Commodity information pushing method and device based on link forecasting

Abstract

The invention discloses a commodity information pushing method based on link forecasting. The commodity information pushing method includes the steps of determining all associated users of a user to be recommended when it is determined that a selected online social network has the multi-association attribute, building a two-part graph from the user to be recommended and the associated users to commodities, judging whether a mapping node of the user to be recommended exists in the two-part graph or not, if it is determined that the mapping node exists, determining commodity information pushed to the user to be recommended based on a two-part graph algorithm, reconstructing a two-part graph from the user to be recommended and the associated users to the commodities according to selection information input by the user to be recommended, determining commodity information pushed to the user to be recommended based on the updated two-part graph, and then repeating the treating process according to selection information input by the user to be recommended. The invention further discloses a commodity information pushing device based on link forecasting.

Description

technical field [0001] The invention relates to commodity information push technology in the network, in particular to a method and device for pushing commodity information based on link prediction. Background technique [0002] With the rapid growth of the scale and coverage of the Internet, users can enjoy the free interaction with the Internet and bring convenience to more and more users. However, the simultaneous presentation of a large amount of information also prevents users from obtaining what they really need from the massive information. Partly, the efficiency of information use is reduced instead, and the recommendation system is a very potential means of information filtering to solve the problem of information overload. The so-called recommendation system uses the network to provide customers with product information and suggestions to help users decide what products they should buy, simulating a salesperson Intelligent systems that help customers through the bu...

AI Technical Summary

Problems solved by technology

[0002] With the rapid growth of the scale and coverage of the Internet, users can enjoy the free interaction with the Internet and bring convenience to more and more users. However, the simultaneous presentation of a large amount of information also prevents users from obtaining what they really need from the massive information. Partly, the efficiency of information use is reduced instead, and the recommendation system is a very potential means of information filtering to solve the problem of information overload. The so-called recommendation system uses the network to provide customers with product information and suggestions to help users decide what products they should buy, simulating a salesperson Intelligent systems that help customers through the buying process

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