Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 36, 2019 No. 2
351-354

Maximal frequent itemset mining algorithm based on B-list

Zhang Chang1
Wen Kai1,2
Zheng Yunjun1
1. Institute of Applied Communication Technology, School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications, Chongqing 400065, China
2. Chongqing Information Technology Designing Co. Ltd. , Chongqing 401121, China
DOI: 10.19734/j.issn.1001-3695.2017.08.0873

Abstract

In order to solve the problems that existing in the maximal frequent itemset mining algorithms, such as the mining time is too long and the memory consumption is too large, this paper presented a maximal frequent itemset mining algorithm BMFI which employed B-list to mining frequent itemsets and employed the whole sequence search tree as the search space. Then, it used the parent equivalence pruning technique to reduce the search space. Finally, which combined with the MFI-tree-based projection strategy to achieve superset detection to improve the efficiency of the algorithm. The experimental results show that the performance of BMFI algorithm is superior to FPMAX algorithm and MFIN algorithm in terms of time efficiency and spatial efficiency. The proposed algorithm has good performance when mining the maximal frequent itemset in dense data set and sparse data set.

Publish Information

DOI: 10.19734/j.issn.1001-3695.2017.08.0873
Publish at: Application Research of Computers Printed Article, Vol. 36, 2019 No. 2
Section: Algorithm Research & Explore
Pages: 351-354
Serial Number: 1001-3695(2019)02-008-0351-04

Publish History

[2019-02-05] Printed Article

Cite This Article

张昌, 文凯, 郑云俊. 基于B-list的最大频繁项集挖掘算法 [J]. 计算机应用研究, 2019, 36 (2): 351-354. (Zhang Chang, Wen Kai, Zheng Yunjun. Maximal frequent itemset mining algorithm based on B-list [J]. Application Research of Computers, 2019, 36 (2): 351-354. )

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)