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Method and system for recommendation based on O2O data

A technology for recommending methods and data, applied in the field of information processing, and can solve problems such as poor user experience

Inactive Publication Date: 2018-05-11
家园网络科技有限公司
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] At present, traditional recommendation systems are generally based on online user transaction data, and obtain user preferences based on online user transaction data, so as to make recommendations based on user preferences. This recommendation method usually only considers online user transactions. data, regardless of offline factors, such as the location and distance of offline service stores and other information. For example, if the recommended service is too far away from the user, the user is likely to give up consumption, resulting in poor user experience

Method used

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  • Method and system for recommendation based on O2O data
  • Method and system for recommendation based on O2O data

Examples

Experimental program
Comparison scheme
Effect test

Embodiment 1

[0057] figure 1It is a flowchart of a recommendation method based on O2O data provided in Embodiment 1 of the present invention.

[0058] refer to figure 1 , the method includes the following steps:

[0059] Step S101, collecting business data information, and updating the business data information within a preset time;

[0060] Here, the service data information includes user data information, user consumption data information and item data information; user data information, user consumption data information and item data information specifically include the following information. In the process of collecting service data information, it is necessary to judge whether the service data information is accessed for the first time or not for the first time.

[0061] If it is the first access, use ETL (or scheduled task JOB) to batch collect all information of C-type users, all information of C-type consumption data, coupons and all information of the merchants they belong to, ...

Embodiment 2

[0112] image 3 API flow chart provided for Embodiment 2 of the present invention.

[0113] refer to image 3 , the recommendation result table API (Application Programming Interface, application programming interface) needs to distinguish between old and new users. If it is an old user and has offline consumption records before, it can have recommendation results; if it is a new user and has no consumption records , you can only make recommendations according to rules (based on location).

[0114] The method includes the following steps:

[0115] Step S201, API request entry, the input parameters are user ID, longitude and latitude of merchant location, recommended quantity C and province and city where merchant is located;

[0116] Step S202, query the city where the user is located, and a list of all merchants to be recommended;

[0117] Step S203, judging whether the number of merchants in the merchant list is greater than 0, if greater than 0, then take the nth page d...

Embodiment 3

[0133] Figure 4 A schematic diagram of a recommendation system based on O2O data provided in Embodiment 3 of the present invention.

[0134] refer to Figure 4 , the system consists of:

[0135] refer to Figure 4 , the system includes a first update unit 10 , a statistical unit 20 , a calculation unit 30 , an interest degree acquisition unit 40 and a preference degree unit 50 .

[0136] The first updating unit 10 is configured to collect business data information and update the business data information within a preset time;

[0137] The statistical unit 20 is used to count the consumption data information, the consumption data information includes the number of users consuming by each merchant, the number of users who consume in different merchants by the same user, and the consumption times of each user in different merchants;

[0138] A calculation unit 30, configured to calculate the number of users who consume at each merchant and the number of users who consume at ...

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Abstract

The present invention provides a method and a system for recommendation based on O2O data. The method comprises the steps of: collecting business data information, and updating the business data information in a preset time; performing statistics of consumption data information, wherein the consumption data information comprises the number of users who perform consumption in each merchant, the number of users who each performs consumption in different merchants and the number of times of consumption of each user in different merchants; calculating the number of users who perform consumption ineach merchant and the number of users who each performs consumption in different merchants, and obtaining a cosine similarity; obtaining the users' interest degrees according to the number of times of consumption of each user in different merchants; and obtaining the users' preference degrees according to the users' interest degrees and a distance weight model. The method and the system for recommendation based on O2O data can provide more accurate recommendation service so as to improve the user experience.

Description

technical field [0001] The present invention relates to the technical field of information processing, in particular to a recommendation method and system based on O2O data. Background technique [0002] At present, traditional recommendation systems are generally based on online user transaction data, and obtain user preferences based on online user transaction data, so as to make recommendations based on user preferences. This recommendation method usually only considers online user transactions. Data, regardless of offline factors, such as the location and distance of offline service stores and other information, for example, if the recommended service is too far away from the user, the user is likely to give up consumption, resulting in poor user experience. Contents of the invention [0003] In view of this, the purpose of the present invention is to provide a recommendation method and system based on O2O data, which can provide more accurate recommendation services a...

Claims

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Application Information

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IPC IPC(8): G06Q30/06G06Q30/02G06F17/30
CPCG06Q30/0255G06Q30/0631G06F16/2462
Inventor 刘津防
Owner 家园网络科技有限公司
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