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12th Iberian Conference on Information Systems and Technologies (CISTI)

作者： Van Erven, Gustavo C. G. Carvalho, Rommel Novaes de Holanda, Maristela Terto Ralha, Celia Minist Transparencia Fiscalizacao & Controladoria Diretoria Pesquisas & Informacoes Estrateg Brasilia DF Brazil Univ Brasilia Dept Ciencia Comp Brasilia DF Brazil

ISBN: (纸本)9781509050475

Procurement is one of the main forms of acquisition of the Federal Government and are subject to fraud and corruption. In this context, many institutions such as the Brazilian Office of the Controller General try to identify fraud evidences, e.g., use of queries in databases with information about partnership of companies owned by the same group of people to simulate competition. However, many of these queries are manual or limited by the use of information systems databases. This paper explore the benefits of using graph NoSQL databases to identify the relationships between companies to detect fraud in procurement. A case study was carried out to validate the use of NoSQL databases using companies' partnership information based on queries defined by the CGU's auditors.

关键词： graph database Fraud Detection NoSQL Relational database

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graph database Indexing Layer for Logic-Based Tree Pattern Matching Over Intensional XML Document databases 18th

Graph Database Indexing Layer for Logic-Based Tree Pattern M...

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18th International Conference on Computational Science and Its Applications (ICCSA)

作者： Alrefae, Abdullah Cao, Jinli Pardede, Eric La Trobe Univ Dept Comp Sci & Informat Technol Melbourne Vic 3086 Australia

ISBN: (纸本)9783319951713;9783319951706

Most XML query evaluation approaches are based on the technique of tree pattern query matching (TPQ) to find similar occurrences of the query's path and conditions. Mainly, two types of constraints are matched to evaluate a given query, including hierarchical structure constraints and value-based constraints. However, TPQ technique falls short when it comes to matching the logic-based constraints and non-hierarchical relationships between nodes and entities in the XML document and database. In this paper, we overcome this shortage by providing an abstract graph database layer that provides a logic-based graph relational model to inspect and resolve the logics of the query to choose most relevant nodes in the XML document. Only the subtrees of the relevant nodes will be traversed in the document and the other subtrees will be skipped. We propose the application of graph database as an indexing layer that defines conceptual linking between database entities, beside logic-based assertions and constraints to evaluate XML queries over this layer to find most related entities and traverse only their related nodes in the XML document. In addition, we propose a mapping criteria and algorithm between XQuery and Cypher, which is a query language for Neo4j graph database.

关键词： Intensional XML Tree pattern query (TPQ) graph database Logic-based constraints Neo4j

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graph database and graph Computing for Cyber-Physical Power Systems 2

Graph Database and Graph Computing for Cyber-Physical Power ...

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2nd IEEE Conference on Energy Internet and Energy System Integration (EI2)

作者： Liu, Xinzhan Wang, Di Xu, Luo Guo, Qinglai Huang, Yu Wu, Zanhong Tsinghua Univ Guangdong Prov Power Dispatching & Control Ctr China Southern Power Grid Beijing 100084 Peoples R China Tsinghua Univ Dept Elect Engn State Key Lab Power Syst Beijing 100084 Peoples R China

ISBN: (纸本)9781538685495

Cyber-physical Power System (CPPS) presents a typical coupling graph structure composed of nodes and lines/links on both physical side and cyber side. With the rapid development of smart grids and coupling between cyber networks and physical networks, the CPPS network becomes larger and more complex. Since the natural graphic features of CPPS networks and its analysis methods are mostly inseparable from the graph theory, the application of graph computing systems and graph database will greatly help the analysis of CPPS problems. First, the representative graph computing systems are briefly introduced in this paper. And then, considering two-layer coupling structure of CPPS, the architecture consisting of the graph database and the graph computing system for CPPS is proposed.

关键词： Cyber-physical power system (CPPS) smart grid graph computing graph database

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Extending the Integrity Constraint Support in a graph database

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IEEE LATIN AMERICA TRANSACTIONS 2021年第4期19卷 604-611页

作者： Reina, Fabio Huf, Alexis Presser, Daniel Siqueira, Frank Univ Fed Santa Catarina Lab Pesquisa Sistemas Distribuidos LPeSD Florianopolis SC Brazil Univ Fed Santa Catarina Programa Grad Ciencia Comp PPGCC Florianopolis SC Brazil Univ Fed Santa Catarina Florianopolis SC Brazil

The large volume of data that has been produced every day has encouraged the development of new data storage technologies, including graph databases, which have experienced a growing adoption rate in recent years. On the other hand, the graph database management systems that are commercially available nowadays still lack means to ensure the consistency of stored data. In this scenario, this work proposes the extension of a graph database management system in order to add support for four new integrity constraints, allowing the definition of: conditions on node attributes, required edges, type of in/out nodes of an edge and edge cardinality. Support for these constraints was added to a modified version of OrientDB and experimental results show improvements in the performance of applications with integrity constraints.

