Fuzzy multiple-level sequential patterns discovery from customer transaction database
نویسندگان
چکیده
Sequential pattern discovery is a very important research topic in data mining and knowledge discovery and has been widely applied in business analysis. Previous works were focused on mining sequential patterns at a single concept level based on definite and accurate concept which may not be concise and meaningful enough for human experts to easily obtain nontrivial knowledge from the rules discovered. In this paper, we introduce concept hierarchies firstly, and then discuss a mining algorithm F-MLSPDA for discovering multiple-level sequential patterns with quantitative attribute based on fuzzy partitions.
منابع مشابه
Multiple-Level Sequential Pattern Discovery from Customer Transaction Databases
Mining sequential patterns from large customer transaction databases has been recognized as a key research topic in database systems. However, the previous works more focused on mining sequential patterns at a single concept level. In this study, we introduced concept hierarchies into this problem and present several algorithms for discovering multiple-level sequential patterns based on the hie...
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