A data mining approach to database compression
| Autor: | Jau-Ji Shen, Chin-Feng Lee, S. Wesley Changchien, Wei-Tse Wang |
|---|---|
| Rok vydání: | 2006 |
| Předmět: |
Information retrieval
Computer Networks and Communications View Computer science Database schema computer.software_genre Database design Database tuning Database testing Theoretical Computer Science Database theory Data mining computer Software Intelligent database Information Systems Database model |
| Zdroj: | Information Systems Frontiers. 8:147-161 |
| ISSN: | 1572-9419 1387-3326 |
| DOI: | 10.1007/s10796-006-8777-x |
| Popis: | Data mining can dig out valuable information from databases to assist a business in approaching knowledge discovery and improving business intelligence. Database stores large structured data. The amount of data increases due to the advanced database technology and extensive use of information systems. Despite the price drop of storage devices, it is still important to develop efficient techniques for database compression. This paper develops a database compression method by eliminating redundant data, which often exist in transaction database. The proposed approach uses a data mining structure to extract association rules from a database. Redundant data will then be replaced by means of compression rules. A heuristic method is designed to resolve the conflicts of the compression rules. To prove its efficiency and effectiveness, the proposed approach is compared with two other database compression methods. |
| Databáze: | OpenAIRE |
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