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ICAI
2003

Mining Generalized Sequential Patterns Using Genetic Programming

13 years 3 months ago
Mining Generalized Sequential Patterns Using Genetic Programming
We propose a new kind of sequential pattern which we call Generalized Sequential Pattern, and we introduce the problem of mining generalized sequential patterns over temporal databases. A classical sequential pattern consists of a sequence of itemsets. This kind of pattern can be discovered in a database of customer transactions where each transaction consists of a transaction-id, transaction time and the items bought in the transaction. On the other hand, our generalized sequential pattern consists of a sequence of SQL expressions and can be discovered in a large temporal database. We present the genetic algorithm SEG-GEN to solve the problem of mining generalized sequential pattern. We show that SEG-GEN performs better than the classical algorithm AprioriAll for mining simple sequential patterns where the minimum support threshold is low.
Sandra de Amo, Ary dos Santos Rocha Jr.
Added 31 Oct 2010
Updated 31 Oct 2010
Type Conference
Year 2003
Where ICAI
Authors Sandra de Amo, Ary dos Santos Rocha Jr.
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