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Content-based mixed graph model image recommendation method

A recommendation method, a hybrid graph technology, applied in still image data retrieval, still image data indexing, special data processing applications, etc.

Active Publication Date: 2018-02-02
BEIJING UNIV OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

First of all, many methods cannot make full use of the information of social curation websites, but only use the relationship between users and items to make recommendations. However, social curation websites are characterized by allowing users to classify, share, like, comment, rate, follow, etc. Operations, especially Pinterest-like websites like Huapetal.com, are based on user interests and users organize information independently. Only using the relationship between users and pictures will waste a lot of useful information on Huapetal.com, and cannot fully model users

Method used

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Embodiment Construction

[0038] The purpose of the present invention is to provide a method for picture recommendation, the framework of which is as follows figure 1 shown. The present invention will be further described in detail below in conjunction with the accompanying drawings and specific examples.

[0039] The realization steps of this invention are as follows:

[0040] 1. Construction of hybrid graph model

[0041] The present invention adopts the data on the petal network of the social curation network to carry out picture recommendation work, and crawls users, petals, pictures, and various relationship information of the petal network. It includes 5,000 users, 200 drawing boards, 33,000 pictures, and about 100,000 connections. And use the data of the petal network to establish a mixed graph G=(V, E), where V is a set of vertices, and E is a set of edges. The vertex collection includes three kinds {V a , V b , V p},V u Represents the set of user vertices, V b Represents the collectio...

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Abstract

The invention discloses a content-based mixed graph model image recommendation method, and relates to the technical field of intelligent media computing and big data analysis. By utilizing data of multiple relational structures of a social curation website, various data relationships form a mixed graph model; and by fully utilizing data of a network, pictures are recommended to a user in combination with a random walk algorithm and content information of the pictures. The content information is combined with a mixed graph, so that the recommendation capability of a recommendation system can begreatly improved.

Description

technical field [0001] The invention relates to the technical field of intelligent media computing and big data analysis, in particular to a picture recommendation method. Specifically, it relates to a recommending method of a graph model formed by using users, drawing boards, pictures and their interaction relationship and picture content information. Background technique [0002] With the rapid development of information technology and the popularization of the Internet, the information on the Internet is growing explosively. In order to solve the problem of information overload caused by this, the recommendation system came into being. However, the problem of data sparsity and cold start has brought great challenges to the recommendation system. Social recommendation can partially solve the problem of data sparsity and cold start, and make personalized recommendation more effectively. Studies have shown that a user is more likely to know and like what his friends and fa...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06Q50/00
CPCG06Q50/01G06F16/51G06F16/583G06F16/9535
Inventor 毋立芳张磊简萌刘海英张岱祁铭超
Owner BEIJING UNIV OF TECH
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