| Author: | Fung, Wai-on David |
| Title: | Maintenance of discovered rules in a parallel environment |
| Degree: | M.Sc. |
| Year: | 1998 |
| Subject: | Data mining Hong Kong Polytechnic University -- Dissertations |
| Department: | Multi-disciplinary Studies |
| Pages: | iv, 85 leaves : ill. ; 30 cm |
| Language: | English |
| Abstract: | Nowadays, business is becoming more competitive and more complex. Though business analysts can utilize their data to perform the query in their mind, it is limited because of the query tool, or even the capability of the analyst. Moreover, efficiency is another concern of the analysts because of handling large amount of data and the performance requirements. Regarding this problem, data mining can be a solution. The goal of data mining is to extract significant patterns or interesting rules from large databases. However, mining large amount of data is a resource-intensive task. Parallel operation is one way to ease this problem. On the other hand, it is reasonable to believe that in most cases, data to be mined consecutively may have repetition to a great extent. Therefore, intelligent use of the previous mining results for subsequent mining purposes can improve the mining efficiency. In this dissertation, a new mining algorithm is proposed. Besides catering for the parallel mining operation, pre-processing before the actual mining by making use of previous mining results will be performed. This is done by building a clustering tree from the transactions for subsequent mining. The actual mining time required is expected to reduce significantly by making use of this clustering tree. |
| Rights: | All rights reserved |
| Access: | restricted access |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| b14259473.pdf | For All Users (off-campus access for PolyU Staff & Students only) | 2.52 MB | Adobe PDF | View/Open |
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