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

A technology of migration system and role, which is applied in the field of public opinion role recognition migration system, can solve problems such as the inability to effectively extract knowledge from Internet users' information, and the inability to realize indirect sharing of knowledge

Inactive Publication Date: 2019-02-01
HARBIN INST OF TECH
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  • Application Information

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 cannot effectively extract knowledge from complicated netizen information, and cannot perform transfer learning between different fields, and then The problem of not being able to realize the indirect sharing of knowledge

Method used

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

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Embodiment Construction

[0078] combined with Figure 1-9 and the corresponding tables, the implementation of the public opinion role recognition migration system based on heterogeneous domain migration described in the present invention is elaborated as follows:

[0079] The public opinion role recognition migration system described in the present invention integrates the transformation complexity into the domain distance, proposes a new domain distance formula, and proposes a calculation method for the migration learning limit from a single source domain to a single target domain. The following is a detailed description of the derivation of the domain distance formula and the determination of the transfer learning boundary from a single source domain to a single target domain:

[0080] In the present invention, except the common knowledge parameters and the intermediate parameters in the derivation process, other parameters have been given definitions.

[0081] Problem Definition: Suppose the sourc...

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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...

Claims

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Application Information

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IPC IPC(8): G06N7/00G06F16/953
CPCG06N7/00
Inventor 何慧张伟哲杨洪伟方滨兴李韬周奉兰白雅雯
Owner HARBIN INST OF TECH
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