Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach
نویسندگان
چکیده
منابع مشابه
Discovery of Frequent Itemsets: Frequent Item Tree-Based Approach
Mining frequent patterns in large transactional databases is a highly researched area in the field of data mining. Existing frequent pattern discovering algorithms suffer from many problems regarding the high memory dependency when mining large amount of data, computational and I/O cost. Additionally, the recursive mining process to mine these structures is also too voracious in memory resource...
متن کاملEfficient Tree-based Discovery of Frequent Itemsets
Various types of data structures and algorithms have been proposed to extract frequently occurring patterns from a given data set. In particular, several tree structures have been devised to represent the input data set for efficient pattern discovery. One of the fastest frequent pattern mining algorithms known to date is the CATS algorithm, which can efficiently represent the whole data set an...
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Mining frequent patterns in large transactional databases is a highly researched area in the field of data mining. The different existing frequent pattern discovering algorithms suffer from various problems regarding the computational and I/O cost, and memory requirements when mining large amount of data. In this paper a novel approach is introduced for solving the aforementioned issues. The co...
متن کاملDiscovery of maximum length frequent itemsets
The use of frequent itemsets has been limited by the high computational cost as well as the large number of resulting itemsets. In many real-world scenarios, however, it is often sufficient to mine a small representative subset of frequent itemsets with low computational cost. To that end, in this paper, we define a new problem of finding the frequent itemsets with a maximum length and present ...
متن کاملA Patricia-Tree Approach for Frequent Closed Itemsets
In this paper, we propose an adaptation of the Patricia-Tree for sparse datasets to generate non redundant rule associations. Using this adaptation, we can generate frequent closed itemsets that are more compact than frequent itemsets used in Apriori approach. This adaptation has been experimented on a set of datasets benchmarks. Keywords—Datamining, Frequent itemsets, Frequent closed itemsets,...
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ژورنال
عنوان ژورنال: ITB Journal of Information and Communication Technology
سال: 2007
ISSN: 1978-3086
DOI: 10.5614/itbj.ict.2007.1.1.4