A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit Databases
Analyzing customer transactions to discover high-utility itemsets is a popular task, which consists of finding the sets of items that are purchased together and yield a high profit. However, many studies assume that transactional data is static while in real-life, it changes over time. For example,...
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2020-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/9087858/ |
| _version_ | 1819276451608788992 |
|---|---|
| author | Bay Vo Loan T.T. Nguyen Trinh D.D. Nguyen Philippe Fournier-Viger Unil Yun |
| author_facet | Bay Vo Loan T.T. Nguyen Trinh D.D. Nguyen Philippe Fournier-Viger Unil Yun |
| author_sort | Bay Vo |
| collection | DOAJ |
| description | Analyzing customer transactions to discover high-utility itemsets is a popular task, which consists of finding the sets of items that are purchased together and yield a high profit. However, many studies assume that transactional data is static while in real-life, it changes over time. For example, the unit profits of items may vary from one week to another because sale prices and production costs may change. Many algorithms for mining high-utility itemsets (HUI) ignore this important property and thus are inapplicable or generate inaccurate results on real data. To address this issue, this paper proposes a novel algorithm named Multi-Core HUI Miner (MCH-Miner). It adapts techniques introduced in the iMEFIM algorithm to run on a parallel multi-core architecture to efficiently mine HUIs in dynamic transaction databases. An empirical evaluation shows that in most cases, MCH-Miner is significantly faster than iMEFIM, and that the cost of database scans is reduced. |
| first_indexed | 2024-12-23T23:40:26Z |
| format | Article |
| id | doaj.art-7c19cf3c50964baba8d34bf0a4ef0a56 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-23T23:40:26Z |
| publishDate | 2020-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-7c19cf3c50964baba8d34bf0a4ef0a562022-12-21T17:25:41ZengIEEEIEEE Access2169-35362020-01-018858908589910.1109/ACCESS.2020.29927299087858A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit DatabasesBay Vo0https://orcid.org/0000-0002-2723-1138Loan T.T. Nguyen1https://orcid.org/0000-0001-6440-6462Trinh D.D. Nguyen2Philippe Fournier-Viger3https://orcid.org/0000-0002-7680-9899Unil Yun4https://orcid.org/0000-0002-3720-0861Faculty of Information Technology, Ho Chi Minh City University of Technology (HUTECH), Ho Chi Minh City, VietnamSchool of Computer Science and Engineering, International University, Ho Chi Minh City, VietnamInstitute of Research and Development, Duy Tan University, Da Nang, VietnamSchool of Humanities and Social Sciences, Harbin Institute of Technology, Shenzhen, ChinaDepartment of Computer Engineering, Sejong University, Seoul, South KoreaAnalyzing customer transactions to discover high-utility itemsets is a popular task, which consists of finding the sets of items that are purchased together and yield a high profit. However, many studies assume that transactional data is static while in real-life, it changes over time. For example, the unit profits of items may vary from one week to another because sale prices and production costs may change. Many algorithms for mining high-utility itemsets (HUI) ignore this important property and thus are inapplicable or generate inaccurate results on real data. To address this issue, this paper proposes a novel algorithm named Multi-Core HUI Miner (MCH-Miner). It adapts techniques introduced in the iMEFIM algorithm to run on a parallel multi-core architecture to efficiently mine HUIs in dynamic transaction databases. An empirical evaluation shows that in most cases, MCH-Miner is significantly faster than iMEFIM, and that the cost of database scans is reduced.https://ieeexplore.ieee.org/document/9087858/Data mininghigh utility itemsetdynamic profitparallelmultithread |
| spellingShingle | Bay Vo Loan T.T. Nguyen Trinh D.D. Nguyen Philippe Fournier-Viger Unil Yun A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit Databases IEEE Access Data mining high utility itemset dynamic profit parallel multithread |
| title | A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit Databases |
| title_full | A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit Databases |
| title_fullStr | A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit Databases |
| title_full_unstemmed | A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit Databases |
| title_short | A Multi-Core Approach to Efficiently Mining High-Utility Itemsets in Dynamic Profit Databases |
| title_sort | multi core approach to efficiently mining high utility itemsets in dynamic profit databases |
| topic | Data mining high utility itemset dynamic profit parallel multithread |
| url | https://ieeexplore.ieee.org/document/9087858/ |
| work_keys_str_mv | AT bayvo amulticoreapproachtoefficientlymininghighutilityitemsetsindynamicprofitdatabases AT loanttnguyen amulticoreapproachtoefficientlymininghighutilityitemsetsindynamicprofitdatabases AT trinhddnguyen amulticoreapproachtoefficientlymininghighutilityitemsetsindynamicprofitdatabases AT philippefournierviger amulticoreapproachtoefficientlymininghighutilityitemsetsindynamicprofitdatabases AT unilyun amulticoreapproachtoefficientlymininghighutilityitemsetsindynamicprofitdatabases AT bayvo multicoreapproachtoefficientlymininghighutilityitemsetsindynamicprofitdatabases AT loanttnguyen multicoreapproachtoefficientlymininghighutilityitemsetsindynamicprofitdatabases AT trinhddnguyen multicoreapproachtoefficientlymininghighutilityitemsetsindynamicprofitdatabases AT philippefournierviger multicoreapproachtoefficientlymininghighutilityitemsetsindynamicprofitdatabases AT unilyun multicoreapproachtoefficientlymininghighutilityitemsetsindynamicprofitdatabases |