Mining method, device and system of frequent item set

A technology of frequent itemset mining and frequent itemsets, applied in the field of big data, can solve problems such as time-consuming, and achieve the effect of improving efficiency

Inactive Publication Date: 2017-10-24
ADVANCED NEW TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] The embodiment of the present application provides a method for mining frequent itemsets to solve the problem in the prior art that it takes a lot of time to mine frequent itemsets in big data
[0009] The embodiment of the present application also provides a frequent item set mining device to s

Method used

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  • Mining method, device and system of frequent item set
  • Mining method, device and system of frequent item set
  • Mining method, device and system of frequent item set

Examples

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Embodiment 1

[0043] In order to solve the problem in the prior art that it takes a lot of time to mine frequent itemsets in big data, Embodiment 1 of the present application provides a frequent itemsets mining method. The execution subject of the method for mining frequent itemsets provided in the embodiment of the present application may be a server, for example, a server serving as a master node of a distributed computing system in a server cluster, and the like.

[0044] For the convenience of description, the implementation of the method will be introduced below by taking the server as the master node of the distributed computing system in the server cluster as an example to execute the method. It can be understood that the execution subject of the method being the server serving as the master node of the distributed computing system in the server cluster is only an exemplary description, and should not be understood as a limitation of the method.

[0045] The schematic diagram of the ...

Embodiment 2

[0087] Based on the aforementioned embodiment 1, the inventive concept of the present application has been described in detail. In order to facilitate a better understanding of the technical features, means and effects of the present application, the mining method of the frequent itemsets of the present application will be further described below, thus forming the present application. Yet another embodiment.

[0088] The mining process of frequent itemsets in Embodiment 2 of the present application is similar to the mining process of frequent itemsets described in Embodiment 1. Other steps not introduced in Embodiment 2 can refer to the relevant description in Embodiment 1, here No longer.

[0089] Before the implementation of the solution is introduced in detail, the implementation scenario of the solution is briefly introduced.

[0090] In this implementation scenario, the frequent itemsets in data d will be mined, the preset minimum support threshold is 40%, and the transa...

Embodiment 3

[0110] In order to solve the problem in the prior art that it takes a lot of time to mine frequent itemsets in big data, embodiment 3 of the present application provides a frequent itemsets mining device. The structural diagram of the frequent itemset mining device is as follows: Figure 7 As shown, it mainly includes the following functional units:

[0111] The slave node determination unit 31 is configured to, after receiving the frequent itemset mining task for the total data assigned by the client, perform data segmentation on the total data according to a predetermined data segmentation rule to obtain each sub-data;

[0112] The frequent itemset acquisition unit 32 of the sub-data is used to assign each sub-data to at least two slave nodes for parallel execution of the first-stage task of the frequent itemset mining task; the first-stage task specifically includes: the The slave node uses a frequent itemset mining algorithm to mine the assigned sub-data according to the ...

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Abstract

The invention discloses a mining method of a frequent item set. The mining method is used for solving the problem in the prior art that a plenty of time is consumed by mining the frequent item set in big data. The mining method of the frequent item set comprises the steps of carrying out data segmentation for total data to obtain each sub-data after a main node receives a frequent item set mining task which is appointed by a client and aims at the total data; distributing each sub-data to at least two slave nodes which are used for performing a first-stage task in parallel, wherein the first-stage task specifically comprises the sub-step of carrying out frequent item set mining for the distributed sub-data by utilizing the frequent item set mining algorithm to obtain a local frequent item set; and by the main node, distributing the frequent item set to each slave node which is used for performing a second-stage task in parallel, wherein the second-stage task comprises the sub-step of obtaining the frequent item set of the total data by each slave node which is used for performing the second-stage task. The invention also discloses a mining device of the frequent item set and a mining system of the frequent item set.

Description

technical field [0001] The present application relates to the field of big data, and in particular to a method, device and system for mining frequent itemsets. Background technique [0002] With the development of Internet technology, the data generated in the Internet may contain a lot of value. With more and more data generated in the network, how to quickly and effectively mine the value of the data generated in the Internet is a major problem in the era of big data. [0003] Data mining generally refers to the process of searching for information hidden in a large amount of data through algorithms. At present, the mining of association rules in data is a widely used data mining method in the field of data mining. Wherein, the association rule refers to the valuable association relationship between different items in the data. If an association rule satisfies the preset minimum support threshold and minimum disposition threshold, the association rule is considered to b...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/148G06F16/182
Inventor 胡辉谢黎文杨军刘义
Owner ADVANCED NEW TECH CO LTD
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