Published In
Journal of Quantum Information Science
Document Type
Article
Publication Date
3-2023
Subjects
Data Mining
Abstract
Maximum frequent pattern generation from a large database of transactions and items for association rule mining is an important research topic in data mining. Association rule mining aims to discover interesting correlations, frequent patterns, associations, or causal structures between items hidden in a large database. By exploiting quantum computing, we propose an efficient quantum search algorithm design to discover the maximum frequent patterns. We modified Grover’s search algorithm so that a subspace of arbitrary symmetric states is used instead of the whole search space. We presented a novel quantum oracle design that employs a quantum counter to count the maximum frequent items and a quantum comparator to check with a minimum support threshold. The proposed derived algorithm increases the rate of the correct solutions since the search is only in a subspace. Furthermore, our algorithm significantly scales and optimizes the required number of qubits in design, which directly reflected positively on the performance. Our proposed design can accommodate more transactions and items and still have a good performance with a small number of qubits.
Rights
Copyright © 2023 by author(s) and Scientific Research Publishing Inc. This work is licensed under the Creative Commons Attribution International License (CC BY 4.0). http://creativecommons.org/licenses/by/4.0/ Open Access
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DOI
10.4236/jqis.2023.131001
Persistent Identifier
https://archives.pdx.edu/ds/psu/41256
Citation Details
Alasow, A. and Perkowski, M. (2023) Quantum Algorithm for Mining Frequent Patterns for Association Rule Mining. Journal of Quantum Information Science, 13, 1-23. https://doi.org/10.4236/jqis.2023.131001
Erratum to “Quantum Algorithm for Mining Frequent Patterns for Association Rule Mining” [Journal of Quantum Information Science 13 (2023) 1-23]
Description
See additional file below -- Erratum to “Quantum Algorithm for Mining Frequent Patterns for Association Rule Mining” [Journal of Quantum Information Science 13 (2023) 1-23]
The original online version of this article (Abdirahman Alasow, Marek Perkowski (2023) Quantum Algorithm for Mining Frequent Patterns for Association Rule Mining. Journal of Quantum Information Science, 13, 1-23. https://doi.org/10.4236/jqis.2023.131001) unfortunately contains a mistake. The authors would like to clarify that Figure 11 and Figure 13 in our paper use a variant of diffusion quantum circuit that is not a standard Grover diffusion operator for the Boolean oracles and the phase oracles of L.K. Grover as presented in [1]-[3]. However, this variant of diffusion quantum circuit in those figures is the same as the quantum diffuser proposed by [4], which is the so-called “controlled-diffusion operator”.