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Incremental data set-oriented knowledge discovery method and discovery device

A technology of knowledge discovery and incremental data, applied in visual data mining, structured data retrieval, electronic digital data processing, etc., can solve the problem that new knowledge is difficult to be discovered in time and accurately

Pending Publication Date: 2021-06-08
CHINA UNIV OF PETROLEUM (EAST CHINA)
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Problems solved by technology

[0007] In order to solve the problem that it is difficult to discover new knowledge in a timely and accurate manner in the context of increasing data volume, the present invention provides a knowledge discovery method for incremental data sets. This method uses the EFPT-IKD algorithm to design a The tree-shaped data structure that is constantly growing and evolving—frequent pattern tree, setting the incremental window (IW) to find new frequent transaction items, the frequent pattern tree is mainly used to store frequent pattern information in the data set, through incremental Window and newly discovered frequent patterns, mining new knowledge in the incremental data set, and dynamically updating the new frequent patterns to the original frequent pattern tree, so that the frequent pattern tree evolves with the increase of the data set

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Embodiment Construction

[0028] In order to make the object, technical solution and advantages of the present invention clearer, the implementation manner of the present invention will be further described in detail below in conjunction with the accompanying drawings.

[0029] We use appeal hotline data from a province in China for testing. The experimental data is the appeal hotline data from July 11, 2016 to September 20, 2018, involving 64 major problem categories, with a total of 177,835 pieces of data.

[0030] We take the first 30,000 pieces of data from all the data in chronological order as the original data set DB. The average daily appeal hotline data in this province is 3,000 pieces (that is, incremental data), and it is known that the subsequent incremental data contains an emergency The process of occurrence, development, outbreak, and disappearance. In the experiment, the minimum support degree min_sup=5%, and the minimum confidence degree min_conf=20%.

[0031] Step 1, we preprocess t...

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Abstract

The embodiment of the invention provides an incremental data set-oriented knowledge discovery method and discovery device. According to the incremental data set-oriented knowledge discovery method and discovery device, an EFPT-IKD algorithm is used, a tree data structure-frequent pattern tree which can evolve continuously along with continuous increase of the data volume is designed, an incremental window (IW) is set to discover newly added frequent transaction items, the frequent pattern tree is mainly used for storing frequent pattern information in a data set, new knowledge in the incremental data set is mined through an incremental window and a newly discovered frequent pattern, and the newly added frequent pattern is dynamically updated into the original frequent pattern tree, so that the frequent pattern tree evolves continuously along with the increase of the data set. According to the technical scheme provided by the embodiment of the invention, the method and device can adapt to an application scene with continuously enlarged data volume, solves the problems of high time complexity and high space complexity faced by incremental data calculation, and has relatively high applicability to the application scene in which incremental data needs to be analyzed.

Description

technical field [0001] The invention relates to a knowledge discovery method, in particular to a knowledge discovery method and discovery device on an incremental data set. Background technique [0002] The Internet of Things, social networks, and the Internet constantly generate new data every moment, and these data need to be analyzed in time to mine their time-sensitive value. With the exponential growth of data volume, its sparsity is becoming more and more significant, and new knowledge and event information are often submerged in a large amount of data. How to extract valuable information and discover various hidden potential relationships among things, including causality, co-variation, coexistence, etc., is a difficult problem in knowledge discovery related research. [0003] Aiming at the ever-increasing data, many researchers use incremental computing to realize data analysis and mining. [0004] One type of algorithm is an incremental computing method based on a...

Claims

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Application Information

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IPC IPC(8): G06F16/25G06F16/26G06F40/216
CPCG06F16/25G06F16/26G06F40/216
Inventor 刘昕郑亮席永轲曹帅于绍文石祥沛
Owner CHINA UNIV OF PETROLEUM (EAST CHINA)
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