High Average-Utility Itemset Mining with A Novel Vertical Weak Upper Bound
High Average Utility Itemset (HAUI) mining (HAUIM) is an important task in data mining, as it has practical applications in diverse domains. To design efficient algorithms for HAUIM, researchers need to utilize upper bounds (UB) and weak upper bounds (WUB), along with corresponding pruning strategie...
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| Định dạng: | Conference paper |
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IEEE
2024
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| Truy cập trực tuyến: | https://scholar.dlu.edu.vn/handle/123456789/3528 |
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oai:scholar.dlu.edu.vn:123456789-35282024-07-09T08:14:45Z High Average-Utility Itemset Mining with A Novel Vertical Weak Upper Bound Trần, Thống Dương, Văn Hải Trương, Chí Tín High Average Utility Itemset (HAUI) mining (HAUIM) is an important task in data mining, as it has practical applications in diverse domains. To design efficient algorithms for HAUIM, researchers need to utilize upper bounds (UB) and weak upper bounds (WUB), along with corresponding pruning strategies, to early eliminate low average utility itemsets (LAUIs). This is necessary due to the fact that the average utility function fails to satisfy the anti-monotonic property. While many UBs and WUBs have been proposed so far, their values remain rather loose when compared to the average utility, leading to the limited efficiency of corresponding algorithms. To address this issue, this paper proposes a novel algorithm called MHAUI- TWUB, which efficiently discovers all HAUIs. The proposed algorithm introduces a novel vertical WUB named tvwaub, and employs an efficient pruning strategy to swiftly eliminate a significant … 2024-07-09T08:14:45Z 2024-07-09T08:14:45Z 2023-12 Conference paper Bài báo đăng trên KYHT quốc tế (có ISBN) https://scholar.dlu.edu.vn/handle/123456789/3528 vi 2023 RIVF International Conference on Computing and Communication Technologies (RIVF) IEEE |
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Thư viện Trường Đại học Đà Lạt |
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Thư viện số |
| language |
Vietnamese |
| description |
High Average Utility Itemset (HAUI) mining (HAUIM) is an important task in data mining, as it has practical applications in diverse domains. To design efficient algorithms for HAUIM, researchers need to utilize upper bounds (UB) and weak upper bounds (WUB), along with corresponding pruning strategies, to early eliminate low average utility itemsets (LAUIs). This is necessary due to the fact that the average utility function fails to satisfy the anti-monotonic property. While many UBs and WUBs have been proposed so far, their values remain rather loose when compared to the average utility, leading to the limited efficiency of corresponding algorithms. To address this issue, this paper proposes a novel algorithm called MHAUI- TWUB, which efficiently discovers all HAUIs. The proposed algorithm introduces a novel vertical WUB named tvwaub, and employs an efficient pruning strategy to swiftly eliminate a significant … |
| format |
Conference paper |
| author |
Trần, Thống Dương, Văn Hải Trương, Chí Tín |
| spellingShingle |
Trần, Thống Dương, Văn Hải Trương, Chí Tín High Average-Utility Itemset Mining with A Novel Vertical Weak Upper Bound |
| author_facet |
Trần, Thống Dương, Văn Hải Trương, Chí Tín |
| author_sort |
Trần, Thống |
| title |
High Average-Utility Itemset Mining with A Novel Vertical Weak Upper Bound |
| title_short |
High Average-Utility Itemset Mining with A Novel Vertical Weak Upper Bound |
| title_full |
High Average-Utility Itemset Mining with A Novel Vertical Weak Upper Bound |
| title_fullStr |
High Average-Utility Itemset Mining with A Novel Vertical Weak Upper Bound |
| title_full_unstemmed |
High Average-Utility Itemset Mining with A Novel Vertical Weak Upper Bound |
| title_sort |
high average-utility itemset mining with a novel vertical weak upper bound |
| publisher |
IEEE |
| publishDate |
2024 |
| url |
https://scholar.dlu.edu.vn/handle/123456789/3528 |
| _version_ |
1813142622046257152 |