General recommendation method and system based on object tags

A recommended method and object technology, applied in special data processing applications, instruments, electrical digital data processing, etc., can solve the problems of limited number of categories, high mapping cost, and low precision

Active Publication Date: 2013-06-26
BEIJING PEOPLE HAPPY INFORMATION TECH
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AI Technical Summary

Problems solved by technology

[0006] Disadvantages: 1. The recommended object must be classified and mapped in advance. If the number of entities is large, it will face the problem of high mapping cost and low accuracy; 2. It is difficult to obtain user information, with low credibility and high user resistance; 3. Recommendation accuracy low, poor effect
[0009] Disadvantages: 1. The recommended object must be classified and mapped in advance. If the number of entities is large, it will face the problem of high mapping

Method used

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  • General recommendation method and system based on object tags
  • General recommendation method and system based on object tags
  • General recommendation method and system based on object tags

Examples

Experimental program
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Embodiment

[0140] 1. Object Correlation Analysis

[0141] In this embodiment, corresponding tags and weights are specified for all objects that need to be analyzed. For example, object O i The label vector is {i ,TF i >,...,k ,TF k >}, object O j The label vector is {j ,TF j >,...,p ,TF p >}. T i Represents a certain label, which can be a label in a closed set or an open label, but it must be able to compare with each other, that is, there is a certain f(x), so that when Ti=Tj, then f(Ti)=f(Tj ), and when Ti≠Tj, then f(Ti)≠f(Tj). TFi represents the weight of Ti on an object, which is a floating-point number. If the object does not have this label, TFi is 0; if there is but the weight of the label cannot be counted, TFi can be assigned a value of 1 or other specified values.

[0142] The correlation between objects can be expressed indirectly by the correlation between their label sets. For example, R(x, y) is used to represent the correlation calculation formula between objects...

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Abstract

The invention relates to a general recommendation method and a system based on object tags. The general recommendation method the based on the object tags comprises the following steps of obtaining a user tag and candidate recommendation object tags; obtaining correlation between the user tag and the candidate recommendation object tags; and choosing candidates and recommending the candidates to a user according to the correlation. The invention provides a unified object correlation calculation method based on the object tags and a general recommendation theory model based on the correlation calculation, and a practical recommendation system is built to prove the validity of the method. The general recommendation system can be applied to almost all the personalized recommendation occasions and part non-personalized recommendation occasions, and has the advantages of being general in data, easy and convenient to deploy, and flexible to expand, and can be deployed and used very conveniently.

Description

technical field [0001] The invention relates to the field of Internet information mining, in particular to a general recommendation method and system based on object tags. Background technique [0002] The existing non-personalized recommendation methods mainly include hotspot recommendation and manual recommendation, both of which recommend the recommendation results to all users indiscriminately. The results of the former come from the choices of most users, while the results of the latter are Rely on artificial selection. [0003] Existing personalized recommendation systems are mainly divided into the following different systems: [0004] Statistical system: This system directly recommends the target object to the right person by mining social information such as the user's age, address, and income. For example, some personalized advertising products, most advertising emails, etc. [0005] Advantages: The method is simple and the amount of calculation is small; [00...

Claims

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Application Information

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IPC IPC(8): G06F17/30
Inventor 薛晔伟何平
Owner BEIJING PEOPLE HAPPY INFORMATION TECH
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