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App. Res. of Comp. Printed Article
Vol. 37, 2020 No. 9
2571-2578

Survey of high utility pattern mining over data streams

Wang Shaofeng
Han Meng
Jia Tao
Zhang Chunyan
Sun Rui
School of Computer Science & Technology, North Minzu University, Yinchuan 750021, China
DOI: 10.19734/j.issn.1001-3695.2019.03.0105

Abstract

The high utility pattern mining methods over data stream are based on the binary frequent pattern mining methods, and introduce the internal utility and external utility of the item. In the pattern mining process, it can consider the importance of the item to explore more valuable patterns. From the perspective of key window technologies, common methods and representations, this paper analyzed the high utility mining methods over data stream and summarized the related algorithms to study its characteristics, advantages, disadvantages and key problems. Specifically, this paper illustrated the common concepts of high utility pattern mining over data stream. It analyzed the key window technologies for processing data flow efficient mode, involving sliding, damped, landmark and titled window model. It researched one-phase and two-phase high utility pattern mi-ning methods over data stream and analyzed the representation of the high utility pattern, that was, the completed high utility pattern and the compressed high utility pattern. It introduced other high utility pattern mining methods over data stream, including sequence high utility pattern, hybrid high utility pattern and high average utility pattern, etc. Finally, this paper looked forward to the further research direction of high utility pattern mining methods over data stream.

Foundation Support

宁夏自然科学基金项目(2020AAC03216)
国家自然科学基金资助项目(61563001)
计算机应用技术自治区重点学科项目(PY1902)
宁夏高等学校一流学科建设(电子科学与技术学科(NXYKXY2017A07)
北方民族大学研究生创新项目(YCX18052)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.03.0105
Publish at: Application Research of Computers Printed Article, Vol. 37, 2020 No. 9
Section: Survey
Pages: 2571-2578
Serial Number: 1001-3695(2020)09-002-2571-08

Publish History

[2020-09-05] Printed Article

Cite This Article

王少峰, 韩萌, 贾涛, 等. 数据流高效用模式挖掘综述 [J]. 计算机应用研究, 2020, 37 (9): 2571-2578. (Wang Shaofeng, Han Meng, Jia Tao, et al. Survey of high utility pattern mining over data streams [J]. Application Research of Computers, 2020, 37 (9): 2571-2578. )

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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