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A Personalized Web Page Recommendation Method Based on Multi-objective Evolutionary Algorithm

A multi-objective evolution and recommendation method technology, applied in the field of personalized web page recommendation, can solve the problems of performance damage of recommendation algorithms, and achieve the effects of improving efficiency, improving accuracy, improving precision and diversity

Active Publication Date: 2021-09-21
ANHUI UNIVERSITY
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

If this fact is ignored, the performance of the recommendation algorithm will suffer

Method used

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  • A Personalized Web Page Recommendation Method Based on Multi-objective Evolutionary Algorithm
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  • A Personalized Web Page Recommendation Method Based on Multi-objective Evolutionary Algorithm

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Embodiment Construction

[0040] refer to figure 1 , a kind of personalized web page recommendation method based on multi-objective evolutionary algorithm proposed by the present invention, comprising:

[0041] Step S1, obtain the webpage information S, and classify the webpage information according to the keywords to obtain the collection {q 1 ,q 2 ,...q m}, {q 1 ,q 2 ,...q m} includes n k A set of sample points, samples in the set of sample points assign the relevance label y of web page information according to the user click stream k .

[0042] In the specific plan, users use browsers every day, and there are various webpage information. Some people pay attention to entertainment gossip, some people like to watch sports events, some people pay attention to medical health, and some people pay attention to various commodity sales, etc. Wait. However, during the browsing process, users only click on the webpage information they are interested in. For example, star fans like to watch entertain...

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Abstract

The invention discloses a personalized webpage recommendation method based on a multi-objective evolutionary algorithm, comprising: S1, obtaining webpage information, and assigning the relevance of the webpage information according to the user's click flow, to obtain a set of related information S; S2, selecting from S Web page information features, and convert S into a second-class sample set according to the web page information features; S3, encode the relevant information set to obtain the parent population, and randomly initialize the parent population; S4, initialize the sub population based on the parent population; S5, Merge and evolve the parent population and sub-population; S6, repeat step S4 and step S5 to carry out next-generation inheritance, until the maximum genetic generation is reached to terminate the inheritance, and obtain the webpage recommendation prediction model; S7, predict the webpage information set through the webpage recommendation prediction model , to obtain the web page information that the user is interested in.

Description

technical field [0001] The invention relates to the technical field of webpage recommendation, in particular to a personalized webpage recommendation method based on a multi-objective evolutionary algorithm. Background technique [0002] With the application of Internet technology in daily life more and more widely, the amount of information that people face is growing at a crazy speed. People need to obtain the information they need from the outside world every day. How to find valuable information among the numerous information is a topic worth studying. [0003] Content-based recommendation, if you have browsed or purchased a certain type of information, it will recommend other information of this type to you. This recommendation method is modeled according to the user's interest preference, and the accuracy of the recommendation depends on the comprehensiveness and completeness of the information modeling. The advantage of content-based recommendation is that it is eas...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/9535G06N3/12
CPCG06N3/126
Inventor 程凡王栋梁郭伟
Owner ANHUI UNIVERSITY
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