Technology of Network & Communication
|
App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 2
499-501,537

Method on dense-blocks detection in tensor data

Fan Weijun
Cheng Yanyun
College of Automation, Nanjing University of Posts & Telecommunications, Nanjing 310023, China
DOI: 10.19734/j.issn.1001-3695.2017.08.0866

Abstract

Past studies have shown that dense blocks in real-world tensor have anomalous or fraudulent behavior such as zombie followers' behavior or network attack. Thus, various methods have been used for detecting dense blocks in tensor. How-ever, these methods have low accuracy or low recall rate. To overcome those limitations, this paper proposed DDB-BST, which was a method on dense blocks detection based on binary tree search which finds the block with the highest metric in tensor by local search. By comparing key values between child's and father's nodes, it judged whether the binary tree grows. Finally, when the binary tree stop growing, all the child nodes are dense blocks. It mathematically proves the end condition of binary tree growing. Experiments on both synthesis data and real-world data show efficiency of the method, the F1 value with DDB-BST being 30 percent higher than for M-zoom.

Foundation Support

国家自然科学基金资助项目(61573194)
江苏省自然科学基金青年项目(BK20150851)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.08.0866
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 2
Section: Technology of Network & Communication
Pages: 499-501,537
Serial Number: 1001-3695(2019)02-039-0499-03

Publish History

[2019-02-05] Printed Article

Cite This Article

范卫俊, 程艳云. 张量数据中的多密集块检测方法 [J]. 计算机应用研究, 2019, 36 (2): 499-501,537. (Fan Weijun, Cheng Yanyun. Method on dense-blocks detection in tensor data [J]. Application Research of Computers, 2019, 36 (2): 499-501,537. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

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