張忠義老師的歷程檔案

期刊名稱	20070303--An Algorithm for Mining Strong Negative Fuzzy Sequential Patterns
資料日期	2007-03-03

[英文摘要] :
Many methods have been proposed for mining fuzzy
sequential patterns. However, most of conventional methods only
consider the occurrences of fuzzy itemsets in sequences. The fuzzy
sequential patterns discovered by these methods are called as positive
fuzzy sequential patterns. In practice, the absences of frequent fuzzy
itemsets in sequences may imply significant information. We call a
fuzzy sequential pattern as a negative fuzzy sequential pattern, if it
also expresses the absences of fuzzy itemsets in a sequence. In this
paper, we proposed a method for mining negative fuzzy sequential
patterns, called NFSPM. In our method, the absences of fuzzy itemsets
are also considered. Besides, only sequences with high degree of
interestingness can be selected as negative fuzzy sequential patterns.
An example was taken to illustrate the process of the algorithm
NFSPM. The result showed that our algorithm could prune a lot of
redundant candidates, and could extract meaningful fuzzy sequential
patterns from a large number of frequent sequences.