User portrait prediction method based on multi-source transboundary data fusion
A data fusion and user technology, applied in data processing applications, special data processing applications, neural learning methods, etc., can solve problems such as sparsity, associated feature loss, etc., to solve feature loss, avoid feature loss, and improve user portrait prediction effect of ability
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[0023] The specific embodiments of the present invention will be further described in detail below in conjunction with the accompanying drawings.
[0024] A user portrait prediction method based on multi-source cross-border data fusion. The specific process is described as follows: figure 1 shown, where:
[0025] Step 1: Collect information generated by user interaction on the shopping platform.
[0026] The collected information includes:
[0027] (1) Basic information of the user, including gender and age.
[0028] (2) User behavior records, including the time of purchasing the product, product number, product name, etc.
[0029] Step 2: Construct heterogeneous knowledge graph and user history interaction sequence;
[0030] 2-1 Construction of heterogeneous knowledge graph
[0031] 2-1-1 Segment the product name to get a set of word segmentation results {i 1 , i 2 ,...,i m ,...}, i m Indicates the mth participle;
[0032] 2-1-2 Perform two rounds of recursive searc...
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