A New Algorithm for High Average-utility Itemset Mining
High utility itemset mining (HUIM) is a new emerging field in data mining which has gained growing interest due to its various applications. The goal of this problem is to discover all itemsets whose utility exceeds minimum threshold. The basic HUIM problem does not consider length of itemsets in it...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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Shahrood University of Technology
2019-11-01
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| Series: | Journal of Artificial Intelligence and Data Mining |
| Subjects: | |
| Online Access: | http://jad.shahroodut.ac.ir/article_1615_b5e5afeabe8fa37c144c1276d94ae3a1.pdf |
| _version_ | 1819018557719052288 |
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| author | A. Soltani M. Soltani |
| author_facet | A. Soltani M. Soltani |
| author_sort | A. Soltani |
| collection | DOAJ |
| description | High utility itemset mining (HUIM) is a new emerging field in data mining which has gained growing interest due to its various applications. The goal of this problem is to discover all itemsets whose utility exceeds minimum threshold. The basic HUIM problem does not consider length of itemsets in its utility measurement and utility values tend to become higher for itemsets containing more items. Hence, HUIM algorithms discover a huge enormous number of long patterns. High average-utility itemset mining (HAUIM) is a variation of HUIM that selects patterns by considering both their utilities and lengths. In the last decades, several algorithms have been introduced to mine high average-utility itemsets. To speed up the HAUIM process, here a new algorithm is proposed which uses a new list structure and pruning strategy. Several experiments performed on real and synthetic datasets show that the proposed algorithm outperforms the state-of-the-art HAUIM algorithms in terms of runtime and memory consumption. |
| first_indexed | 2024-12-21T03:21:19Z |
| format | Article |
| id | doaj.art-ced9aba8659e4acfa9d48ea8379b785a |
| institution | Directory Open Access Journal |
| issn | 2322-5211 2322-4444 |
| language | English |
| last_indexed | 2024-12-21T03:21:19Z |
| publishDate | 2019-11-01 |
| publisher | Shahrood University of Technology |
| record_format | Article |
| series | Journal of Artificial Intelligence and Data Mining |
| spelling | doaj.art-ced9aba8659e4acfa9d48ea8379b785a2022-12-21T19:17:42ZengShahrood University of TechnologyJournal of Artificial Intelligence and Data Mining2322-52112322-44442019-11-017453755010.22044/jadm.2019.7483.18931615A New Algorithm for High Average-utility Itemset MiningA. Soltani0M. Soltani1Dept. of Computer Engineering, University of Bojnord, Bojnord, Iran.Dept. of Computer Engineering, Quchan University of Technology, Quchan, Iran.High utility itemset mining (HUIM) is a new emerging field in data mining which has gained growing interest due to its various applications. The goal of this problem is to discover all itemsets whose utility exceeds minimum threshold. The basic HUIM problem does not consider length of itemsets in its utility measurement and utility values tend to become higher for itemsets containing more items. Hence, HUIM algorithms discover a huge enormous number of long patterns. High average-utility itemset mining (HAUIM) is a variation of HUIM that selects patterns by considering both their utilities and lengths. In the last decades, several algorithms have been introduced to mine high average-utility itemsets. To speed up the HAUIM process, here a new algorithm is proposed which uses a new list structure and pruning strategy. Several experiments performed on real and synthetic datasets show that the proposed algorithm outperforms the state-of-the-art HAUIM algorithms in terms of runtime and memory consumption.http://jad.shahroodut.ac.ir/article_1615_b5e5afeabe8fa37c144c1276d94ae3a1.pdfdata miningfrequent patternutilityhigh average-utility itemset |
| spellingShingle | A. Soltani M. Soltani A New Algorithm for High Average-utility Itemset Mining Journal of Artificial Intelligence and Data Mining data mining frequent pattern utility high average-utility itemset |
| title | A New Algorithm for High Average-utility Itemset Mining |
| title_full | A New Algorithm for High Average-utility Itemset Mining |
| title_fullStr | A New Algorithm for High Average-utility Itemset Mining |
| title_full_unstemmed | A New Algorithm for High Average-utility Itemset Mining |
| title_short | A New Algorithm for High Average-utility Itemset Mining |
| title_sort | new algorithm for high average utility itemset mining |
| topic | data mining frequent pattern utility high average-utility itemset |
| url | http://jad.shahroodut.ac.ir/article_1615_b5e5afeabe8fa37c144c1276d94ae3a1.pdf |
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