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Data processing method and data processing device

A user, directed edge technology, applied in the field of data processing, can solve the problem of low similarity judgment accuracy, and achieve the effect of increasing accuracy, ensuring accuracy, and improving computing efficiency

Active Publication Date: 2017-06-09
NEUSOFT CORP
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  • Claims
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AI Technical Summary

Problems solved by technology

[0006] In view of this, the purpose of this application is to provide a data processing method to solve the problem of low accuracy in judging similarity in the prior art

Method used

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  • Data processing method and data processing device
  • Data processing method and data processing device
  • Data processing method and data processing device

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Embodiment Construction

[0061] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0062] Such as figure 1 Shown is a flow chart of Embodiment 1 of a data processing method provided by the present application, and the method includes the following steps:

[0063] Step S101: Obtain the user's access information, and construct the user's access path graph in the form of a directed graph according to the user's access information;

[0064] Wherein, the user access path graph includes nodes, directed edges, visits of nodes, and visits of direct...

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Abstract

The invention provides a data processing method. In the data processing method, a user access path diagram is constructed in a directed graph form according to access information of a user, the user access path diagram comprises nodes, directed edges, access amount of the nodes and the access amount of the directed edges, wherein each directed edge shows an access sequence of the two nodes connected with the directed edge, one initial node is selected from the user access path diagram as a starting point, all the nodes in the user access path diagram are passed, and weights of the directed edges are calculated and frequent items are determined; and similarity among users is calculated according to all the nodes in a preset queue, the access amount and the frequent items in the directed edges. The data processing method provided by the invention has the advantages that the directed edges in a user range path diagram are combined, sequence relation among articles is considered, similarity calculation dimensionality among different users is improved, improvement of similarity calculation accuracy can be facilitated, mean value of vectors in the dimensionality and fluctuation property are considered, compared with the traditional sparse matrix similarity calculation method, the calculation efficiency is greatly improved, and the accuracy of calculation result is also guaranteed.

Description

technical field [0001] The present application belongs to the technical field of data processing, and in particular relates to a data processing method and device. Background technique [0002] With the development of information technology, when users browse online information, the recommendation system can recommend corresponding items according to the user's preferences. [0003] Among them, the collaborative filtering algorithm is one of the most commonly used methods in the recommendation system. Its basic idea is that people with similar interests will like the same items, and similar items will also be liked by the same person. The most important thing is to calculate the relationship between users. , or the similarity between items. [0004] In the existing public calculation methods, the triplet of (user, item, preference) is generally used to construct a sparse matrix between user items, and then the traditional similarity calculation method, such as Cosine (cosin...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 孟令胜
Owner NEUSOFT CORP
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