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Subgraph Matching: Past and Present(子图匹配:前世与今生)
日期:2021-05-11编辑:信科院 科研办

报告人:林学民教授,澳大利亚新南威尔士大学计算机科学与工程学院

报告时间:2021年5月12 上午10:00到11:00

报告地点:软件大楼624

报告摘要:

Graph data are key parts of Big Data and widely used for modelling complex structured data with a broad spectrum of applications. Over the last decade, tremendous research efforts have been devoted to many fundamental problems in managing and analysing graph data.  In this talk, I will focus on a fundamental problem, subgraph matching. I will cover solutions for single computer, as well as distributed solutions.

  图形数据是大数据的重要组成部分,广泛应用于复杂结构化数据的建模,具有广泛的应用前景。在过去的十年中,在管理和分析图形数据的许多基本问题上,人们进行了大量的研究工作。在本次演讲中,将重点讨论一个基本问题:子图匹配;将介绍单台计算机的解决方案,以及分布式解决方案。

 

报告人简介: 

Xuemin Lin is a UNSW distinguished Professor - Scientia Professor, and the head of database and knowledge research group in the school of computer science and engineering at UNSW. Xuemin is a distinguished visiting Professor at Tsinghua University and visiting Chair Professor at Fudan University. He is a fellow of IEEE. Xuemin's research interests lie in databases, data mining, algorithms, and complexities. Specifically, he is working in the areas of scalable processing and mining of large scale data, including graph, spatial-temporal, streaming, text and uncertain data.

Xuemin currently serves as the editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (Jan 2017 - now). He was an associate editor of ACM Transactions Database Systems (2008-2014) and IEEE Transactions on Knowledge and Data Engineering  (Feb 2013- Jan 2015), and an associate editor-in-Chief of IEEE Transactions on Knowledge and Data Engineering (2015-2016), respectively.  He has been regularly serving as a PC member and area chairs/SPC in SIGMOD, VLDB, ICDE, ICDM, KDD, CIKM, and EDBT. He is a PC co-chair of ICDE2019 and VLDB2022.


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