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Maintenance of Erasable Itemsets for Product Deletion

Published: 16 July 2018 Publication History

Abstract

Mining erasable itemsets is a problem derived from production planning of manufacturing industry. Previous erasable-itemset mining methods only focused on static product databases. In this paper, we propose a method to solve the maintenance problem of erasable itemsets for product deletion. It partitions all the itemsets into four cases according to whether they are erasable in the original database and in the deleted products. Each case will take the corresponding process to reduce the number of times required for rescanning the original database. At last, experiments are made to verify the proposed approach.

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  • (2018)Reducing Database Scan in Maintaining Erasable Itemsets from Product Deletion2018 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2018.8621965(2627-2632)Online publication date: Dec-2018

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    cover image ACM Other conferences
    MISNC '18: Proceedings of the 5th Multidisciplinary International Social Networks Conference
    July 2018
    177 pages
    ISBN:9781450364652
    DOI:10.1145/3227696
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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    Publication History

    Published: 16 July 2018

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    Author Tags

    1. FUP algorithm
    2. data mining
    3. erasable-itemset
    4. maintenance

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    • (2018)Reducing Database Scan in Maintaining Erasable Itemsets from Product Deletion2018 IEEE International Conference on Big Data (Big Data)10.1109/BigData.2018.8621965(2627-2632)Online publication date: Dec-2018

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