Deep learning recommendation method and system based on multi-platform fusion

A deep learning and recommendation method technology, applied in the field of recommendation system, can solve the problems of inaccurate recommendation and inability to make recommendations, etc., achieve fast convergence speed, optimal recommendation effect, and improve accuracy

Pending Publication Date: 2022-05-27
创络(上海)数据科技有限公司
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] In order to solve the above-mentioned technical problems, the present invention provides a deep learning recommendation method and system based on multi-platform fusion. This method effectively solves the problem of insufficient data for initial use of new users by fusing multi-platform information and combining deep learning algorithms. Accurate or Impossible to Make Recommendation Questions

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Deep learning recommendation method and system based on multi-platform fusion
  • Deep learning recommendation method and system based on multi-platform fusion
  • Deep learning recommendation method and system based on multi-platform fusion

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0057] The technical solutions in the embodiments of the present invention will be described clearly and completely below. 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.

[0058] In order to describe in detail the technical content of the present invention, the achieved objectives and technical effects, the following detailed description is given in conjunction with the embodiments and the accompanying drawings.

[0059] see figure 1 , the deep learning recommendation method of multi-platform integration includes:

[0060] Step S1: building multi-platform user relationships, specifically collecting users and trust relationships from general social platforms and / or specific fields, so as ...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a deep learning recommendation method based on multi-platform fusion, and the method comprises the steps: multi-platform user relationship construction: collecting users and interaction relationships from a universal social platform and / or a specific field, thereby constructing social relationships between the users, the social relationships between the users being divided into first-level friends and second-level friends; constructing a matrix decomposition neural collaborative filtering model, and constructing the model by fusing MF and LSTM; the model is trained, and the obtained model is trained through a data set published by the Internet; and performing feedback correction on the trained model, and correcting the similarity between the element user and the recommended user according to the interaction of the element user on the recommended article. The invention further provides a system of the deep learning recommendation method based on multi-platform fusion. According to the method, the recommendation algorithm is improved, and the higher convergence speed and the better recommendation effect are achieved.

Description

technical field [0001] The present invention relates to the field of recommendation systems, in particular, to a deep learning recommendation method and system based on multi-platform fusion. Background technique [0002] With the rapid development of Internet technology and the explosive growth of information on the Internet, people enjoy the convenience brought by huge information resources. Users can search for specific keywords by specifying keywords to solve their needs for specific information. Earlier information retrieval was done through In this context, the emerging recommendation system is just right to solve this pain point problem, that is, based on the user's historical records, infer the user's interest needs, And recommend products that users may like in real time. Its generation can not only tap the potential interests of users and improve user experience, but also promote product promotion and increase the enthusiasm of physical manufacturing. [0003] The...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F16/9536G06F16/958G06F16/2458G06Q30/06G06N3/04G06N3/08
CPCG06F16/9536G06F16/958G06F16/2465G06Q30/0631G06N3/08G06N3/044Y02P90/30
Inventor 江元元
Owner 创络(上海)数据科技有限公司
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products