Mining fuzzy temporal association rules by item lifespans | |
---|---|
學年 | 104 |
學期 | 2 |
出版(發表)日期 | 2016-04-01 |
作品名稱 | Mining fuzzy temporal association rules by item lifespans |
作品名稱(其他語言) | |
著者 | Chun-Hao Chena; Guo-Cheng Lanb; Tzung-Pei Hong; Shih-Bin Lind |
單位 | |
出版者 | |
著錄名稱、卷期、頁數 | Applied Soft Computing 41, pp.265–274 |
摘要 | Data mining is the process of extracting desirable knowledge or interesting patterns from existing databases for specific purposes. In real-world applications, transactions may contain quantitative values and each item may have a lifespan from a temporal database. In this paper, we thus propose a data mining algorithm for deriving fuzzy temporal association rules. It first transforms each quantitative value into a fuzzy set using the given membership functions. Meanwhile, item lifespans are collected and recorded in a temporal information table through a transformation process. The algorithm then calculates the scalar cardinality of each linguistic term of each item. A mining process based on fuzzy counts and item lifespans is then performed to find fuzzy temporal association rules. Experiments are finally performed on two simulation datasets and the foodmart dataset to show the effectiveness and the efficiency of the proposed approach. |
關鍵字 | Fuzzy set;Fuzzy data mining;Fuzzy temporal association rule;Item lifespan |
語言 | en |
ISSN | 1568-4946 |
期刊性質 | 國外 |
收錄於 | SCI |
產學合作 | |
通訊作者 | |
審稿制度 | 否 |
國別 | NLD |
公開徵稿 | |
出版型式 | ,紙本 |
相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/112493 ) |