Public opinion role recognition and migration system based on heterogeneous domain migration

Abstract

The public opinion role recognition and migration system based on heterogeneous domain migration relates to the fields of data mining and machine learning. In order to solve the problem that the existing technology can not effectively extract knowledge in the face of the complex information of the netizen, can not carry out transfer learning between different fields, and thus can not realize the indirect sharing of knowledge. The system is a public opinion role identification migration model based on the Markov logic network, includes a data predicate module, The structure learning module, theknowledge extraction module, the knowledge transfer module and the parameter learning module. The domain knowledge is converted into the knowledge which can be recognized by the model for structurallearning and extract the knowledge which needs to be transferred to the target domain to complete the knowledge transfer, and then the model after the transfer learning through the parameter learningmodule is obtained. By integrating the conversion complexity into the domain distance and considering the transfer learning boundary from single source domain to single target domain, the migration iseffectively extracted in the face of complex netizen information.

Description

technical field [0001] The invention relates to a public opinion role recognition migration system, and relates to the fields of data mining and machine learning. Background technique [0002] Transfer learning is divided into isomorphic transfer learning and heterogeneous transfer learning from the perspective of whether the input space of the source domain and the target domain are the same feature space. The factors that affect the effect of transfer learning are not only the selection of specific models, but also the domain distance. Factors, in the related research on the transfer learning boundary, researchers will first define the domain distance, because this will be used in the final transfer learning boundary analysis, and then use various known theoretical reasoning to obtain the final transfer Learning bounds, however, the current transfer learning bounds on heterogeneous relational data from a single source domain to a single target domain have a gap with the pe...

AI Technical Summary

Problems solved by technology

[0004] The purpose of the present invention is to provide a public opinion role recognition and migration system based on heterogeneous domain migration. In order to solve the problem that the existing technology c...

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