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Teaching resource personalization recommendation method based on neural network

A technology of teaching resources and recommendation methods, applied in the field of personalized recommendation of resources, can solve problems such as cold start of new projects, and achieve the effect of solving cold start problems

Inactive Publication Date: 2013-10-16
DALIAN UNIV OF TECH
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  • Description
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AI Technical Summary

Problems solved by technology

[0005] 1) The content-based recommendation module makes recommendations based on the content and attributes of teaching resources, which can solve the problem of cold start of new projects;

Method used

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  • Teaching resource personalization recommendation method based on neural network
  • Teaching resource personalization recommendation method based on neural network
  • Teaching resource personalization recommendation method based on neural network

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Embodiment Construction

[0043] The personalized recommendation method for teaching resources includes at least the following modules:

[0044] 1) The content-based recommendation module makes recommendations based on the content and attributes of teaching resources, which can solve the problem of cold start of new projects;

[0045] 2) User-based collaborative filtering module: According to the user's score, download, browse the matrix to calculate the similarity between users, and then recommend the user;

[0046] 3) Project-based collaborative filtering module: calculate the similarity between teaching resources according to the user's scoring, downloading, and browsing matrix, and then recommend to the user;

[0047] 4) Neural network module: A common 1.5-layer feed-forward neural network composed of S-function neurons is used. Since the artificial neural network has a powerful dynamic nonlinear mapping capability, this module has a high ability to predict the user's preference for teaching resour...

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Abstract

The invention discloses a personalization recommendation method aiming at teaching resources, which at least comprises the following modules: 1) a content-based recommendation module: recommending through taking the content and the attributes of teaching resources as the basis to solve the cold start problem of a new project; 2) a user-based collaborative filtering module: downloading and browsing the similarity of matrix calculation users according to the user rating, and then recommending the users; 3) a project-based collaborative filtering module: downloading and browsing the similarity of teaching resources according to the user rating, and then recommending the users; 4) a neural network module: having strong dynamic nonlinear mapping capability and high precision and satisfaction on teaching resource recommending. The recommending effect is superior to the linear interpolation singly adopting the recommendation module or the recommendation results of the modules.

Description

technical field [0001] The invention relates to a method for personalized recommendation of resources, in particular to a method for personalized recommendation in a teaching resource system. Background technique [0002] In recent years, with the development of WEB2.0, the Internet has become a platform for data sharing, but it is accompanied by the problem of data explosion. Although search engines can help users find target information quickly, in many cases, users It is not clear what your needs are, or it is difficult to express your own needs, so a recommendation system based on the user's personal tastes and preferences is very necessary. This helps users switch from simple targeted data searches to more user-friendly information discovery. Nowadays, with the development of recommendation technology, recommendation system has been successfully applied to many WEB applications, and has achieved great success. The recommendation model is applied to more and more field...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 夏锋牛亚男孔祥杰
Owner DALIAN UNIV OF TECH
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