In accordance with regulations and requirements, the editorial department's website domain has been changed to arocmag.cn. The original domain (arocmag.com) will be discontinued after Dec. 31st, 2024.
Algorithm Research & Explore
|
2907-2910

Method for tag recommendation of tensor decomposition based on multiple relationships

Zeng Hui
Hu Qiang
Gan Xiuxiu
College of Information Engineering, East China Jiaotong University, Nanchang 330013, China

Abstract

The exist methodd of tag recommendation ignore the connection among the characteristics of a variety of attributes and cannot guarantee the accuracy of the recommender system in the big data environment. Aiming at this problem, this paper proposed a tag recommendation method based on user clustering and tensor decomposition, which could further improve the quality of tag recommendation. The method firstly clustered the users who had an important influence on the product, and then comprehensively calculated the total weight based on the multiple relationships among the users, products, tags, and product ratings. Finally, it constructed the tensor according to the user groups after clustering and the total weight of the multivariate relations, and performed the tensor factorization. Experiment compared with the traditional tensor decomposition method, and the results show that proposed method improves the accuracy and verifies the effectiveness of the algorithm.

Foundation Support

国家自然科学基金资助项目(61562027)
江西省教育厅科学技术研究资助项目(GJJ170379)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.04.0215
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 10
Section: Algorithm Research & Explore
Pages: 2907-2910
Serial Number: 1001-3695(2019)10-005-2907-04

Publish History

[2019-10-05] Printed Article

Cite This Article

曾辉, 胡强, 淦修修. 基于多元关系的张量分解标签推荐方法 [J]. 计算机应用研究, 2019, 36 (10): 2907-2910. (Zeng Hui, Hu Qiang, Gan Xiuxiu. Method for tag recommendation of tensor decomposition based on multiple relationships [J]. Application Research of Computers, 2019, 36 (10): 2907-2910. )

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)