An Efficient Approach for Mining Reliable High Utility Patterns
Utility mining is one of the most thriving research topics with a wide range of real-world applications. High utility pattern mining uses a utility function to extract all desired patterns that exceed a minimum utility threshold. However, a significant number of patterns will be generated if this th...
| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2022-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9664557/ |
| _version_ | 1798035261470277632 |
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| author | Mohammed A. Fouad Wedad Hussein Sherine Rady Philip S. Yu Tarek F. Gharib |
| author_facet | Mohammed A. Fouad Wedad Hussein Sherine Rady Philip S. Yu Tarek F. Gharib |
| author_sort | Mohammed A. Fouad |
| collection | DOAJ |
| description | Utility mining is one of the most thriving research topics with a wide range of real-world applications. High utility pattern mining uses a utility function to extract all desired patterns that exceed a minimum utility threshold. However, a significant number of patterns will be generated if this threshold is set too low, which is an inherent limitation of these algorithms. This may cause the mining process to be inefficient as it would be difficult to analyze the patterns found. Furthermore, most of these patterns are unreliable and hard to be employed in making decisions. This paper proposed a novel problem of mining reliable high utility patterns by adapting the concept of reliability to mine a significant type of pattern called reliable high utility patterns. To address this issue, an efficient approach named RUPM (Reliable Utility-based Pattern Mining) is presented. RUPM introduces three novel measurements for estimating the reliability of utility-based patterns and proposes several strategies to efficiently handle reliable patterns with high utility values. Experimental results suggest that up to 99% of the patterns discovered by existing traditional high utility pattern mining algorithms were, in fact, unreliable. In contrast, the average reliability proportion in the resultant patterns obtained from the RUPM approach is at least 47.6% higher. Moreover, the proposed pruning strategies provide a reduction in both the runtime and memory usage. |
| first_indexed | 2024-04-11T20:55:45Z |
| format | Article |
| id | doaj.art-8c95f3682239437ab573e61ac1c736ec |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-11T20:55:45Z |
| publishDate | 2022-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-8c95f3682239437ab573e61ac1c736ec2022-12-22T04:03:41ZengIEEEIEEE Access2169-35362022-01-01101419143110.1109/ACCESS.2021.31390289664557An Efficient Approach for Mining Reliable High Utility PatternsMohammed A. Fouad0https://orcid.org/0000-0003-4897-5352Wedad Hussein1Sherine Rady2https://orcid.org/0000-0003-4991-966XPhilip S. Yu3https://orcid.org/0000-0002-3491-5968Tarek F. Gharib4https://orcid.org/0000-0003-0780-782XInformation Systems Department, Faculty of Computer and Information Sciences, Luxor University, Luxor, EgyptInformation Systems Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, EgyptInformation Systems Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, EgyptDepartment of Computer Science, University of Illinois Chicago, Chicago, IL, USAInformation Systems Department, Faculty of Computer and Information Sciences, Ain Shams University, Cairo, EgyptUtility mining is one of the most thriving research topics with a wide range of real-world applications. High utility pattern mining uses a utility function to extract all desired patterns that exceed a minimum utility threshold. However, a significant number of patterns will be generated if this threshold is set too low, which is an inherent limitation of these algorithms. This may cause the mining process to be inefficient as it would be difficult to analyze the patterns found. Furthermore, most of these patterns are unreliable and hard to be employed in making decisions. This paper proposed a novel problem of mining reliable high utility patterns by adapting the concept of reliability to mine a significant type of pattern called reliable high utility patterns. To address this issue, an efficient approach named RUPM (Reliable Utility-based Pattern Mining) is presented. RUPM introduces three novel measurements for estimating the reliability of utility-based patterns and proposes several strategies to efficiently handle reliable patterns with high utility values. Experimental results suggest that up to 99% of the patterns discovered by existing traditional high utility pattern mining algorithms were, in fact, unreliable. In contrast, the average reliability proportion in the resultant patterns obtained from the RUPM approach is at least 47.6% higher. Moreover, the proposed pruning strategies provide a reduction in both the runtime and memory usage.https://ieeexplore.ieee.org/document/9664557/Data miningreliable high-utility itemsetutility miningpruning strategy |
| spellingShingle | Mohammed A. Fouad Wedad Hussein Sherine Rady Philip S. Yu Tarek F. Gharib An Efficient Approach for Mining Reliable High Utility Patterns IEEE Access Data mining reliable high-utility itemset utility mining pruning strategy |
| title | An Efficient Approach for Mining Reliable High Utility Patterns |
| title_full | An Efficient Approach for Mining Reliable High Utility Patterns |
| title_fullStr | An Efficient Approach for Mining Reliable High Utility Patterns |
| title_full_unstemmed | An Efficient Approach for Mining Reliable High Utility Patterns |
| title_short | An Efficient Approach for Mining Reliable High Utility Patterns |
| title_sort | efficient approach for mining reliable high utility patterns |
| topic | Data mining reliable high-utility itemset utility mining pruning strategy |
| url | https://ieeexplore.ieee.org/document/9664557/ |
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