User clustering method and device

A user clustering and user technology, applied in the Internet field, can solve problems such as unsupervised, poor manual weight adjustment effect, low efficiency, etc., and achieve good clustering effect

Active Publication Date: 2015-12-09
无线生活(杭州)信息科技有限公司
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Problems solved by technology

[0002] User clustering is a common topic in recommendation systems. When using the kmeans algorithm for clustering, the existing technical solutions often rely on experience to empower user characteristics manually, and it is unsupervised, and the training set cannot be used to inform the model. which results are good
This manual weighting process is inefficient
It is necessary to repea

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  • User clustering method and device

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Embodiment Construction

[0049] The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

[0050] figure 1 Shown is a flowchart of a user clustering method in an embodiment of the present invention, as figure 1 As shown, including the following steps S10-S50:

[0051] Step S10, assigning the user to the user group closest to the user.

[0052] Step S20, calculate the value of the objective function of the user group according to the products browsed by the user and the preset objective function, and the objective function is used to indicate the similarity between the user groups for the products;

[0053] Step S30, judging whether the value of the objective function is less than or equal to a preset threshold;

[0054] Step S40, when the value of the ...

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Abstract

The invention discloses a user clustering method and device. The method comprises the steps of: distributing a user to a closest user group; according to goods browsed by the user and a preset objective function, and calculating the value of an objective function of the user group, wherein the objective function is used for indicating a similar degree between pointed goods among user groups; when the value of the objective function is smaller than or equal to a preset threshold, using all user groups as a clustering result; and when the value of the objective function is larger than the preset threshold, adjusting the weight of each identity attribute characteristic vector of the user according to a decreasing direction of the objective function, and re-distributing the user to the closest user group until the value of the objective function is smaller than or equal to the preset threshold. According to the technical scheme, unsupervised clustering is turned into supervised clustering, and the clustering result is better.

Description

technical field [0001] The invention relates to the technical field of the Internet, in particular to a user clustering method and device. Background technique [0002] User clustering is a common topic in recommendation systems. When using the kmeans algorithm for clustering, the existing technical solutions often rely on experience to empower user characteristics manually, and it is unsupervised, and the training set cannot be used to inform the model. Which results are good. This manual weighting process is inefficient. It is necessary to repeatedly adjust the weight according to the results; and the effect of manual weight adjustment is poor, and the effect depends on the experience of engineers; manual weight adjustment only supports a small number of feature dimensions, and the project cycle will increase with the increase of dimensions, and the dimension will increase to 10 Dimensions above, the project is not acceptable. Contents of the invention [0003] The pr...

Claims

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Application Information

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IPC IPC(8): G06K9/62
CPCG06F18/23213
Inventor 高云翔
Owner 无线生活(杭州)信息科技有限公司
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