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Recommendation algorithm optimization method based on non-independent same distribution

A technology for recommending algorithms and optimization methods, applied in computing, data processing applications, forecasting, etc., can solve problems such as inaccurate analysis results, and achieve the effect of ensuring comprehensiveness

Pending Publication Date: 2021-04-23
LIAONING TECHNICAL UNIVERSITY
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  • Abstract
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  • Application Information

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Problems solved by technology

Therefore, the study found that if the coupling relationship is ignored, the analysis results will become inaccurate due to the loss of important information

Method used

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  • Recommendation algorithm optimization method based on non-independent same distribution
  • Recommendation algorithm optimization method based on non-independent same distribution
  • Recommendation algorithm optimization method based on non-independent same distribution

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Embodiment Construction

[0027] The specific implementation of the present invention will be described in detail below in conjunction with the accompanying drawings. As a part of this specification, the principles of the present invention will be described through examples. Other aspects, features and advantages of the present invention will become clear through the detailed description. 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.

[0028] see figure 1 , the present invention provides a recommendation algorithm optimization method based on non-IID, comprising the following steps:

[0029] data preprocessing

[0030] The group of values ​​based on the scoring time in the user scoring table is used as the detection standard for scoring outliers. First, calculate the rating time difference of the same user for different movies and the num...

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Abstract

The invention discloses a recommendation algorithm optimization method based on non-independent identical distribution. The recommendation algorithm optimization method comprises the steps: 1, data preprocessing: taking a set of values of scoring time in a user scoring table as detection standards of scoring abnormal values; 2, classifying of the attributes of the users: calculating entropy values of a calculation user attribute value group in which user attribute values appear, and taking the obtained comprehensive equipartition matrix as a finally obtained equipartition scoring matrix. According to the recommendation algorithm optimization method based on non-independent same distribution, the sparsity problem of the user scoring matrix is solved, the improved classification decision tree is used for classifying the user attributes to the users, and prediction is carried out through the scoring mean value matrix of the classified users.

Description

technical field [0001] The invention belongs to the technical field of learning recommendation methods, and in particular relates to a recommendation algorithm optimization method based on non-independent and identical distribution. Background technique [0002] With the rapid development of the information age, applications such as e-commerce and social networking have become the main branches of Internet information services. Since network users also become users and producers of network information when acquiring information, the number of users also determines the amount of network information. At the same time, the growth rate of user attributes and attribute values ​​is slower than that of the number of users. In order to prevent network information from exceeding the range that individuals or systems can accept, process or effectively use, and lead to failures. Therefore, in order to solve the occurrence of information overload, collaborative filtering recommendatio...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q10/04
CPCG06Q10/04
Inventor 郭鹏飞孙铭阳
Owner LIAONING TECHNICAL UNIVERSITY