Automobile after-sale service recommendation method and system

A service recommendation, automotive technology, applied in instruments, data processing applications, computing, etc.

Inactive Publication Date: 2016-03-09
SHENZHEN TIANHANGJIA TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, how to recommend the most suitable and valuable car after-sales service to different

Method used

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  • Automobile after-sale service recommendation method and system
  • Automobile after-sale service recommendation method and system

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Embodiment Construction

[0035] The present invention will be further described below in conjunction with the accompanying drawings and preferred embodiments.

[0036]The specific embodiment of the present invention provides a car after-sales service recommendation system, which is used to recommend suitable car after-sales services to users at an appropriate time. module, tree decision maker building module, user portrait building module, post-service recommendation module and physical store recommendation module.

[0037] The data collection module is used to grab the discussion information related to the car after-sales service through the web crawler technology. For example, grabbing the discussion information related to the car after-sales service from forums, blogs, question-and-answer systems, social networks, etc. on the Internet can be stored in a NoSQL (non-relational database) storage method to facilitate the use of distributed environment for big data mining. The discussion information r...

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Abstract

The present invention discloses an automobile after-sale service recommendation method and system. The system comprises a data acquisition module, an automobile basic data knowledge base building module, a pattern sequence generation module, a treelike decider building module, a user portrait building module, an after-sale service recommendation module and a physical store recommendation module, wherein the pattern sequence generation module automatically generates an extraction rule according to an automobile basic data knowledge base, and performs feature extraction and normalization on related discussed information of automobile after-sale services to enable each datum to be formalized into a pattern sequence; the user portrait building module adopts statistical information, hypothesis verification and significance analysis to obtain a plurality of distribution patterns of automobile after-sale service consumption of a user, so as to build a user portrait; the after-sale service recommendation module inputs a user vehicle feature set and the user portrait to a treelike decider, and recommends N paths with high matching degrees as service schemes to the user; and the physical store recommendation module recommends M optimal physical stores to the user for each automobile after-sale service.

Description

technical field [0001] The invention relates to the field of car after-sales service recommendation, in particular to a method and system for car after-sales service recommendation based on big data. Background technique [0002] There are more and more car owners in today's society, and many people choose to drive to the airport by themselves. However, due to the limited parking spaces at the airport and the high price, and the parking lots around the airport have not been effectively used due to distance and other reasons, it is difficult for car owners who drive to the airport by themselves. The airport valet parking just solves the problem of car owners parking at the airport and returning to pick up the car. The current airport valet parking service process is roughly as follows: the car owner places an order through the WeChat platform or the valet driving app before the trip, and the system assigns the valet driver to wait for the car owner to park at the terminal acc...

Claims

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Application Information

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IPC IPC(8): G06Q30/02G06Q50/10
Inventor 张磊钟小武
Owner SHENZHEN TIANHANGJIA TECH CO LTD
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