Optimized Frequent Pattern Mining for Classified Data Sets
نویسندگان
چکیده
منابع مشابه
Optimized Frequent Pattern Mining for Classified Data Sets
Mining frequent patterns in data is a useful requirement in several applications to guide future decisions. Association rule mining discovers interesting relationships among a large set of data items. Several association rule mining techniques exist, with the Apriori algorithm being common. Numerous algorithms have been proposed for efficient and fast association rule mining in data bases, but ...
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A major challenge in frequent-pattern mining is the sheer size of its mining results. In many cases, a high min sup threshold may discover only commonsense patterns but a low one may generate an explosive number of output patterns, which severely restricts its usage. In this paper, we study the problem of compressing frequent-pattern sets. Typically, frequent patterns can be clustered with a ti...
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Frequent pattern mining is an essential data mining task, with a goal of discovering knowledge in the form of repeated patterns. Many efficient pattern mining algorithms have been discovered in the last two decades, yet most do not scale to the type of data we are presented with today, the so-called “Big Data”. Scalable parallel algorithms hold the key to solving the problem in this context. In...
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Discovering clusters in subspaces, or subspace clustering and related clustering paradigms, is a research field where we find many frequent pattern mining related influences. In fact, as the first algorithms for subspace clustering were based on frequent pattern mining algorithms, it is fair to say that frequent pattern mining was at the cradle of subspace clustering—yet, it quickly developed i...
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In recent years, data streams have emerged as a new data type that has attracted much attention from the data mining community. They arise naturally in a number of applications (Brian et al., 2002), including financial service (stock ticker, financial monitoring), sensor networks (earth sensing satellites, astronomic observations), web tracking and personalization (webclick streams). These stre...
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ژورنال
عنوان ژورنال: International Journal of Computer Applications
سال: 2010
ISSN: 0975-8887
DOI: 10.5120/504-821