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ABSTRACT
Title |
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Frequent Itemset mining over transactional data streams using Item-Order-Tree |
Authors |
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Pramod S., O.P. Vyas |
Keywords |
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Frequent Itemset, Freequent Itemset Mining ,
Online Data Mining, Item-Order-Tree |
Issue Date |
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November 2010 |
Abstract |
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The association rule mining is one of the
important area for research in data mining. In association
rule mining online association rule mining is one of the
hottest area due to the reason that the knowledge embedded
in the data stream is more likely to be changed as time goes
by. This paper proposes an algorithm as well as a data
structure for online data mining. In this method the pruning
in the data structure as well as the frequent itemset
generation will be based on the request. The data structure
which we introducing will have the capability to maintain
the transactions in the sorted order. Every transaction can be
extracted from the item-Order-Tree as by doing the traversal
in depth. Frequent itemset can be generated as by do the
traversal from the parent node that the user requested for.
This ItemOrder-Tree improves the performance of the
online association rule mining.
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Page(s) |
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2598-2601 |
ISSN |
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0975–3397 |
Source |
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Vol. 2, Issue.8 |
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