Personalized commodity recommending method and system which integrate attributes and structural similarity

Abstract

The invention discloses a personalized commodity recommending method which integrates attributes and structural similarity. In the method, users and commodities are used as nodes with characteristic information to be mapped to a network by integrating the attribute information and structural similarity information, and an information network chart is established according to the purchasing relation between customers and the commodities; and interests and preference among user node pairs are measured by the integrated attributes and structural similarity in the information network chart, and the nearest neighbor is selected by the interests and the preference to improve the accuracy of recommending. On the basis of the recommending method, the invention also discloses a personalized commodity recommending method which integrates the measurement of the attributes and the structural similarity. In the system, the interests and the preference of the users are measured accurately by a computing method of integrating the similarity of the attributes and the similarity of node structure backgrounds in the information network chart, and the generation efficiency of the nearest neighbor is improved by utilizing clustering technology. The method and the system can be applied to electronic commerce, and provide personalized commodity recommending for the users.

Description

technical field [0001] The present invention relates to the field of computer Internet technology, in particular to the field of e-commerce, in particular to a personalized product recommendation method and system integrating attributes and structural similarities. Background technique [0002] With the continuous development of e-commerce, the number and types of goods are increasing rapidly. In order to find the goods they need as soon as possible, users want a function similar to a shopping guide to help them choose the right goods or services. Personalized recommendation systems should be used. And born. Based on massive data analysis and mining technology, personalized recommendation recommends products and information of interest to users according to their behavior habits and interest characteristics. At present, almost all large-scale e-commerce websites integrate personalized recommendation technology into the system to varying degrees, among which collaborative fi...

AI Technical Summary

Problems solved by technology

However, the above two calculation methods based on structural similarity and attribute similarity will lose some information when making recommendations. According to the similarity enhancement hypothesis: the similarity between two objects not only depends on their own attributes but also depends on their attributes. similarity between related other objects

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