Abstract
The discovery of frequent patterns and their representations has attracted a lot of attention in the data mining community. An extensive research has been carried out mainly in discovering positive patterns. Recently, the generalized disjunction–free representation GDFLR of all frequent patterns both with and without negation has been proposed. There are cases, however, when a user is interested in patterns with a restricted number of negated items. In this paper, we offer the k-GDFLR representation as an adaptation of GDFLR, which represents all frequent patterns with at most k negated items. Algorithms discovering this representation are discussed as well. The experimental results show that k-GDFLR is more concise than GDFLR.
Research has been supported by grant No 3 T11C 002 29 received from Polish Ministry of Education and Science.
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Kryszkiewicz, M. (2006). Generalized Disjunction-Free Representation of Frequents Patterns with at Most k Negations. In: Ng, WK., Kitsuregawa, M., Li, J., Chang, K. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2006. Lecture Notes in Computer Science(), vol 3918. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11731139_54
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DOI: https://doi.org/10.1007/11731139_54
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