Recommendation method and system based on heterogeneous information network and adaptive denoising

A technology of heterogeneous information network and recommendation method, which is applied in the field of recommendation methods and systems based on heterogeneous information network and adaptive denoising, can solve the problems of extraction and embedding, low precision, inability to adapt to data sets, etc., and achieves noise removal. , the effect of improving the accuracy

Pending Publication Date: 2022-04-19
DALIAN MARITIME UNIVERSITY
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Problems solved by technology

[0005] In view of this, the present invention provides a recommendation system based on heterogeneous information network and adaptive denoising, which solves the problem that most of the current recommendation systems only focus on recommendation accuracy, and only focus on recommendation accuracy without considering the diversity of data sets. For example, homogeneous graphs and heterogeneous graphs will lead to inability to adapt to more complex data sets, unable to better simulate the real world, and the ob

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  • Recommendation method and system based on heterogeneous information network and adaptive denoising
  • Recommendation method and system based on heterogeneous information network and adaptive denoising
  • Recommendation method and system based on heterogeneous information network and adaptive denoising

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[0042] In order to make those skilled in the art better understand the solutions of the present invention, 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 Embodiments are part of the present invention, but not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0043] It should be noted that the terms "first", "second" and the like in the description and claims of the present invention and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific sequence or sequence. It is to be understood that the data so used may be interchanged under appropriate ...

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Abstract

The invention discloses a recommendation method and system based on a heterogeneous information network and adaptive denoising, and belongs to the technical field of recommendation systems. According to the method, the heterogeneous information network is adopted as the input of the model, complex input can be better processed, the real world can be better modeled, the problem that a homogeneous information network cannot simulate the real situation is solved, and the recommendation precision is greatly improved. And an adaptive denoising module is added, so that noise in the data set can be effectively removed, and effective data of the heterogeneous information network data set can be better reserved. And meanwhile, the depth map convolutional neural network is assisted, so that the precision of the recommendation model can be effectively improved, and the method adapts to a more complex real world. The problem that most of current recommendation systems only pay attention to recommendation precision is solved, the recommendation effect of the model can be changed from the perspective of the data set, meanwhile, due to the fact that the denoising module is added, the time complexity of the model becomes low, and the method can be effectively applied to the actual industrial environment.

Description

technical field [0001] The invention belongs to the technical field of recommendation systems, and relates to a recommendation method and system based on heterogeneous information networks and adaptive denoising. Background technique [0002] In recent years, recommender systems have played an increasingly important role in different online services, helping users discover items of interest in huge data sources. [0003] In the field of recommender systems, many previous studies are based on homogeneous information networks. One advantage of this is that modeling is more convenient, there is no need to consider different types of nodes and edges, and the implementation of the algorithm is more natural. [0004] However, the types and relationships of information networks in the real world are multi-faceted, and various forms of auxiliary information such as user, commodity, director, starring and other entity information can be used in the recommendation system. It is diff...

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Application Information

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IPC IPC(8): G06F16/9536G06N3/04G06N3/08
CPCG06F16/9536G06N3/08G06N3/045
Inventor 张益嘉靳思晨
Owner DALIAN MARITIME UNIVERSITY
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