Mining Association Rules in the Hypermarket with an RFID System
Date Issued
2006
Date
2006
Author(s)
Lo, Tzu-Wei
DOI
en-US
Abstract
When the RFID technique is becoming popular, we expect there will be a lot of applications based on it. Thus, we design an application in a hypermarket with an RFID system. We collect the shopping paths and items of customers, and find the RFSPIs (Relationship between Frequent Shopping paths and items). Therefore, in this thesis, we propose an algorithm to mine the RFSPIs. Our proposed method consists of two phases. First, we construct a mapping graph to record the information of a grid sensor structure and a transaction database. Second, we traverse the mapping graph in the DFS manner to find the RFSPIs. By using the mapping graph to mine the RFSPIs, we don’t generate unnecessary candidates, need fewer database scans, and properly utilize the characteristic of the problem that a sensor has at most four neighboring sensors. Therefore, our proposed method is more efficient than the PrefixSpan-based method. The experiment results show that our proposed method outperforms the PrefixSpan-based method by one order of magnitude.
Subjects
資料探勘
關聯法則
序列型樣
最大頻繁項目集合
頻繁購物路徑與頻繁商品集合的關聯法則
無線射頻識別技術
data mining
association rules
sequential patterns
maximal frequent itemset
RFSPI
RFID
Type
other
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