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Online e-commerce recommendation method based on big data and big data AI system

A technology of e-commerce and recommendation method, applied in the field of big data, can solve the problems of stagnation of accuracy time sequence, lack of consideration of business service attribute update, etc., to achieve the effect of improving accuracy

Inactive Publication Date: 2021-11-02
李德财
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, related technologies lack the consideration of updating the business service attributes of e-commerce business, and are usually determined by the data of the initial statistical configuration, which leads to a stagnation in the accuracy of subsequent e-commerce business recommendations.

Method used

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  • Online e-commerce recommendation method based on big data and big data AI system
  • Online e-commerce recommendation method based on big data and big data AI system
  • Online e-commerce recommendation method based on big data and big data AI system

Examples

Experimental program
Comparison scheme
Effect test

Embodiment a1

[0154] Example Step a1, the plurality of acquired target point target interactive session interest potential session intended behavior may include content described steps: acquiring a target point of the target interactive conversation history with reference to the interest mapping knowledge information; according to a predetermined correspondence between the sequence of historical references and historical knowledge map knowledge map reference information session interactive session point of interest to characterize the potential behavior of intent, as well as the historical reference target knowledge map information, determining that the target session interactive points of interest more potential targets session intention of the author.

[0155] For example, the goal of historical knowledge map reference information for the target interest point to distinguish between interactive sessions, mapping knowledge in the history of interactive process of knowledge production target hi...

Embodiment a2

[0163] Example a2 implemented, according to potential session with intent to session interactive POI session interactive points of interest pre-determined historical reference knowledge map information, historical reference knowledge map information characterizing interactive update business scenarios and historical reference knowledge map information characterizing the correspondence between sequence, and the target reference history information knowledge map, interactive session to determine the target interest point of each of the potential target session with intent to update the corresponding target interactive business scenarios.

[0164] Correspondence between the sequence of records, for example, predetermined historical reference knowledge map information, historical reference knowledge map information session interactive point of interest to characterize the potential session intention of the author of the interactive updating business scenarios and historical reference ...

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Abstract

The embodiment of the invention provides an online e-commerce recommendation method based on big data and a big data AI system, and the method comprises the steps: obtaining a first business service attribute of a target e-commerce business and e-commerce big data of the target e-commerce business in a preset statistical segment, and based on this, according to the first business service attribute and the e-commerce big data, generating a target input component, and performing business service attribute updating on the target input component based on the business service attribute updating model to obtain a second business service attribute corresponding to the target e-commerce business. Therefore, in combination with the first business service attribute and the e-commerce big data of the target e-commerce business in the preset statistical segment, the initial business service attribute characteristics and the characteristics of the e-commerce big data can be considered, and the business service attribute is updated based on the characteristics, so the accuracy of subsequent e-commerce business recommendation is improved.

Description

Technical field [0001] The present disclosure relates to the field of big data technology, exemplarily, directed to a method and online e-commerce recommendation system based on the large data AI big data. Background technique [0002] With the Internet, the rapid development of cloud computing, ubiquitous mobile devices, RFID, wireless sensor are generating data every minute, hundreds of millions of Internet users are always a huge amount of data interaction occurs. And based on these, a large number of e-commerce industry generated structured and semi-structured data visualization, data analysis and data mining through other means, through the process and comprehensive consideration to help electricity companies to do business globally, systematic decisions, find solutions and operational decisions optimized, this is known as big data electricity supplier. The big data applications related to electronic commerce are attributed to this concept category. [0003] Recommended busi...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/02G06Q30/06
Inventor 李德财
Owner 李德财
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