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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Vincent To-Yee Ng Jacky Man-Lee Wong Bao, P. |
| Copyright Year | 2001 |
| Description | Author affiliation: Dept. of Comput., Hong Kong Polytech. Univ., China (Vincent To-Yee Ng) |
| Abstract | Introducing data compression concept to large databases has been proposed for many years. In this project, we propose a new algorithm for the compression of large databases. Our goal is to optimize the I/O effort for finding association rules. The algorithm partitions the databases into two parts and all transactions will be compressed with the help of a reference transaction found in the small partition. We also compared the proposed compression algorithms with a normal compression algorithm - the binary compression. Empirical evaluation shows that the proposed algorithm performs well both in reducing the storage space and the I/O process required to find the large item sets for association rules. |
| Sponsorship | Int. Fuzzy Syst. Assoc. |
| Starting Page | 441 |
| Ending Page | 446 |
| File Size | 407777 |
| Page Count | 6 |
| File Format | |
| ISBN | 0780370783 |
| DOI | 10.1109/NAFIPS.2001.944293 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2001-07-25 |
| Publisher Place | Canada |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Relational databases Transaction databases Association rules Compression algorithms Data compression Partitioning algorithms Itemsets Performance evaluation Frequency Compressors |
| Content Type | Text |
| Resource Type | Article |
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