Metapath-based full-view information representation heterogeneous e-commerce platform user alignment method

Abstract

The invention belongs to the field of network alignment, and particularly relates to a meta-path-based full-view information representation heterogeneous e-commerce platform user alignment method, which comprises the following steps of: acquiring attribute data and interaction data of a user, and performing aggregation preprocessing on the attribute data and the interaction data of the user; extracting the user data after aggregation preprocessing; inputting the extracted user data into a meta-path-based full view information representation heterogeneous e-commerce platform user alignment model, and carrying out alignment processing on the user. From three aspects of user attribute information, user commodity interaction information and user interest attention, the key part of the method is that heterogeneous platform sparse data is aggregated by adopting a meta-path; more effective experimental data are obtained, and weight distribution is performed on learned user attribute relation vectors and user interaction relation vectors by adopting an attention mechanism, so that efficient task alignment is performed.

Description

Technical field [0001] The present invention belongs to the field of network alignment, and specifically, the present invention relates to a transparent information based on a meta-path-based information representing the alignment method of heterogeneous e-commerce platform. Background technique [0002] With the popularity of mobile intelligent terminals and the rapid development of Internet technology, most people will create their own accounts in different platforms, but because of the muddar of the platform, it is difficult to judge whether the two accounts in different platforms are the same. A user is in use. In response to how to identify cross-platform users, the heterogeneous network users are aligned, early researchers mainly propose entity alignment methods based on user attribute information, such as public information information, including nickname, birthday, address, Gender, data photo, etc., measure the similarities between accounts and identify match. However, wi...

AI Technical Summary

Problems solved by technology

The analysis of a single personal attribute information or structural relationship is one-sided, and in the actual system, the interaction information is very rich, and it is difficult to integrate such information to identify the user identity

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