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Information recommendation method and system

A technology for information recommendation and items, applied in the field of communication, can solve problems such as ignoring users' specific ratings on items, sparsity, and algorithm speed reduction, and achieve the effect of reducing data sparsity and improving recommendation quality

Inactive Publication Date: 2014-05-07
CHINA MOBILE GRP GUANGDONG CO LTD
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AI Technical Summary

Problems solved by technology

The existing personalized recommendation methods based on collaborative filtering have the following defects: (1) Scalability problem: the recommendation algorithm needs to be carried out in real time and can respond in the shortest possible time, and the scale of massive data will gradually increase. As a result, the speed of the algorithm drops sharply, and recommendations cannot be generated in time; (2) Sparsity, due to the large-scale number of products and the large number of users, and users generally only rate the products they are interested in, the information used to indicate user interests is limited
However, this method only considers the structural correlation between users and items to calculate the degree of association between nodes, while ignoring the similarity between users and items, and ignoring the specific ratings of users on items. Instead, only user-item dependencies are considered

Method used

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  • Information recommendation method and system
  • Information recommendation method and system

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Embodiment Construction

[0025] In order to make the technical problems, technical solutions and advantages to be solved by the present invention clearer, the following will describe in detail with reference to the drawings and specific embodiments.

[0026] Such as figure 1 As shown, it is a flowchart of an information recommendation method of an embodiment provided by the present invention, including the following steps:

[0027] Step S101: Process the user, item and user's rating on the item into a bipartite graph, the user and the item correspond to nodes on the bipartite graph, and the user's rating to the item corresponds to an edge on the bipartite graph.

[0028] Step S102: Determine the similarity between the target user and other users according to the user's rating of the item.

[0029] Step S103: Use the vector composed of the similarity between the target user and other users as a restart vector, and calculate the correlation between the target user and the item based on a restartable ra...

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Abstract

The invention provides an information recommendation method and system. The method includes processing users, items and grades of the items and from the users into a bipartite graph; determining the similarity between a target user and other users according to the grades of the items and from the users; utilizing vector composed of the similarity of the target user and other users as a restarting vector and calculating relevancy between the target user and the items based on a restartable random walk model; selecting information that the items correspond to and recommending the information to the target user according to the relevancy. According to the information recommendation method, the relevancy between the target user and other users is determined according to the grades of the items and from the users, the relevancy between user nodes and item nodes is completely excavated, the data sparse problem effect is greatly reduced, the grade items that the users are interested in can be accurately recommended, and the recommendation quality is improved.

Description

technical field [0001] The present invention relates to the field of communication technology, in particular to an information recommendation method and system. Background technique [0002] Personalized recommendation can learn users' interests and hobbies by collecting and analyzing user information, and recommend products and services to users that meet their preferences. Therefore, it has been more and more widely used in the fields of movie, music, news, product and WEB page recommendation. [0003] With the rapid increase in the number of mobile phone users and the rapid development of mobile communication technology, the rapid growth of mobile value-added data services has brought a large number of data services and application points, such as providing users with real-time weather, news, sports, Transportation and stocks are becoming new hot spots in the mobile value-added service market. In order to enable users to obtain the information they need in a timely and ...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/9535
Inventor 张永俊李启文蒋迎锋唐文波
Owner CHINA MOBILE GRP GUANGDONG CO LTD
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