关键词： IEEE transactions Nanoelectromechanical systems Monitoring Memory Indexes Data integrity Big Data data management graph database integrity constraints data integrity OrientDB

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Service composition based on pre-joined service network in graph database

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INTERNATIONAL JOURNAL OF WEB AND GRID SERVICES 2020年第4期16卷 422-440页

作者： Li, Jing Zhu, Ming Yu, Miao Yan, Yuhong Cui, Lizhen Shandong Univ Technol Sch Comp Sci & Technol Zibo 255000 Peoples R China Univ Lincoln Sch Comp Sci Lincoln LN6 7TS England Concordia Univ Dept Comp Sci & Software Engn Montreal PQ H3G 1M8 Canada Shandong Univ Artificial Intelligence Res C FAIR Joint SDU NTU Ctr Sch Software Jinan 250101 Peoples R China

To perform an arbitrary service composition task in a graph database, and to support plug-in semantic matching of services, we present a novel service composition approach in a graph database named pre-joined service network. Firstly, the proposed approach constructs and stores a composition network with all services and compositions in a graph database. Then, it fetches a satisfying solution by converting the user's request into queries in the graph database. To illustrate the process of searching for a solution, a simple but meaningful example is provided. Furthermore, we test the performance of the proposed approach with a challenge dataset. Experiment results show that the proposed approach can always find a valid solution and lead to higher user satisfaction when compared with the pre-joined semantic indexing graph approach.

关键词： graph database service composition QoS

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Managing 3D GIS Data for Indoor Environment Using Property graph database

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IEEE ACCESS 2023年 11卷 37216-37228页

作者： Jang, Hanme Yu, Kiyun Park, Seula Seoul Natl Univ Dept Civil & Environm Engn Seoul 08826 South Korea

With the diversification of three-dimensional (3D) urban space data sources and data collection methods, the Open Geospatial Consortium published 3D spatial data standards in Geography Markup Language (GML). Among them, IndoorGML is a data model for expressing the topological relationship between indoor spaces with advantages in terms of semantic information storage and navigation applications. Conversion into a suitable binary file must be accomplished to use the IndoorGML documents through integration with other data. This study proposes a method of generating graph database objects from the documents of IndoorGML to promote usability and interoperability. The labeled property graph model is designed to reflect IndoorGML's multilayered graph concept. Moreover, in the proposed graph model, the geometry of physical indoor spaces is segregated into separate surfaces. All elements from IndoorGML are managed with specific labels in Neo4j, the most dominant graph database. By applying the proposed method, the graph database is constructed using the officially distributed IndoorGML documents of three buildings. The number of generated graph objects is determined to confirm whether the IndoorGML features are accurately converted into graph database objects. Furthermore, the utility of the constructed graph database is verified through two scenario-based routing tests consisting of finding the optimal room with the lowest route cost and allocating indoor spaces for patrolling to outdoor security offices through indoor and outdoor data integration. In conclusion, this study confirms that the utility of IndoorGML can be promoted using a graph database system in data integration, data queries, and pathfinding applications while preserving data topology and interoperability.

关键词： databases Three-dimensional displays Data models Spatial databases Geometry Standards database systems graph database indoorGML indoor database property graph model 3D GIS data

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A novel deep learning method for query task execution time prediction in graph database

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FUTURE GENERATION COMPUTER SYSTEMS-THE INTERNATIONAL JOURNAL OF ESCIENCE 2020年 112卷 534-548页

作者： Chu, Zheng Yu, Jiong Hamdulla, Askar Xinjiang Univ Sch Informat Sci & Engn Urumqi 830046 Peoples R China

The execution time prediction for query tasks in graph database has become difficult and challenging due to the complexity of query plan and system. It is difficult for database Administrators (DBA) or database Management System (DBMS) to catch the accurate execution time during and before the execution of a query task. Before executing a query task, predicting its execution time can help the DBA or DBMS to efficiently management in the fields of load management, task scheduling, permission control, progress monitoring, system scale customization, etc. Therefore, accurately and efficiently predicting the execution time for query tasks is a key technology in these fields. In this paper, motivated by the combination of artificial intelligence technologies and graph database theories, we first propose a novel deep learning method to predict the execution time for query tasks in graph database. First, each query plan tree of tasks is encoded into an operation sequence. Second, top-20 features are selected from 68 candidate system features using random forest (RF), and the selected top-20 features are reduced to five principal components using principal component analysis (PCA). Finally, an accurate and efficient model based on the long short-term memory (LSTM) is designed and implemented to predict the execution time. The model can predict the execution time in advance before executing a query task in graph database. The experimental results from six kinds of benchmarks with the public data set Yelp show that the average accuracy of the proposed model can reach 81.34% with a high prediction efficiency rate, which proves the feasibility of the deep learning method. In particular, the proposed model can achieve the state-of-the-art prediction performance for query task execution time. (c) 2020 Published by Elsevier B.V.

