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Data resampling method and device, storage medium and electronic device

A resampling and data technology, applied in the field of intelligence, can solve problems such as Matthew effect data sparsity, and achieve the effects of saving development time, improving usage efficiency, and strong pertinence

Inactive Publication Date: 2019-05-21
北京网众共创科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] Embodiments of the present invention provide a data resampling method and device, a storage medium, and an electronic device to at least solve the problems of the Matthew effect and data sparsity in the recommendation system in the related art

Method used

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  • Data resampling method and device, storage medium and electronic device
  • Data resampling method and device, storage medium and electronic device
  • Data resampling method and device, storage medium and electronic device

Examples

Experimental program
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Embodiment 1

[0024] The data resampling method embodiment provided in Embodiment 1 of the present application may be executed in a mobile terminal, a computer terminal or a similar computing device. Taking running on a mobile terminal as an example, figure 1 It is a block diagram of a hardware structure of a mobile terminal according to a data resampling method in an embodiment of the present invention. Such as figure 1 As shown, the mobile terminal 10 may include one or more ( figure 1 Only one is shown in the figure) a processor 102 (the processor 102 may include but not limited to a processing device such as a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the above-mentioned mobile terminal also A transmission device 106 for communication functions as well as input and output devices 108 may be included. Those of ordinary skill in the art can understand that, figure 1 The shown structure is only for illustration, and does not ...

Embodiment 2

[0063] In this embodiment, a data resampling device is also provided, which is used to execute the steps in any one of the above method embodiments, and the content that has been described will not be repeated here. image 3 is a structural block diagram of a data resampling device according to an embodiment of the present invention, such as image 3 As shown, the device includes:

[0064] The first determination module 30 is used to determine the probability distribution of the input data by calculating the frequency of occurrence of users or items in the input data; the second determination module 32 is used to determine the evaluation index and sparseness of the Matthew effect according to the probability distribution of the input data The evaluation index of the sparsity problem; the sampling module 34 is used to re-sample the input data according to the determined evaluation index of the Matthew effect and the evaluation index of the sparsity problem.

[0065] Through th...

Embodiment 3

[0070] An embodiment of the present invention also provides a storage medium, in which a computer program is stored, wherein the computer program is set to execute the steps in any one of the above method embodiments when running.

[0071] Optionally, in this embodiment, the above-mentioned storage medium may be configured to store a computer program for performing the following steps:

[0072] S1, determine the probability distribution of the input data by calculating the frequency of occurrence of users or items in the input data;

[0073] S2, determine the evaluation index of the Matthew effect and the evaluation index of the sparsity problem according to the probability distribution of the input data;

[0074] S3, resampling the input data according to the determined evaluation index of the Matthew effect and the evaluation index of the sparsity problem.

[0075] Optionally, the storage medium is also configured to store a computer program for performing the following ste...

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Abstract

The embodiment of the invention provides a data resampling method and device, a storage medium and an electronic device. The method comprises: determining probability distribution of input data by calculating the occurrence frequency of a user or an article in the input data; According to the probability distribution of the input data, determining an evaluation index of the matthew effect and an evaluation index of the sparsity problem; And re-sampling the input data according to the determined evaluation index of the matthew effect and the evaluation index of the sparsity problem. The problemthat a recommendation system in the prior art has the Mai Chi effect and the data sparsity is solved.

Description

technical field [0001] The present invention relates to the field of intelligent technology, in particular, to a data resampling method and device, a storage medium, and an electronic device. Background technique [0002] In recent years, with the vigorous development of the Internet, the recommendation system has attracted more and more attention. The recommendation system refers to the products and technologies that use the user's past data to discover items of interest to the user and recommend them to the user through data mining. The recommendation system has flourished for nearly 20 years and is widely used in various business fields such as e-commerce, news, video, etc. Major Internet companies at home and abroad have their own recommendation system strategies and reserves. The development in the field of recommender systems is manifested in the development and evolution of a series of algorithms. The earliest model of the recommendation system was collaborative fi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/2458G06F16/9535
Inventor 周循
Owner 北京网众共创科技有限公司
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