USDR model based cloud recommendation method

Abstract

A USDR model based cloud recommendation method is provided. The method comprises the following steps: the first step: USDR data model modeling, whose process is as follows: 1.1 user data model modeling, wherein the user data is divided into six categories: user basic data, time data, location data, environmental data, user preference data and history data, and 1.2 system data model modeling, wherein the system data model comprises: basic data, functional data and other data; the second step: the USDR model based cloud recommendation method, whose process is as follows: 2.1 user based cloud recommendation method, and 2.2 system based cloud recommendation method; and the third step: obtaining a user commendation degree list by using the USDR model based cloud recommendation method. According to the method provided by the present invention, the USDR model for multi-source heterogeneous data is used, and different recommendation degrees of the user and the system are quickly obtained by classifying the user data and the system data, so that efficient data recommendation in the cloud environment can be realized.

Description

technical field [0001] The present invention relates to a cloud recommendation method based on USDR model Background technique [0002] The Web has entered the "2.0 era" with the advancement of technology and the update of information. At the same time, due to the acceleration of various information updates, Internet data resources have also entered the era of big data cloud. To a certain extent, Internet spam and There are also more and more invalid resources. When ordinary users want to find some useful resources, how to filter out specific resources from massive data has become an urgent problem to be solved. [0003] In the cloud environment, the unified modeling of cloud data has always been a research hotspot. For various information recommendation systems deployed in the cloud, the data structure is multi-source and heterogeneous, so users have higher requirements for data flexibility and security. With the continuous development of data information technology, netw...

AI Technical Summary

Problems solved by technology

[0009] In order to overcome the inability of the existing push method to solve the problem of personalized recommendation for users in the cloud environment facing multi-source heterogeneous data, the present invention aims at the characteristics of multi-source heterogeneous data in the cloud environment, and integrates mobile Internet security and privacy etc., the present invention provides a cloud recommendation method based on the USDR model that effectively solves the user's personalized recommendation problem in a cloud environment oriented to multi-source heterogeneous data, and adopts USDR (User System Data Relationship) oriented to multi-source heterogeneous data Model, by classifying user data and system data to quickly obtain different recommendation degrees of users and systems, so as to realize efficient recommendation of data in the cloud environment

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