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

LDA-based user consumption forecasting method for electronic commerce

A technology of e-commerce and forecasting methods, applied in the field of user consumption forecasting in e-commerce, can solve the problems of ignoring the impact and achieve the effect of optimizing the forecasting model

Active Publication Date: 2017-07-04
AEROSPACE INFORMATION
View PDF22 Cites 6 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] Extracting the user's purchase records and browsing path data, and relying on the acquired knowledge to predict their current consumption behavior is a common strategy at present. This method is simple and intuitive, but ignores the impact of user potential data on their consumption behavior

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
  • LDA-based user consumption forecasting method for electronic commerce
  • LDA-based user consumption forecasting method for electronic commerce
  • LDA-based user consumption forecasting method for electronic commerce

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0043] A commodity has many attributes, such as material, use, shape, size, etc., because of the diversity of attributes, it can be assigned to multiple categories, and each category is called a theme; and the description semantic information of commodities, historical transactions The comment information and other related information constitute the text information of the commodity, the historical consumption data owned by the consumer, the browsing path data, and the personal information of the consumer constitute the descriptive information about the consumer, and the two are called documents; Processing, extracting words. Based on the LDA model, a probability model of users and products is constructed, and the probability model is used to classify existing historical consumption data, classify user behavior, and predict the consumption trajectory of new users. The invention proposes an LDA-based e-commerce user consumption prediction model.

[0044]The process of construc...

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 present invention provides an LDA-based user consumption forecasting method for electronic commerce. The method comprises: mining a correlation between a current consumption behavior and a historical consumption behavior, a track of browsing commodities of a user, consumption information of the user, review information of a merchant for the user, personal information of the user and such more dual information of the user and commodity; modeling a consumption behavior and a product by using a Dirichlet distribution relation and an LDA topic model; constructing a probability model of a commodity, a user and between two; analyzing a new consumption behavior according to an obtained probability distribution model, so as to realize consumption forecasting of an e-commerce platform.

Description

technical field [0001] The invention relates to computer and Internet technologies, in particular to a user consumption prediction method for e-commerce based on an LDA model. Background technique [0002] In the era of e-commerce, the consumption mode of online promotion and offline consumption feedback gradually occupies people's daily life, and a large amount of data is generated in the process, including product promotion data, user consumption data, feedback data, and some Potential invisible data, including the location of the terminal, the user's social data, the correlation between the user's historical consumption, and so on. With the increase of e-commerce platforms, the data of e-commerce has also reached explosive growth. It is not feasible to rely on manpower to analyze massive data. How to effectively and automatically mine big data and obtain valuable potential data is a current research hotspot. [0003] Extracting the user's purchase records and browsing p...

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): G06Q10/04G06Q30/02G06F17/30
CPCG06Q10/04G06Q30/0202G06F16/35
Inventor 孙科武
Owner AEROSPACE INFORMATION
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

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic, Popular Technical Reports.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap|About US| Contact US: help@patsnap.com