Methods and devices of recommending network object

Abstract

The application discloses methods and devices of recommending a network object. One of the methods includes: acquiring data of access of each geographical region to each network object; classifying the access data on the basis of the geographical regions to obtain an initial access data set respectively corresponding to each geographical region; calculating similarity among all the initial accessdata sets; merging initial access data sets, of which similarity is greater than a set threshold value, to obtain one or more target access data sets; and recommending the network object to computingequipment in one or more geographical regions, which correspond to a target access data set, on the basis of the target access data set. When the network object is recommended, the recommended networkobject is enabled to be influenced by corresponding data of a geographical region in which computing equipment is located, and also influenced by access data of the other geographical regions which are similar to the geographical region in which the computing equipment is located, association analysis on the data of the multiple regions is realized, and efficiency of mining and utilization on thedata is improved.

Description

technical field [0001] The present application relates to the technical field of information recommendation, in particular to a method for recommending network objects and a device for recommending network objects. Background technique [0002] With the development of information technology, the technology of providing information recommendation for users based on the historical records of user behavior is also developing continuously, for example, recommending other products of similar categories to users based on the user's shopping records, browsing records and other information. [0003] Generally speaking, recommendations can be made based on rankings, ratings, or other behavioral data of users. In the prior art, it is relatively common to make recommendations by analyzing the data of the area where the user is located, but the influence of other areas on the area where the user is located cannot be taken into consideration when recommending. The existing technology on...

AI Technical Summary

Problems solved by technology

In the existing technology, it is a relatively common way to make recommendations by analyzing the data of the user's area, but the influence of other areas on the user's area cannot be taken into account when recommending

The existing technology only recommends based on the historical data of the region, and cannot perform correlation analysis on the data of multiple regions, and cannot realize the full mining and utilization of the data

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