A Method of Link Prediction in Heterogeneous Networks Based on Meta-Path
A heterogeneous network and link prediction technology, applied in the direction of neural learning methods, biological neural network models, electrical components, etc., can solve the problems of complex network interlacing and heterogeneity, and achieve the effect of high algorithm efficiency and accuracy
Active Publication Date: 2022-06-17
BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY
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Problems solved by technology
The complex interlacing of networks in real life brings great challenges to the accuracy of link prediction. An effective link prediction method can provide users with accurate prediction results and has important application value
However, the existing network link prediction methods often ignore the impact of network heterogeneity on link prediction. Most of the existing methods are aimed at homogeneous networks, but most real networks are heterogeneous.
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[0058] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.
[0059] In order to make the above objects, features and advantages of the present invention more clearly understood, the present invention will be described in further detail below with reference to the accompanying drawings and specific embodiments.
[0060] The present invention provides a method for predicting a heterogeneous network link based on a meta-path, which specifically includes the following steps:
[0061] Step 1. Build...
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The invention discloses a method for predicting heterogeneous network links based on meta-paths, using meta-paths to process rich and complex semantics of heterogeneous networks, extracting meta-path instances from the network and learning network node weights, and synthesizing network topology features to update Network node embedding, using updated network node embedding, can do classification, clustering and link prediction. It has high applicability in real life and can effectively improve the performance of heterogeneous network classification, clustering and link prediction. Accuracy.
Description
technical field [0001] The invention relates to the technical field of data mining, in particular to a method for predicting links of heterogeneous networks based on meta-paths. Background technique [0002] With the development of science and technology and the advent of the era of big data, the recommendation system has emerged as the times require, which aims to help users more easily find the most interesting content in the massive data. Link prediction is a bridge between complex networks and information technology, it can effectively restore missing links and predict upcoming links, and is an important method to implement recommender systems. The network interleaving is complex in real life, which brings great challenges to the accuracy of link prediction. An effective link prediction method can provide users with accurate prediction results and has important application value. However, the existing network link prediction methods often ignore the influence of network...
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IPC IPC(8): H04L41/147H04L41/14H04L41/12G06F16/901G06N3/04G06N3/08
CPCH04L41/147H04L41/145H04L41/12G06F16/9024G06N3/084G06N3/045
Inventor 段大高尹丹琪韩忠明杨伟杰刘文文
Owner BEIJING TECHNOLOGY AND BUSINESS UNIVERSITY