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An efficient algorithm for mining frequent weighted itemsets using interval word segments

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Abstract

Mining frequent weighted itemsets (FWIs) from weighted-item transaction databases has recently received research interest. In real-world applications, sparse weighted-item transaction databases (SWITDs) are common. For example, supermarkets have many items, but each transaction has a small number of items. In this paper, we propose an interval word segment (IWS) structure to store and process tidsets for enhancing the effectiveness of mining FWIs from SWITDs. The IWS structure allows the intersection of tidsets between two itemsets to be performed very fast. A map array is proposed for storing a 1-bit index for words. From the map array, 1-bits are mapped to create the tidset of an itemset for faster calculation of the weighted support of itemsets. Experimental results for a number of SWITDs show that the method based on IWS structure outperforms existing methods.

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Acknowledgments

This research is funded by Vietnam National Foundation for Science and Technology Development (NAFOSTED) under grant number 102.05-2015.10.

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Authors and Affiliations

  1. Department of Math & Informatics, University of People’s Security, Ho Chi Minh City, Vietnam

    Ham Nguyen

  2. Faculty of Information Technology, Ho Chi Minh City University of Technology, Ho Chi Minh, Vietnam

    Bay Vo

  3. School of Graduate Studies, Ha Noi National University, Hanoi, Vietnam

    Minh Nguyen

  4. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, T6R 2V4 AB, Canada

    Witold Pedrycz

  5. Department of Electrical and Computer Engineering, Faculty of Engineering, King Abdulaziz University, Jeddah, 21589, Saudi Arabia

    Witold Pedrycz

  6. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Witold Pedrycz

Authors
  1. Ham Nguyen
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  2. Bay Vo
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  3. Minh Nguyen
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  4. Witold Pedrycz
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Correspondence to Bay Vo.

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Nguyen, H., Vo, B., Nguyen, M. et al. An efficient algorithm for mining frequent weighted itemsets using interval word segments. Appl Intell 45, 1008–1020 (2016). https://doi.org/10.1007/s10489-016-0799-6

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  • DOI: https://doi.org/10.1007/s10489-016-0799-6

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