA Laboratory of Surface Technology School of Chemical Engineering and Technology Tianjin UniversityTianjin 300072 China

The Fe3O4 films were prepared by in-situ oxidative hydrolysis on chitosan. The structures and characteristics of the prepared Fe3O4 films were investigated by X-ray diffractometry （XRD）, scanning electron microscopy （SEM）, atom force microscopy （AFM）, vibrating sample magnetometry （VSM） and thermogravimetric-differentia thermal analysis （TG-DTA）. The results show that, （1） the as-synthesized Fe3O4 films are pure Fe3O4 with cubic inverse spinel structure; （2） the network structured film can be obtained at lower temperature, and the compact particle film at higher temperature; （3） the prepared Fe3O4 films are super-paramagnetic, and the saturation magnetization is improved with increasing the reaction temperature, which is 49.03 emu/g at 80℃; （4） the temperature of phase transformation from Fe3O4 to a-Fe2O3 is about 495℃. Besides, the formation mechanism of Fe3O4 film was also proposed.

关键词： Fe3O4 film In-situ Oxidative hydrolysis Chitosan