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Bipartite graph recommendation method based on differentiated resource allocation

A technology for resource allocation and recommendation methods, applied in special data processing applications, instruments, electrical digital data processing, etc., and can solve problems such as unreasonable initial resource settings

Active Publication Date: 2020-05-29
CHONGQING UNIV OF POSTS & TELECOMM +1
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004]This invention aims to solve the problem of unreasonable initial resource setting in traditional bipartite graph and the problem of adjusting resource allocation coefficient only by item degree and user degree

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  • Bipartite graph recommendation method based on differentiated resource allocation
  • Bipartite graph recommendation method based on differentiated resource allocation
  • Bipartite graph recommendation method based on differentiated resource allocation

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Embodiment Construction

[0054] 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.

[0055] The technical scheme that the present invention solves the problems of the technologies described above is:

[0056] In this embodiment, a recommendation method based on the joint community of users and ratings is performed as follows.

[0057] Step 1: Model the recommender system as a bipartite graph

[0058] The recommendation system is modeled as a bipartite graph, in which the two sets of nodes represent the user set U and the item set O respectively, and when the user selects an item, they are connected, that is, the two form an edge. One consists of n users U={u 1 ,u 2 … u n} and m items O = {o 1 ,o 2 ,...,o m} The bipartite graph composed of adjacency matrix A={a αi} n,m means that ...

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Abstract

The invention discloses a bipartite graph recommendation method based on differentiated resource allocation. Firstly, a recommendation system is modeled into a bipartite graph, and two sets of nodes represent a user set U and a project set O respectively; differentially setting project initial resources, correcting an initial score by using a score standardization and maximum and minimum value method, and quoting an Ebbinghaus forgetting function on the basis to quantify the influence brought by user'interest offset '; secondly, a user score similarity function and a user preference function are used for carrying out differentiated setting on the resource allocation coefficient, so that the resource flow is converted to be more reasonable; and finally, generating a recommendation list according to the size of the resources obtained by the project. The bipartite graph recommendation method is improved on the basis of a traditional bipartite graph recommendation method, differentiated setting is conducted on the project initial resources and the resource allocation coefficients, and the recommendation diversity can be improved while the recommendation accuracy is guaranteed.

Description

technical field [0001] The invention belongs to the field of personalized recommendation, specifically a bipartite graph recommendation method based on differentiated resource allocation. Background technique [0002] With the rapid development of communication information technology and the Internet, people have gradually entered the age of information excess from the age of information scarcity, resulting in the rapid development of recommendation systems that can meet user needs. Recommender systems are software tools and techniques that recommend desired items to users. The recommendations provided are intended to support the user through various decision-making processes, for example, what to buy, what song to listen to, or what news to read. The value of the recommendation system is to help users solve information overload and make better choices. It is also one of the most powerful and popular information discovery tools in the Internet field. The recommendation alg...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F16/9536G06F16/9535
CPCG06F16/9536G06F16/9535Y02D30/70
Inventor 张功国江洋李校林
Owner CHONGQING UNIV OF POSTS & TELECOMM