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News recommendation method and system based on user behavior detection and computer equipment

A behavioral and user-based technology, applied in the field of data analysis, can solve problems such as insufficient optimization capabilities and ignoring the production environment, and achieve the effects of speeding up mining, reducing running time, and avoiding useless calculations

Active Publication Date: 2019-11-22
CHONGQING UNIV OF POSTS & TELECOMM
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the traditional association rule method has insufficient optimization ability in terms of lift
In addition, many researchers ignore the real production environment, such as data mining tasks for growing data

Method used

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  • News recommendation method and system based on user behavior detection and computer equipment
  • News recommendation method and system based on user behavior detection and computer equipment
  • News recommendation method and system based on user behavior detection and computer equipment

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Embodiment Construction

[0023] The specific embodiments of the present invention will be described below to further illustrate the starting point and corresponding technical solutions of the present invention.

[0024] figure 1 It is a flow chart of a news recommendation method based on user behavior data detection provided by an embodiment of the present invention, which includes the following steps:

[0025] Step 101, converting the user behavior data to generate a processable user behavior data set;

[0026] The user behavior can be a user behavior generated when a user clicks on news while browsing news, that is, a user behavior that occurs when a user clicks on news, or a user behavior generated when a user searches for news keywords, or it can also be a user behavior that a user pays attention to or collects news, URLs, User behavior generated when an event or person occurs.

[0027] Preferably, the user behavior data is converted into integer data starting from 1 to N according to the order ...

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Abstract

The invention relates to a news recommendation method and system based on user behavior data detection and computer equipment. The method comprises the following steps of: converting the news click behavior data of the user; generating a processible user behavior data set; filtering non-frequent behaviors in the user behavior data set; obtaining a relative frequent item set by using a frequent item set serial mining algorithm; constructing a relatively frequent item set tree formed by a relatively frequent item set in the user behavior, finding out an optimal frequent item set; calculating thecomplete support degree of the optimal frequent item set in the user behaviors, generating association rules related to the user behavior frequent item set according to the complete support degree, and recommending news to users according to the association rules. The real production environment can be fully considered, a large number of user behavior data sets can be efficiently processed, and the method belongs to the technical field of data analysis.

Description

technical field [0001] The present invention relates to the technical field of data analysis, in particular to a news recommendation method, system and computer equipment based on user behavior data detection. Background technique [0002] News recommendation algorithm is a hot spot in new media research at present. In the early days of Internet development, popular recommendation methods for information were developed and widely used in websites such as Yahoo. In the current era of big data, personalized algorithm recommendation and information flow are the mainstream. With the development of communication technology and mobile Internet of Things, the scale of data is becoming larger and larger. Data mining can extract important information from large-scale data, and it is widely used in various fields, such as user behavior analysis, spatial prediction and network security detection. However, classical algorithms require a large amount of calculations for massive data, w...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9535G06F16/2458
CPCG06F16/9535G06F16/2465
Inventor 代劲郭亮夏鲁宏胡峰
Owner CHONGQING UNIV OF POSTS & TELECOMM
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