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A news recommendation method for data sparsity

A recommendation method and data sparse technology, applied in the field of recommendation, can solve the problems of sparse news broadcast score matrix and inaccurate business recommendation list, and achieve the effect of increasing the number of common scores, accurate recommendation, and accurate filling.

Active Publication Date: 2021-05-18
赣州柏朗科技有限公司
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  • Abstract
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  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

In the field of news recommendation, due to the huge amount of news on the website, but only a few users are willing to rate the news playback end they have been to, this results in a huge sparseness of the news listening user-news broadcast scoring matrix, resulting in The recommended list of merchants obtained is not accurate enough

Method used

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  • A news recommendation method for data sparsity
  • A news recommendation method for data sparsity
  • A news recommendation method for data sparsity

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Embodiment Construction

[0018] The technical solutions in the embodiments of the present invention will be described clearly and in detail below with reference to the drawings in the embodiments of the present invention. The described embodiments are only some of the embodiments of the invention.

[0019] The technical scheme that the present invention solves the problems of the technologies described above is:

[0020] Such as figure 1 Shown is a news recommendation method for solving data sparsity, which includes the following steps:

[0021] Receive a voice request for broadcasting news, filter the user's historical behavior data of the voice request, obtain information related to the news broadcast terminal and the news listening user, and obtain the news listening user-news broadcast scoring matrix, based on the screening result from the preset user Determine the target attribute item associated with the voice request in the attribute item set; and use the established news listening user-news ...

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Abstract

The present invention claims to protect a news recommendation method for solving data sparseness, which includes the following steps: receiving a voice request for broadcasting news, screening the user's historical behavior data of the voice request, and obtaining a news listening user-news broadcast scoring matrix , determine the target attribute item associated with the voice request from the preset user attribute item set based on the screening result; and construct a historical scoring record set for each news listening user and each news broadcast terminal, and construct a user set at the same time, according to Sorting the users in the user set from large to small according to the number of users’ rating news broadcast terminals; constructing the final similar user set, using the similar user set of the target user to fill the news listening user-news broadcast scoring matrix; the rest of the scoring matrix The unpopulated data is filled again by similar news broadcasting terminal, and the news broadcasting terminal makes a preliminary recommendation; the target news is screened out for recommendation. The invention can improve the accuracy of news recommendation.

Description

technical field [0001] The invention belongs to the technical field of recommendation, in particular to a news recommendation method for solving data sparseness. Background technique [0002] With the development of computer technology and the continuous accumulation of network data, artificial intelligence technology is developing rapidly. The news recommendation method for providing news services to users is a method of using electronic devices to actively recommend news to users, and is an information processing method that can simplify operations for users to obtain news and improve the efficiency of users in obtaining news. Different users have different demands and preferences for news information. In the traditional news recommendation method, when screening the news recommended for users, the timeliness of the news and the quality of the news content are usually considered, and the same recommendation results are output to different users, so different groups of peo...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06Q30/02G06F16/9535
CPCG06Q30/0201
Inventor 张晓瑜
Owner 赣州柏朗科技有限公司
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