关键词： Deep learning Execution time prediction Query task graph database

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High-Performance with an In-GPU graph database Cache

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IT PROFESSIONAL 2017年第6期19卷 58-64页

作者： Morishima, Shin Matsutani, Hiroki Keio Univ Dept Informat & Comp Sci Keio Japan

graph databases could represent complex network structures, but they currently underperform for this task. To improve performance for graph database queries, the authors propose caching the graph database in distribut... 详细信息

关键词： Cache Storage database Management Systems graph Theory graphics Processing Units Local Area Networks Query Processing Neo 4 J Social Logistics Networks Complex Network Structures Huge Network Structures In GPU graph database Cache 10 Gbit Ethernet Network graph database Queries Two Orders Of Magnitude Performance Improvement graphical Models databases graphical User Interfaces Complex Systems Structured Query Language GPU graph database No SQL

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Query Optimization Framework for graph database in Cloud Dew Environment

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Computers, Materials & Continua 2023年第1期74卷 2317-2330页

作者： Tahir Alyas Ali Alzahrani Yazed Alsaawy Khalid Alissa Qaiser Abbas Nadia Tabassum Department of Computer Science Lahore Garrison UniversityLahorePakistan Faculty of Computer Science and Information Systems Islamic University Madinah Madinah42351Saudi Arabia Networks and Communications Department College of Computer Science and Information TechnologyImam Abdulrahman Bin Faisal UniversityP.O.Box 1982Dammam31441Saudi Arabia Department of Computer Science Virtual University of PakistanLahorePakistan

The query optimizer uses cost-based optimization to create an execution plan with the least cost,which also consumes the least amount of *** challenge of query optimization for relational database systems is a combinatorial optimization problem,which renders exhaustive search impossible as query sizes *** in CPU performance have surpassed main memory,and disk access speeds in recent decades,allowing data compression to be used—strategies for improving database performance *** performance enhancement,compression and query optimization are the two most *** reduces the volume of data,whereas query optimization minimizes execution *** the database reduces memory requirement,data takes less time to load into memory,fewer buffer missing occur,and the size of intermediate results is more *** paper performed query optimization on the graph database in a cloud dew environment by considering,which requires less time to execute a *** factors compression and query optimization improve the performance of the *** research compares the performance of MySQL and Neo4j databases in terms of memory usage and execution time running on cloud dew servers.

关键词： Query optimization compression cloud dew decompression graph database

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TED⁺: Towards Discovering Top-k Edge-Diversified Patterns in a graph database

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IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING 2024年第5期36卷 2224-2238页

作者： Huang, Kai Cui, Yue Ye, Qingqing Zhao, Yan Zhao, Xi Tian, Yao Zheng, Kai Hu, Haibo Zhou, Xiaofang Macau Univ Sci & Technol Fac Innovat Engn Sch Comp Sci & Engn Taipa Macau Peoples R China Hong Kong Univ Sci & Technol Dept Comp Sci & Engn Kowloon Hong Kong Peoples R China Hong Kong Polytech Univ Dept Elect & Informat Engn Kowloon Hong Kong Peoples R China Aalborg Univ Dept Comp Sci DK-9220 Aalborg Denmark Univ Elect Sci & Technol China Sch Comp Sci & Engn Chengdu 610054 Peoples R China

With an exponentially growing number of graphs from disparate repositories, there is a strong need to analyze a graph database containing an extensive collection of small- or medium-sized data graphs (e.g., chemical compounds). Although subgraph enumeration and subgraph mining have been proposed to bring insights into a graph database by a set of subgraph structures, they often end up with similar or homogenous topologies, which is undesirable in many graph applications. To address this limitation, we propose the Top-k Edge-Diversified Patterns Discovery problem to retrieve a set of subgraphs that cover the maximum number of edges in a database. To efficiently process such query, we present a generic and extensible framework called Ted(+) which achieves a guaranteed approximation ratio to the optimal result. Three optimization strategies are further developed to improve the performance, and a lightweight version called TEDLITE is designed for even larger graph databases. Experimental studies on real-world datasets demonstrate the superiority of Ted(+ )to traditional techniques.

关键词： Edge-Diversified patterns graph database subgraph enumeration subgraph mining

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