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Recommend method and recommend system of heterogeneous network

A recommendation method and heterogeneous network technology, applied in transmission systems, special data processing applications, instruments, etc.

Active Publication Date: 2008-12-10
TSINGHUA UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] However, in Web2.0 applications where heterogeneous data emerges in an endless stream, users are faced with a variety of different types of data (such as figure 2 A general social network containing users, categories, resources, and tags and their complex relationships shown in ), such a heterogeneous network provides us with a new environment for validating recommendation methods, and also brings new challenges

Method used

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  • Recommend method and recommend system of heterogeneous network
  • Recommend method and recommend system of heterogeneous network
  • Recommend method and recommend system of heterogeneous network

Examples

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Embodiment 1

[0069] This embodiment is used to illustrate a non-personalized sub-image recommendation method. The operation of recommending subgraphs based on subgraphs in the social relationship network can be performed by means of the importance calculation means, the correlation degree calculation means and the recommendation means. At this time, the recommendation result has nothing to do with the user, and any user will get the same recommendation result for the same input subgraph.

[0070] The non-personalized subgraph recommendation method includes the following four steps:

[0071] Step 1: Establishing a social network database, in which there are different types of objects and the relationships among these objects, and the objects include users, resources, tags and categories.

[0072] Step 2: Use the importance calculation device to evaluate the global importance of social network objects. The role of the importance calculation means is to evaluate the global importance for ea...

Embodiment 2

[0146] This embodiment is used to illustrate a personalized subgraph recommendation method. The operation of recommending subgraphs based on subgraphs in the social relationship network can be performed through the correlation degree calculation device, the importance degree calculation device and the browsing history information calculation device. At this point, the recommendation results vary with different users, that is, different users will get different recommendation results for the same input subgraph.

[0147] The personalized recommendation method is to add browsing information means on top of the relevance degree calculation means and the importance degree calculation means, that is to say, after using the relevance degree calculation means for correlation calculation and using the importance degree calculation means for global importance evaluation Afterwards, when the user logs in, the sub-picture is recommended according to the user's browsing history, which can...

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Abstract

The invention relates to a recommendation method in a heterogeneous network and a recommendation system based on the method. The recommendation method in the heterogeneous network uses a uniform model to simulate a plurality of objects with different types and a complex relation that may exist in the objects, and finishes recommendation perfectly by the model. Firstly, a social network library (the objects and the relation are heterogeneous) is established; and then, the global importance estimation to the social network object is executed by an importance calculating device; next, the relevance estimation to the social network object is executed by a relevance calculating device; the browse information of the active user is obtained by a browse historic information calculating device; atlast, the operation of given subgraph and recommendation subgraph is executed by above three basic devices in the social relation network. The method is effective and overcomes the defect that only atype of object is recommended in the prior art.

Description

technical field [0001] The invention relates to the field of social network information processing, in particular to a recommendation method in a heterogeneous network and a recommendation system based on the method. Background technique [0002] Recommendation is a method that can effectively reduce the cost of finding information. Recommendation technology is widely used in many popular e-commerce applications, such as Amazon.com, CDNow.com, eBay.com, Reel.com, etc. [0003] In recent years, many recommendation methods have been proposed one after another, such as methods based on content filtering, collaborative filtering, clustering models, classification models, graph models, and association rules. These methods are adopted by many Internet applications, and most of the existing applications often only recommend a specific type of object based on several keywords or an object input by the user (Amazon only recommends books, newsbaidu only recommends news, movielens.com ...

Claims

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Application Information

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IPC IPC(8): H04L29/08H04L29/06G06F17/30
Inventor 唐杰张静杨子李涓子
Owner TSINGHUA UNIV
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