Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 39, 2022 No. 9
2745-2751

Task recommendation based on spatial-temporal information and task popularity analysis in mobile crowd sensing

Yang Guisong1a
Wang Jingru1a
Li Jun2
He Xingyu1b
1. a. School of Optical-Electrical & Computer Engineering, b. College of Communication & Art Design, University of Shanghai for Science & Technology, Shanghai 200093, China
2. National Industrial Information Security Development Research Center, Beijing 100040, China
DOI: 10.19734/j.issn.1001-3695.2022.01.0046

Abstract

The drawbacks of existing task recommendation in mobile crowd sensing were as follows: on the one hand, not fully considering the influence of spatial-temporal information on worker preference led to low accuracy of recommendation, on the other hand, ignoring the impact of task popularity on recommendation led to poor recommendation coverage. To solve these drawbacks, this paper proposed a novel task recommendation approach based on spatial-temporal information and task popularity analysis in mobile crowd sensing. Firstly, this approach made full use of the relevant information contained in the worker execution record(e. g., the time and location of worker performing tasks) to accurately predict the preference of worker for performing tasks. Secondly, in order to reduce the impact of popular tasks on recommendation coverage, this paper analyzed task popularity based on worker reputation and task execution record, and designed appropriate task popularity penalty factor. Then, combining worker preference and task popularity penalty factor, this paper provided an appropriate task recommendation list for each worker. Finally, the experimental results show that compared with the existing baseline methods, the proposed method improves the recommendation accuracy by 3.5% and the recommendation coverage by 25%.

Foundation Support

国家自然科学基金资助项目(61602305,61802257)
上海市自然科学基金资助项目(18ZR1426000,19ZR1477600)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2022.01.0046
Publish at: Application Research of Computers Printed Article, Vol. 39, 2022 No. 9
Section: Algorithm Research & Explore
Pages: 2745-2751
Serial Number: 1001-3695(2022)09-028-2745-07

Publish History

[2022-04-11] Accepted Paper
[2022-09-05] Printed Article

Cite This Article

杨桂松, 王静茹, 李俊, 等. 基于时空信息和任务流行度分析的移动群智感知任务推荐 [J]. 计算机应用研究, 2022, 39 (9): 2745-2751. (Yang Guisong, Wang Jingru, Li Jun, et al. Task recommendation based on spatial-temporal information and task popularity analysis in mobile crowd sensing [J]. Application Research of Computers, 2022, 39 (9): 2745-2751. )

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)