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News recommendation method used for solving data sparsity

A recommendation method and data sparse technology, applied in the recommendation field, can solve problems such as inaccurate merchant recommendation lists and sparse news broadcast scoring matrix, and achieve the effects of increasing the number of common scores, accurate recommendation, and accurate similarity calculation

Active Publication Date: 2018-11-23
赣州柏朗科技有限公司
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  • Summary
  • Abstract
  • Description
  • 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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  • News recommendation method used for solving data sparsity
  • News recommendation method used for solving data sparsity
  • News recommendation method used for solving 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 invention requests for protecting a news recommendation method used for solving data sparsity. The method comprises the following steps of receiving a voice request for playing news, screening historical user behavior data of the voice request, acquiring a matrix of news listening users and news playing scores, and determining a target attribute item associated with the voice request from a preset user attribute item set based on a screening result; building a historical news record set for each news listening user and each news playing terminal, simultaneously building a user set, and sorting users in the user set in a descending order according to score news playing terminal numbers of the users; building a final similar user set, and filling the matrix of news listening users and news playing scores by using the similar user set of the target user; re-filling the residual unfilled data in the score matrix by using the similar news playing terminal, and preliminarily recommendingthe news playing terminal; and screening the target news for recommending. According to the method provided by the invention, the news recommendation accuracy can be improved.

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 Applications(China)
IPC IPC(8): G06Q30/02G06F17/30
CPCG06Q30/0201
Inventor 张晓瑜
Owner 赣州柏朗科技有限公司
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