Author:
Han Meng,Cheng Haodong,Zhang Ni,Li Xiaojuan,Wang Le
Funder
National Natural Science Foundation of China
Natural Science Foundation of Ningxia Province
North Minzu University Innovation Project Fund
Publisher
Springer Science and Business Media LLC
Subject
Artificial Intelligence,Hardware and Architecture,Human-Computer Interaction,Information Systems,Software
Reference43 articles.
1. Liu Y, Liao W-K, Choudhary A (2005) A fast high utility itemsets mining algorithm. In: Proceedings of the 1st international workshop on utility-based data mining, pp 90–99. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/1089827.1089839
2. Agrawal R, Srikant R (1994) Fast algorithms for mining association rules. In: Proceedings of the 20th international conference on very large data bases, VLDB, vol 1215, pp 487–499. Morgan Kaufmann, San Francisco, CA. Citeseer
3. Tseng VS, Shie B-E, Wu C-W, Philip SY (2012) Efficient algorithms for mining high utility itemsets from transactional databases. IEEE Trans Knowl Data Eng 25(8):1772–1786. https://doi.org/10.1109/TKDE.2012.59
4. Dawar S, Goyal V (2015) Up-hist tree: an efficient data structure for mining high utility patterns from transaction databases. In: Proceedings of the 19th international database engineering and applications symposium, pp 56–61. Association for Computing Machinery, New York, NY, USA. https://doi.org/10.1145/2790755.2790771
5. Tseng VS, Wu C-W, Shie B-E, Yu PS (2010) Up-growth: an efficient algorithm for high utility itemset mining. In: Proceedings of the 16th ACM SIGKDD international conference on knowledge discovery and data mining, pp 253–262. Association for Computing Machinery, New York, NY, USA (2010). https://doi.org/10.1145/1835804.1835839
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