Abstract
In this paper, we give a general treatment for some kind of sequences such as customer sequences, document sequences, and DNA sequences, etc. Large collections of transaction, document, and genomic information have been accumulated in recent years, and embedded latently in it there is potentially significant knowledge for exploitation in the retailing industry, in information retrieval, in medicine and in the pharmaceutical industry, respectively. The approach taken here to the distillation of such knowledge is to detect strings in sequences which appear frequently, either within a given sequence (eg for a particular customer, document, or patient) or across sequences (eg from different customers, documents, or patients sharing a particular transaction, information retrieval, or medical diagnosis; respectively).
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Guan, J.W., Bell, D.A., Liu, D. (2004). Discovering Maximal Frequent Patterns in Sequence Groups. In: Tsumoto, S., Słowiński, R., Komorowski, J., Grzymała-Busse, J.W. (eds) Rough Sets and Current Trends in Computing. RSCTC 2004. Lecture Notes in Computer Science(), vol 3066. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-25929-9_74
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DOI: https://doi.org/10.1007/978-3-540-25929-9_74
Publisher Name: Springer, Berlin, Heidelberg
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