Performance evaluation of approximate frequent pattern mining based on probabilistic technique
نویسندگان
چکیده
منابع مشابه
Approximate Frequent Pattern Mining
Frequent pattern mining has been a focused theme in data mining research and an important first step in the analysis of data arising in a broad range of applications. The traditional exact model for frequent pattern requires that every item occurs in each supporting transaction. However, real application data is usually subject to random noise or measurement error, which poses new challenges fo...
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Data mining on large relational databases has gained popularity and its significance is well recognized. However, the performance of SQL based data mining is known to fall behind specialized implementation since the prohibitive nature of the cost associated with extracting knowledge, as well as the lack of suitable declarative query language support. Frequent pattern mining is a foundation of s...
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Frequent pattern mining is an important data mining problem with broad applications. Although there are many in-depth studies on efficient frequent pattern mining algorithms and constraint pushing techniques, the effectiveness of frequent pattern mining remains a serious concern: it is non-trivial and often tricky to specify appropriate support thresholds and proper constraints. In this paper, ...
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This paper introduces a new algorithm for approximate mining of frequent patterns from streams of transactions using a limited amount of memory. The proposed algorithm consists in the computation of frequent itemsets in recent data and an effective method for inferring the global support of previously infrequent itemsets. Both upper and lower bounds on the support of each pattern found are retu...
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ژورنال
عنوان ژورنال: Journal of Korean Society for Internet Information
سال: 2013
ISSN: 1598-0170
DOI: 10.7472/jksii.2013.14.63