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Hadoop cloud platform-based Web resource personalized recommendation system and method

A recommendation system and cloud platform technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of huge data volume and difficult calculation process.

Inactive Publication Date: 2017-03-15
ANHUI UNIVERSITY
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Problems solved by technology

However, in real life, due to the large amount of data, the calculation process is very difficult, and we cannot easily obtain the results we need

Method used

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  • Hadoop cloud platform-based Web resource personalized recommendation system and method
  • Hadoop cloud platform-based Web resource personalized recommendation system and method
  • Hadoop cloud platform-based Web resource personalized recommendation system and method

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Embodiment Construction

[0125] Such as Figure 1-Figure 5 as shown, Figure 1-Figure 5 A personalized recommendation system based on Hadoop cloud platform Web resources proposed by the present invention.

[0126] refer to Figure 1-Figure 5, the personalized recommendation system based on Hadoop cloud platform Web resources that the present invention proposes, comprises:

[0127] The user model module is used to collect the browsing behavior information of the user on the web resource page, and calculate the user's interest in the above web resource page according to the above browsing behavior information of the user;

[0128] The recommendation algorithm module, according to the degree of interest calculated by the user model module, uses the recommendation algorithm to cluster the collected user browsing behavior information on the Web resource page to obtain the clustering results, and then constructs a matrix based on the above clustering results, and then passes Analyze the matrix constructe...

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Abstract

The invention discloses a Hadoop cloud platform-based Web resource personalized recommendation system and method. The system comprises a user model module which collects browsing behavior information of a user on a Web resource page, endows different weights to different behavior types of the user according to the browsing behavior information of the user on the Web resource page, and calculates the degree of interest of the user in the Web resource page according to the different weights, a recommendation algorithm module which carries out clustering processing on the collected browsing behavior information of the user on the Web resource page by using a recommendation algorithm according to the degree of interest calculated by the user model module, then constructs a matrix according to a clustering result, carries out nearest neighbor analysis on a target resource through the constructed matrix to obtain a nearest neighbor result of the target resource, and forecasts and fuses the degree of interest of the user according to the nearest neighbor result to obtain a recommendation scheme, and a parallel processing module which carries out off-line distributed calculation on the recommendation algorithm under a Hadoop cloud platform, and saving a calculation result.

Description

technical field [0001] The invention relates to the technical field of resource recommendation systems, in particular to a Hadoop cloud platform-based Web resource personalized recommendation system and method. Background technique [0002] With the rapid development of the Internet, the web resources in the network are growing explosively. Users are often at a loss when faced with such a large number of resources, and it takes a lot of time to find the information they want. As an important means of information filtering, personalized recommendation is an effective way to solve the current information overload problem, so it is necessary to make appropriate personalized recommendations for users. However, in real life, due to the large amount of data, the calculation process is very difficult, and we cannot easily obtain the results we need. The emergence of cloud computing technology provides us with a good method, so that we can better use the distributed computing envir...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 张以文王祥如郭星严远亭刘政怡
Owner ANHUI UNIVERSITY
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