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Algorithm Research & Explore
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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 2
385-389

FP-Growth-based user temporal association control habits mining method for smart home

Liang Tiankaia
Zeng Bia
Liu Jianqib
a. School of Computer, b. School of Automation, Guangdong University of Technology, Guangzhou 510006, China
DOI: 10.19734/j.issn.1001-3695.2018.07.0527

Abstract

Concern the problem that the traditional association analysis algorithms cannot efficiently and accurately mine the user's potential temporal association control habits which are implied in the user's operation records, this paper proposed a novel user temporal association control habits mining method based on FP-Growth. This method included three stages: to generate the transaction set, the temporal frequent item set, and the final temporal association control habits via the user operation-action forest, the improved FP-Growth algorithm and a time constraint rule. Finally, the comparative experiments by using the real user control records show that this method can improve the efficiency of transaction set generation and can more accurately discover the user's temporal association habits of smart home devices.

Foundation Support

国家自然科学基金青年基金资助项目(61701122)
广东省产学研重大专项资助项目(2016B010108004)
广州市重点科技项目(201604020016)
广东省产学研专项资助项目(2014B090904080)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2018.07.0527
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 2
Section: Algorithm Research & Explore
Pages: 385-389
Serial Number: 1001-3695(2020)02-014-0385-05

Publish History

[2020-02-05] Printed Article

Cite This Article

梁天恺, 曾碧, 刘建圻. 基于FP-Growth的智能家居用户时序关联操控习惯挖掘方法 [J]. 计算机应用研究, 2020, 37 (2): 385-389. (Liang Tiankai, Zeng Bi, Liu Jianqi. FP-Growth-based user temporal association control habits mining method for smart home [J]. Application Research of Computers, 2020, 37 (2): 385-389. )

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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