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A movie group recommendation method and system based on convolutional collaborative filtering

A collaborative filtering recommendation and collaborative filtering technology, applied in the field of recommendation services, to achieve the effect of improving the hit rate

Active Publication Date: 2021-08-10
GUILIN UNIV OF ELECTRONIC TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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Problems solved by technology

[0004] The purpose of the present invention is to overcome the shortcomings of the prior art, provide a movie group recommendation method and system based on convolution collaborative filtering, and solve the shortcomings of the current recommendation method

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  • A movie group recommendation method and system based on convolutional collaborative filtering
  • A movie group recommendation method and system based on convolutional collaborative filtering
  • A movie group recommendation method and system based on convolutional collaborative filtering

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Embodiment Construction

[0033] In order to make the purposes, technical solutions and points of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only It is a part of the embodiments of this application, not all of them. The components of the embodiments of the application generally described and illustrated in the figures herein may be arranged and designed in a variety of different configurations. Accordingly, the following detailed description of the embodiments of the present application provided in the accompanying drawings is not intended to limit the scope of the claimed application, but merely represents selected embodiments of the present application. Based on the embodiments of the present application, all other embodiments obtained by those skilled in th...

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Abstract

The invention relates to a movie group recommendation method and system based on convolution collaborative filtering. The recommendation method includes: obtaining user data and product content data through operators to form user groups, and processing them into a format that can be recognized by the model; using volume-based The active collaborative filtering recommendation algorithm processes the above data to obtain the recommendation list of the user group; recommends to the relevant user group, obtains the user's feedback data at the same time, and returns the feedback data to the system, processes it into a corresponding format, and then uses the convolution-based The collaborative filtering algorithm performs data processing to calculate the recommendation list, and continues to recommend products to the user group. The advantage of the present invention is that: after the user embedding and item embedding features are linearly fused, the processed fusion embedding vector is directly sent to a single-layer convolutional neural network; a lot of parameters can be reduced. It can effectively improve the hit rate of the model's recommended products.

Description

technical field [0001] The present invention relates to the technical field of recommendation services, in particular to a method and system for recommending movie groups based on convolution collaborative filtering. Background technique [0002] With the rapid development of society, people have to screen a lot of information every day when surfing the Internet; in order to solve the problem of information overload, recommendation systems are widely used in online information systems such as e-commerce platforms and mobile apps. An efficient recommendation system can not only bring traffic and profits to service providers, but also help them select products that they are more interested in. [0003] Traditional recommendation algorithms often do not use neural networks in the system, which leads to a lot of room for improvement in system performance. In recent years, some recommendation systems have been applied to various neural networks, but most of them are multi-layer p...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/9536G06F16/9535G06N3/04
CPCG06F16/9536G06F16/9535G06N3/045
Inventor 杨青李贺永
Owner GUILIN UNIV OF ELECTRONIC TECH