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Data flow clustering method and device based on density peak value

A data flow clustering and density peaking technology, which is applied in the fields of electrical digital data processing, special data processing applications, digital data information retrieval, etc., can solve problems such as clustering algorithms that cannot be processed effectively, so as to improve accuracy and ensure high efficiency sexual effect

Inactive Publication Date: 2019-08-23
UNIV OF JINAN
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

In addition, due to the inconsistency of the high-dimensional data in the data stream, it is inevitable that there will be mixed data, and the traditional clustering algorithm cannot be processed effectively. Therefore, HCLuStream, a data stream clustering algorithm oriented to mixed attributes, was proposed, making the clustering Algorithms are more adaptable to real data flow environments

Method used

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  • Data flow clustering method and device based on density peak value
  • Data flow clustering method and device based on density peak value
  • Data flow clustering method and device based on density peak value

Examples

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Embodiment 1

[0060] In order to realize full online data stream clustering and improve algorithm efficiency, according to one aspect of one or more embodiments of the present disclosure, a density peak-based data stream clustering method is provided.

[0061] Such as Figure 1-Figure 2 As shown, a data stream clustering method based on density peaks, the method includes:

[0062] A method for clustering data streams based on density peaks, the method comprising:

[0063] Step S1: receive the first batch of data stream data to be clustered, initialize parameters and data structures;

[0064] Step S2: Receive a new batch of data stream data to be clustered as new data, perform pre-clustering of new data, and attenuate the old data stream data;

[0065] Step S3: Merge a new batch of data stream data to be clustered with old data stream data and its data structure, and cluster the merged data, and the merged data becomes old data;

[0066] Step S4: Carry out the screening update of suspecte...

Embodiment 2

[0107] According to an aspect of one or more embodiments of the present disclosure, there is provided a computer-readable storage medium.

[0108] A computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor of a terminal device and executing the method for clustering data streams based on density peaks.

Embodiment 3

[0110] According to an aspect of one or more embodiments of the present disclosure, a terminal device is provided.

[0111] A terminal device, which includes a processor and a computer-readable storage medium, the processor is used to implement instructions; the computer-readable storage medium is used to store multiple instructions, and the instructions are suitable for being loaded by the processor and executing the described one A clustering method for data streams based on density peaks.

[0112] These computer-executable instructions, when executed in a device, cause the device to perform the methods or processes described in accordance with various embodiments in the present disclosure.

[0113] In this embodiment, a computer program product may include a computer-readable storage medium carrying computer-readable program instructions for performing various aspects of the present disclosure. A computer readable storage medium may be a tangible device that can retain and...

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Abstract

The invention discloses a data flow clustering method and device based on density peak values. A density peak value and a fuzzy clustering method are taken as the basis; the concept of suspected outliers is proposed for the first time; a width adaptive sampling window model and a space-time attenuation mechanism are used as main innovation points; a new data stream clustering method and device, namely a density peak value-based data stream clustering method and device, are innovatively provided by taking improvement of the efficiency of an algorithm for data stream clustering as a main targetand starting point, and a more efficient data stream clustering effect is obtained on the premise of ensuring considerable clustering precision.

Description

technical field [0001] The disclosure belongs to the technical field of data stream clustering, and relates to a density peak-based data stream clustering method and device. Background technique [0002] The statements in this section merely provide background information related to the present disclosure and do not necessarily constitute prior art. [0003] Today's world is in the fourth scientific and technological revolution dominated by advanced technologies such as artificial intelligence, machine learning, big data analysis, and virtual reality. The trend of the arrival of the intelligent age has been overwhelming, and all walks of life are actively joining the tide of intelligence , strive to improve production efficiency and competitiveness. [0004] Data is the raw material of this gluttonous feast in the intelligent age. Huge amounts of high-dimensional data contain rich information and knowledge. With the rapid development of personal terminal technology and netw...

Claims

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Application Information

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IPC IPC(8): G06K9/62G06F16/2455G06F16/2458
CPCG06F16/24568G06F16/2465G06F18/23213
Inventor 孙红卫张瑞杜韬王信堂许婧文朱连江
Owner UNIV OF JINAN
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