A Narrow Group Recommendation List Method Based on Subgroup and Social Behavior
A recommendation list and subgroup technology, applied in the field of data processing, can solve the problem of large-scale recommendation list and achieve the effect of convenient selection
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[0022] An embodiment of the present invention, taking a movie list as an example, introduces a method for reducing a group recommendation list based on subgroups and social behaviors. The implementation process is as follows: figure 1 shown.
[0023] Step 1: Divide the group into several subgroups.
[0024] Filter out the useless data from the obtained original data set, preprocess the data set (randomly divide it into several groups), obtain the project theme feature (ie movie type) model and user theme preference model, and divide each group into several groups. subgroups. The method for obtaining the item topic feature model and the user topic preference model includes the following steps:
[0025] 1-1) Use the LDA (Latent Dirichlet Allocation, latent Dirichlet distribution) topic model to obtain the following project topic feature models:
[0026]
[0027] Among them, use represents the sth movie m s Whether it contains the subject feature g i . when represent...
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