Method of generating association rules from data stream and data mining system

Inactive Publication Date: 2009-02-26
GRIZZLY
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Benefits of technology

[0029]According to the invention, it is possible to effectively generate association rules from

Problems solved by technology

However, since the above algorithms need to search a large number of data sets and to manage each transaction information item, they are not suitable to search the frequent itemsets of a data stream.
However, these approaches for a finite set of transactions need to manage each transaction information item and to scan the data sets multiple times. Therefore, they are not suitable for finding frequent itemsets of a data stream.
Therefore, it is difficult to store all the elements in a separated limited space.
To satisfy these requirements, generally

Method used

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  • Method of generating association rules from data stream and data mining system
  • Method of generating association rules from data stream and data mining system
  • Method of generating association rules from data stream and data mining system

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Embodiment Construction

[0051]Exemplary embodiments of the present invention will now be described in detail with reference to the accompanying drawings. In the following description, a detailed description of known functions and configurations incorporated herein will be omitted for conciseness and clarity.

[0052]Before the description of the invention, first, symbols used in the invention are defined.

[0053]A data stream for mining frequent itemsets is an infinite set of continuously generated transactions, and can be defined as follows:

[0054]i) I={i1, i2, . . . , in} is a set of items that have ever been used as unit information in an application domain;

[0055]ii) When 2I, is the power set of I and eε(2I−{Ø}) is satisfied, e is called an itemset. The length |e| of the itemset indicates the number of items forming the itemset e, and an arbitrary itemset e is defined as an |e|-itemset depending on the length of the corresponding itemset. In general, a 3-itemset {a,b,c} is simply represented by abc;

[0056]iii) A

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Abstract

Disclosed is a method and data mining system for generating association rules from a data stream. An embodiment of the invention provides a method of generating association rules from a data stream, which is a non-limited data set composed of transactions continuously generated. The method includes: when itemsets included in the generated transactions and the counts of the itemsets are managed using a prefix tree and each node of the prefix tree has information on the count of a specific itemset corresponding to the node and a specific item, updating the information of a node corresponding to the itemset or adding a new node on the basis of the itemset included in the generated transaction and the count of the itemset; comparing the support of the itemset corresponding to each of the nodes of the prefix tree with a minimum support, which is a predetermined threshold value, to select frequent itemsets; and visiting all or some of the nodes corresponding to the selected frequent itemsets, and generating the association rule on the basis of the information of each of the visited nodes.

Description

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Claims

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Application Information

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Owner GRIZZLY
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