Tightening Upper Bounds to the Expected Support for Uncertain Frequent Pattern Mining
نویسندگان
چکیده
منابع مشابه
Tightening Upper Bounds to the Expected Support for Uncertain Frequent Pattern Mining
Due to advances in technology, high volumes of valuable data can be collected and transmitted at high velocity in various scientific and engineering applications. Consequently, efficient data mining algorithms are in demand for analyzing these data. For instance, frequent pattern mining discovers implicit, previously unknown, and potentially useful knowledge about relationships among frequently...
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Utility mining in data mining has recently been an emerging research issue due to its practical applications. In this paper, with the concept of projection technique, we propose an efficient algorithm for finding high utility itemsets in databases. In particular, an improved upper-bound strategy in the proposed algorithm is designed to further tighten the upper bounds of the utility values for ...
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There are number of existing algorithms proposed that mines frequent patterns from certain or precise data. But know a day’s demand of uncertain data mining is increased. There are many situations in which data are uncertain. For frequent pattern mining from uncertain data mainly two approaches are proposed that are level-wise approach and pattern-growth approach. Level-wise approach use the ge...
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Traditional methods use a single minimum support threshold to find out the complete set of frequent patterns. However, in real word applications, using single minimum item support threshold is not adequate since it does not reflect the nature of each item. If single minimum support threshold is set too low, a huge amount of patterns are generated including uninteresting patterns. On the other h...
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ژورنال
عنوان ژورنال: Procedia Computer Science
سال: 2014
ISSN: 1877-0509
DOI: 10.1016/j.procs.2014.08.113