Recommendation method and system integrating user behaviors and object content

A technology for recommending methods and items, applied in special data processing applications, instruments, calculations, etc., to achieve the effect of improving precision and personalization, and improving accuracy

Active Publication Date: 2014-01-15
TCL CORPORATION
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  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0006] The technical problem to be solved by the present invention is to provide a recommendation method and system that integrates user behavior and item content to solve the cold start of the existing recommendation system and how to smoothly transition from cold start to health problems

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  • Recommendation method and system integrating user behaviors and object content
  • Recommendation method and system integrating user behaviors and object content
  • Recommendation method and system integrating user behaviors and object content

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Embodiment Construction

[0034] In order to make the object, technical solution and advantages of the present invention more clear and definite, the present invention will be further described in detail below with reference to the accompanying drawings and examples. It should be understood that the specific embodiments described here are only used to explain the present invention, not to limit the present invention.

[0035] see figure 1 , figure 1 It is a flow chart of the recommendation method for integrating user behavior and item content provided by the present invention, including the following steps:

[0036] Step S100, by associating the behavior data of each user with the content data of all items, to obtain a user interest list of each user for all item contents;

[0037] Step S200, calculate the similarity between the user interest list and the content data of all items, obtain the item weight recommended by each user for the item content data, and obtain the weight of each user by sorting...

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Abstract

The invention discloses a recommendation method and system integrating user behaviors and object content. The recommendation method integrating the user behaviors and the object content comprises the steps that through correlation between behavior data of each user and content data of all the objects, a list of user interest of each user to all the objects is obtained; the similarity of the list of user interest and the content data of all the objects is calculated, the recommendation object weight of each user to the content data of each object is obtained, and the objects recommended to each user are obtained through ranking of the recommendation object weights. According to the recommendation method and system integrating the user behaviors and the object content, the main problems that how an existing recommendation conducts cold start and how the existing recommendation smoothly transmits to the normal operation state from cold start are solved, the accuracy, the coverage rate, the novelty and the like of the system are greatly improved, the accuracy and the personalization of the recommendation system can be well improved, and more users are attracted and use the recommendation system.

Description

technical field [0001] The invention relates to an intelligent recommendation system, in particular to a recommendation method and system integrating user behavior and item content. Background technique [0002] With the development of information technology and the Internet, how to find the information that users are interested in from a large amount of information, and how to make their own information popular with users, is a very difficult thing for both users and providers. The task of the recommendation system is to connect users and information. On the one hand, it helps users find information that is valuable to them, and on the other hand, it allows information to be displayed in front of users who are interested in it, so as to achieve a win-win situation for both information consumers and information providers. . The recommendation system mainly predicts the user's interest and makes recommendations to the user by analyzing the user's behavior and modeling it. ...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/337G06F16/9535
Inventor 李朝汪灏泓
Owner TCL CORPORATION
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