Looking for breakthrough ideas for innovation challenges? Try Patsnap Eureka!

Intelligent e-commerce page stock-out management method and system based on machine learning

A machine learning and management system technology, applied in the field of out-of-stock management on smart e-commerce pages, can solve complex and other problems, achieve the effect of reducing difficulty, achieving scalability, and high scalability

Active Publication Date: 2018-12-21
方骥
View PDF10 Cites 10 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the physical flow and information flow chains of modern e-commerce supply chains are becoming more and more complex, and the reasons for page out-of-stocks are complex and changeable due to the involvement of multiple stakeholders. The rhythm of e-commerce platform operations (especially special windows such as promotions and brand events, such as 6.18, Double Eleven, etc.), cannot fundamentally solve the problem

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
  • Intelligent e-commerce page stock-out management method and system based on machine learning
  • Intelligent e-commerce page stock-out management method and system based on machine learning
  • Intelligent e-commerce page stock-out management method and system based on machine learning

Examples

Experimental program
Comparison scheme
Effect test

specific Embodiment

[0035] A smart e-commerce page out-of-stock management system based on machine learning, including data source definition management 101, heterogeneous multi-data source processing 104, knowledge and learning mechanism 102, reasoning based on deep learning 105, out-of-stock prediction alarm and Management 106; wherein, the data source definition management 101 is used to provide a highly flexible definition and configuration management method for multi-source heterogeneous data; the heterogeneous multi-data source processing 104 is used to realize the cleaning, classification and merging of imported data; The knowledge and learning mechanism 102 is used to manage reasoning structure definition, feature and mode definition, workflow definition, and machine learning model configuration, training evolution and parameter management; and related data information are automatically analyzed and reasoned to determine the reason for shortage; the shortage prediction alarm and management...

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 relates to the technical field of machine learning, and discloses a management method for automatically deducing, tracking processing and replenishing the shortage reason of an e-commerce page, which realizes eliminating the shortage to the maximum extent through an algorithm model. The invention is characterized in that the deep neural network model and the method of the continuousevolution mechanism are applied to the e-commerce industry, comprising the following steps of: acquiring and processing multi-source heterogeneous data; Pattern Analysis and Reasoning Based on NeuralNetwork; Automatic workflow task assignment; Multidimensional data analysis; Knowledge management and model evolution. The invention extracts mode codes based on commodity page status, inventory, order, logistics, personnel and other information; the algorithm model automatically recognizes and deduces the code. Establish workflow for stock-out events based on results and knowledge base; the forecasting model can generate shortage warning and trigger replenishment event. The invention effectively processes the shortage of e-commerce pages, has high accuracy of analysis and inference, monitorsunknown shortage reasons, and realizes the transformation from post-processing to pre-prevention.

Description

technical field [0001] The present invention relates to the technical field of machine learning, and more specifically, to a machine learning-based smart e-commerce page out-of-stock management method and system. Background technique [0002] With the rapid development of e-commerce in China, the transaction scale of China's e-commerce retail market has already reached trillions, ranking first in the world in 2015. The rapid expansion of online shopping users has laid a good user base for the development of the online shopping market, releasing huge market potential. At the same time, it also puts forward higher requirements and challenges for the operational capabilities of e-commerce. Out-of-stock on the e-commerce page refers to the fact that the purchase page of the product indicates that it is out of stock, including out-of-stock of product categories, regional out-of-stock, general out-of-stock and off-shelf status, etc., when consumers cannot make purchases. Out-of-...

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): G06Q30/06G06Q30/02G06Q10/08G06K9/62
CPCG06Q10/087G06Q30/0201G06Q30/0202G06Q30/0641G06F18/23G06F18/2413G06F18/24147
Inventor 方骥
Owner 方骥
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Patsnap Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Patsnap Eureka Blog
Learn More
PatSnap group products