Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 4
1063-1068

Sparse autoencoder community recognition algorithm based on smoothed l1 norm

Zhang Junxiang
Li Shuqin
Liu Bin
College of Information Engineering, Northwest A & F University, Yangling Shaanxi 712100, China
DOI: 10.19734/j.issn.1001-3695.2018.09.0743

Abstract

In the age of big data, it is increasingly difficult to make the community structure mining of large-scale complex networks by using the traditional community discovery algorithm and the accuracy rate is low. Therefore, this research came up with l1-ECDA, a community discovery algorithm for deep sparse self-encoder based on smooth l1 norm. This algorithm preprocessed the adjacency matrix of the network diagram with the method based on s jump. Then it established the deep sparse self-encoder based on smooth l1 norm and got the low dimensional characteristic matrix by training the similarity matrix of the network graph. Finally, it got the network community structure by clustering the low-dimensional feature matrix through the K-means algorithm. Experiments on simulated network and real network data set show that l1-ECDA improves the accuracy of community recognition effectively. Its accuracy rate is 4% higher than the DBCS algorithm on average, and is 5.4% higher than DeepWalk algorithm and CoDDA algorithm on average.

Foundation Support

陕西省重点研发计划资助项目(2017GY-197)
中国博士后科学基金资助项目(2017M613216)
陕西省自然科学基金资助项目(2017JM6059)
陕西省博士后基金资助项目(2016BSHEDZZ121)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.09.0743
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 4
Section: Algorithm Research & Explore
Pages: 1063-1068
Serial Number: 1001-3695(2020)04-021-1063-06

Publish History

[2020-04-05] Printed Article

Cite This Article

张军祥, 李书琴, 刘斌. 基于平滑l1范数的深度稀疏自动编码器社区识别算法 [J]. 计算机应用研究, 2020, 37 (4): 1063-1068. (Zhang Junxiang, Li Shuqin, Liu Bin. Sparse autoencoder community recognition algorithm based on smoothed l1 norm [J]. Application Research of Computers, 2020, 37 (4): 1063-1068. )

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.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)