Expert recommendation method based on multi-modal information learning

An information learning and recommendation method technology, applied in the field of expert recommendation based on multimodal information learning, can solve problems such as low recommendation accuracy, inability to learn experts from models, and incomplete expert information, and achieve the effect of improving accuracy.

Pending Publication Date: 2022-06-24
SHIJIAZHUANG TIEDAO UNIV
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Problems solved by technology

At the same time, when a new expert appears, there is often a problem of incomplete expert information, the model cannot learn the effective representation of t

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  • Expert recommendation method based on multi-modal information learning
  • Expert recommendation method based on multi-modal information learning
  • Expert recommendation method based on multi-modal information learning

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Embodiment Construction

[0057] In order to make the objectives, technical solutions and advantages of the present invention clearer, the present invention is further described below with reference to the accompanying drawings.

[0058] In this example, see figure 1 and figure 2 As shown, the present invention proposes an expert recommendation method based on multimodal information learning, including steps:

[0059] S10, crawl network expert information data and project information data, preprocess the data, and sort out the expert information data in the existing expert database;

[0060] S20, construct an expert historical review project sequence according to the information of experts serving as judges, and construct a heterogeneous graph of expert attributes according to expert attributes;

[0061] S30, use the bert model to learn the expert's text information, use the graph neural network model to learn the expert's attribute heterogeneous graph, build a self-attention recommendation model to...

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Abstract

The invention discloses an expert recommendation method based on multi-modal information learning, and the method comprises the steps: crawling network expert information data and project information data, and arranging the expert information data in an existing expert database; constructing an expert review heterogeneous graph and an expert attribute heterogeneous graph; the text information of the expert is learned by the bert model, the attribute heterogeneous graph of the expert is learned by the graph neural network, the historical review sequence of the expert is learned by building a self-attention recommendation model, the learned embedding is input into the fusion layer to obtain expert information embedding, and a pre-training model is obtained; and extracting expert information embedding by using a pre-training model, encoding project information to obtain project information embedding, and inputting the obtained expert attribute representation and project information representation into a multi-layer perceptron to train the model to obtain recommendation scores of experts and projects. According to the method, rich semantics and attribute information are fully fused into embedding and model parameters of experts, and the accuracy of expert recommendation is improved.

Description

technical field [0001] The invention belongs to the technical field of data processing, in particular to an expert recommendation method based on multimodal information learning. Background technique [0002] With the development of science and technology and other aspects to vigorously promote theoretical innovation, the number of applications for various innovative projects has increased significantly, which in turn leads to an increasing number of applications for science and technology projects. Among them, there is a key step in the stage of scientific research project initiation and conclusion—recommendation by review experts. Review expert recommendation refers to recommending experts in related fields to review the project according to the scientific research project documents, so as to evaluate the practical significance, feasibility and completion quality of the project. This requires that the skills and fields of expertise mastered by the review experts match the...

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Application Information

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IPC IPC(8): G06N3/04G06N3/08G06F16/951
CPCG06N3/08G06F16/951G06N3/045
Inventor 王书海彭浩唐翊群赵晓亮王辉胡畅霞
Owner SHIJIAZHUANG TIEDAO UNIV
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