USING FREQUENT PATTERN MINING ALGORITHMS IN TEXT ANALYSIS
نویسندگان
چکیده
منابع مشابه
Algorithms for Frequent Pattern Mining - An Analysis
Data mining refers to extracting knowledge from large amounts of data. Frequent itemsets is one of the emerging task in data mining. Frequent itemsets mining is crucial and most expensive step in association rule mining. The problem of mining frequent itemsets arises in large transactional databases where there is need to find association rules among the transactional data for the growth of bus...
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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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This chapter will provide a detailed survey of frequent pattern mining algorithms. A wide variety of algorithms will be covered starting from Apriori. Many algorithms such as Eclat, TreeProjection, and FP-growth will be discussed. In addition a discussion of several maximal and closed frequent pattern mining algorithms will be provided. Thus, this chapter will provide one of most detailed surve...
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Integration of data mining and database management systems could significantly ease the process of knowledge discovery in large databases. We consider implementations of frequent itemset mining algorithms, in particular pattern-growth algorithms similar to the top-down FP-growth variations, tightly coupled to relational database management systems. Our implementations remain within the confines...
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ژورنال
عنوان ژورنال: Information System in Management
سال: 2017
ISSN: 2084-5537,2544-1728
DOI: 10.22630/isim.2017.6.3.5