A fast method for frequent pattern discovery with secondary memory.

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  • Additional Information
    • Author-Supplied Keywords:
      big data
      Data mining
      frequent patterns
    • Abstract:
      Data mining technology has been widely studied and applied in recent years. Frequent pattern mining is one important technical field of such research. The frequent pattern mining technique is popular not only in academia but also in the business community. With advances in technology, databases have become so large that data mining is impossible because of memory restrictions. In this study, we propose a novel algorithm for Fast mining with Secondary Memory, abbreviated as FSM-Mining, to help improve this situation. FSM-Mining saves a part of the information that is not stored in the memory, and through the use of mixed hard disk and memory mining we are able to complete data mining with limited memory. The results of empirical evaluation under various simulation conditions show that FSM-Mining delivers excellent performance in terms of execution efficiency and scalability. [ABSTRACT FROM AUTHOR]
    • Abstract:
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    • Author Affiliations:
      1Department of Computer Science and Information Engineering, National Kaohsiung University of Applied Sciences, Kaohsiung, Taiwan
      2Department of Industrial Engineering and Management, National Chiao Tung University, Hsinchu, Taiwan
    • ISSN:
      1088-467X
    • Accession Number:
      10.3233/IDA-170876
    • Accession Number:
      122400924
  • Citations
    • ABNT:
      LIN, K. W. et al. A fast method for frequent pattern discovery with secondary memory. Intelligent Data Analysis, [s. l.], v. 21, p. S159–S176, 2017. Disponível em: . Acesso em: 18 out. 2019.
    • AMA:
      Lin KW, Sheng-Hao Chung, Ju-Chin Chen, Sheng-Shiung Huang, Chun-Cheng Lin. A fast method for frequent pattern discovery with secondary memory. Intelligent Data Analysis. 2017;21:S159-S176. doi:10.3233/IDA-170876.
    • APA:
      Lin, K. W., Sheng-Hao Chung, Ju-Chin Chen, Sheng-Shiung Huang, & Chun-Cheng Lin. (2017). A fast method for frequent pattern discovery with secondary memory. Intelligent Data Analysis, 21, S159–S176. https://doi.org/10.3233/IDA-170876
    • Chicago/Turabian: Author-Date:
      Lin, Kawuu W., Sheng-Hao Chung, Ju-Chin Chen, Sheng-Shiung Huang, and Chun-Cheng Lin. 2017. “A Fast Method for Frequent Pattern Discovery with Secondary Memory.” Intelligent Data Analysis 21 (March): S159–76. doi:10.3233/IDA-170876.
    • Harvard:
      Lin, K. W. et al. (2017) ‘A fast method for frequent pattern discovery with secondary memory’, Intelligent Data Analysis, 21, pp. S159–S176. doi: 10.3233/IDA-170876.
    • Harvard: Australian:
      Lin, KW, Sheng-Hao Chung, Ju-Chin Chen, Sheng-Shiung Huang & Chun-Cheng Lin 2017, ‘A fast method for frequent pattern discovery with secondary memory’, Intelligent Data Analysis, vol. 21, pp. S159–S176, viewed 18 October 2019, .
    • MLA:
      Lin, Kawuu W., et al. “A Fast Method for Frequent Pattern Discovery with Secondary Memory.” Intelligent Data Analysis, vol. 21, Mar. 2017, pp. S159–S176. EBSCOhost, doi:10.3233/IDA-170876.
    • Chicago/Turabian: Humanities:
      Lin, Kawuu W., Sheng-Hao Chung, Ju-Chin Chen, Sheng-Shiung Huang, and Chun-Cheng Lin. “A Fast Method for Frequent Pattern Discovery with Secondary Memory.” Intelligent Data Analysis 21 (March 2, 2017): S159–76. doi:10.3233/IDA-170876.
    • Vancouver/ICMJE:
      Lin KW, Sheng-Hao Chung, Ju-Chin Chen, Sheng-Shiung Huang, Chun-Cheng Lin. A fast method for frequent pattern discovery with secondary memory. Intelligent Data Analysis [Internet]. 2017 Mar 2 [cited 2019 Oct 18];21:S159–76. Available from: http://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=122400924&custid=s8280428