Abstract
Efficient mining of high utility itemsets has become one of the most interesting data mining tasks with broad applications. In this paper, we proposed two efficient one-pass algorithms, MHUI-BIT and MHUI-TID, for mining high utility itemsets from data streams within a transaction-sensitive sliding window. Two effective representations of item information and an extended lexicographical tree-based summary data structure are developed to improve the efficiency of mining high utility itemsets. Experimental results show that the proposed algorithms outperform than the existing algorithms for mining high utility itemsets from data streams.
| Original language | English |
|---|---|
| Title of host publication | ICDM 2008: EIGHTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS |
| Publisher | IEEE |
| Pages | 88-+ |
| ISBN (Electronic) | 978-0-7695-3502-9 |
| ISBN (Print) | 978-0-7695-3502-9 |
| DOIs | |
| State | Published - 2008 |
| Event | 8th IEEE International Conference on Data Mining - Pisa, Italy Duration: 15 Dec 2008 → 19 Dec 2008 |
Publication series
| Name | IEEE International Conference on Data Mining |
|---|---|
| Publisher | IEEE |
| ISSN (Print) | 1550-4786 |
| ISSN (Electronic) | 1550-4786 |
Conference
| Conference | 8th IEEE International Conference on Data Mining |
|---|---|
| Country | Italy |
| City | Pisa |
| Period | 15/12/08 → 19/12/08 |
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Cite this
Li, H. F., Huang, H-Y., Chen, Y-C., Liu, Y-J., & Lee, S-Y. (2008). Fast and Memory Efficient Mining of High Utility Itemsets in Data Streams. In ICDM 2008: EIGHTH IEEE INTERNATIONAL CONFERENCE ON DATA MINING, PROCEEDINGS (pp. 88-+). (IEEE International Conference on Data Mining). IEEE. https://doi.org/10.1109/ICDM.2008.107