Mining Negative Sequential Patterns in Transaction Databases

Sequential pattern is an important research topic in data mining and knowledge discovery. Sequential pattern is traditionally formed as (A, B) where A and B are frequent sequence in a transaction database. We extend this definition to include sequential patterns of forms (A, notB), (notA, B) and (notA, notB), which present negative sequential patterns among sequences. We call patterns of the form (A, B) positive sequential patterns, and patterns of the other forms negative patterns. Negative sequential patterns can also provide very useful insight view into the data set although they are different from positive ones. We put forward a discovery algorithm for mining negative sequential patterns from large transaction database in this paper.

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