计算机科学 ›› 2023, Vol. 50 ›› Issue (6A): 220100237-5.doi: 10.11896/jsjkx.220100237
杨恒, 朱焱
YANG Heng, ZHU Yan
摘要： 近年来学术领域逐渐积累了海量的数据,网络结构作为一种表示和分析大数据的有效方法,具有较丰富的维度且能够对现实生活中大量数据进行建模。Graph OLAP(图联机处理)技术继承了传统OLAP技术的相关思想,允许用户从不同角度与粒度对多维网络数据进行分析。然而现有的图OLAP技术大多围绕数据立方体的构建展开,相关操作大多都是传统OLAP技术在图数据上的简单扩展,并且构建的模型对网络自身的拓扑结构的挖掘能力较弱。为此,首先设计了学术网络星座模式和相关的图OLAP分析算法,更加明显地突出了学术网络的拓扑结构信息,提高了图OLAP的分析能力,其次提出了对应的物化策略,有效地提升了图OLAP分析的效率。
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| [1]QUEIROZ-SOUSA P O,SALGADO A C.A review onolap tech-nologies applied to information networks[J].ACM Transactions on Knowledge Discovery from Data(TKDD),2019,14(1):1-25. [2]KONG X,SHI Y,YU S,et al.Academic social networks:Mode-ling,analysis,mining and applications[J].Journal of Network and Computer Applications,2019,132:86-103. [3]CHEN C,YAN X,ZHU F,et al.Graph OLAP:Towards online analytical processing on graphs[C]//2008 Eighth IEEE International Conference on Data Mining.IEEE,2008:103-112. [4]QU Q,ZHU F,YAN X,et al.Efficient topological OLAP on information networks[C]//International Conference on Database Systems for Advanced Applications.Berlin:Springer,2011:389-403. [5]ZHAO P,LI X,XIN D,et al.Graph cube:on warehousing and OLAP multidimensional networks[C]//Proceedings of the 2011 ACM SIGMOD International Conference on Management of Data.2011:853-864. [6]WANG P,WU B,WANG B.TSMH Graph Cube:A novel frame-work for large scale multi-dimensional network analysis[C]//2015 IEEE International Conference on Data Science and Advanced Analytics(DSAA).IEEE,2015:1-10. [7]ZHANG Z,WU B,WU X,et al.Path-dimensional GraphOLAP parallel analysis framework for large-scale multidimensional networks[J].Journal of Software,2018,29(3):545-568. [8]SHI C,LI Y,ZHANG J,et al.A survey of heterogeneous information network analysis[J].IEEE Transactions on Knowledge and Data Engineering,2016,29(1):17-37. [9]WANG Y,YUAN Y,WANG G,et al.Graph cells:Top-k structural-textual aggregated query over information networks[J].Information Sciences,2020,547:354-366. [10]YIN M,WU B,ZENG Z.HMGraph OLAP:a novel framework for multi-dimensional heterogeneous network analysis[C]//Proceedings of the Fifteenth International Workshop on Data Warehousing and OLAP.2012:137-144. [11]ZHANG Z,WU B,WANG Z.A parallel framework for large-scale multidimensional heterogeneous network analysis[C]//Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017.2017:625-626. [12]YIN D,GAO H,ZOU Z,et al.Approximate iceberg cube on heterogeneous dimensions[C]//International Conference on Database Systems for Advanced Applications.Cham:Springer,2016:82-97. [13]YANG Heng,born in 1998,postgra-duate.His main research interests include academic social network data mi-ning and graph OLAP analysis. |
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