Output method, system and server of recommendation information

A recommended information and server technology, applied in the network field, can solve problems such as heavy manual operation workload, mismatch between recommended information and recommended time, and achieve the effect of increasing transmission speed, reducing information input, and reducing transmission volume

Active Publication Date: 2012-02-08
ALIBABA GRP HLDG LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] The purpose of the embodiment of the present application is to provide a method, system and server for outputting recommendation information, so as to solve the problems in the prior art that the output recommendation information does not match the recommendation time, and the manual operation causes a large workload

Method used

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  • Output method, system and server of recommendation information
  • Output method, system and server of recommendation information
  • Output method, system and server of recommendation information

Examples

Experimental program
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no. 1 example

[0031] see figure 1 , which is the flow chart of the first embodiment of the output method of recommendation information in this application:

[0032] Step 101: Extract user behavior data within a preset statistical period from the user behavior database.

[0033] The behavior data of all users’ operations on commodities will be saved in the user behavior database. The types of user behavior data include the number of clicks on commodities, the number of browsing times, the browsing time, the purchase amount, and the purchase quantity. Every time the interface completes a user action, the server saves the action data triggered by the user action into an entry corresponding to the user in the action database.

[0034] In the user behavior database, different user behavior data for the same product may be stored in different basic tables. When the user behavior data needs to be processed, the user behavior database can be searched according to the start time and end time of the...

no. 2 example

[0044] see figure 2 , which is the flow chart of the second embodiment of the output method of recommendation information in this application:

[0045] Step 201: Extract user behavior data within a preset statistical period from the user behavior database.

[0046] The behavior data of all users’ operations on commodities will be saved in the user behavior database. The types of user behavior data include the number of clicks on commodities, the number of browsing times, the browsing time, the purchase amount, and the purchase quantity. Every time the interface completes a user action, the server saves the action data triggered by the user action into an entry corresponding to the user in the action database.

[0047] In the embodiment of the present application, the processing of user behavior data can be started according to a trigger command input by the system, or can be automatically processed according to a preset time interval. In the user behavior database, differen...

no. 1 example

[0096] see Figure 4 , which is a block diagram of the first embodiment of the output server of the recommendation information of this application:

[0097] The server includes: an extraction unit 410 , a classification unit 420 , a calculation unit 430 , a receiving unit 440 and an output unit 450 .

[0098] Wherein, the extracting unit 410 is configured to extract user behavior data within a preset statistical period from the user behavior database;

[0099] A classification unit 420, configured to classify the user behavior data according to commodity identifiers, and obtain a time series of interest levels of each commodity within the statistical period;

[0100] A calculation unit 430, configured to calculate the peak purchase probability of the product according to the time series of the degree of interest;

[0101] a receiving unit 440, configured to receive an order for outputting recommendation information;

[0102] The output unit 450 is configured to sort the pur...

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Abstract

The invention discloses an output method, system and server of recommendation information. The method comprises the following steps of: extracting user action data in a predetermined statistic period from a user action database; classifying the user action data according to commodity identifications to obtain a time sequence about interestingness of each commodity in the statistic period; computing a purchase peak probability of the commodity according to the time sequence about interestingness; when receiving a command of outputting the recommendation information, sorting the purchase peak probability according to an order from high to low, and outputting the recommendation information of the commodity according to a sorting result. The method provided by the invention automatically computes the purchase peak probability of the commodity on time dimension according to the user action data, thereby improving the recommendation accuracy of a recommendation system and reducing the transmission quantity of unnecessary data in the network; since the recommendation information is automatically modified and output by a server, and the computation capability of the server is sufficiently used, the information input quantity and computation resource of the recommendation system can be reduced when the recommendation information is adjusted according to the purchase peak probability.

Description

technical field [0001] The present application relates to the field of network technology, in particular to a method, system and server for outputting recommendation information. Background technique [0002] Online shopping has become a common way of shopping in people's lives. When users browse products and choose shopping on the website, the recommendation engine server of the website may recommend popular products to users, and present the relevant information of these popular products on the webpage. A specific location for the user to choose from. In the prior art, when outputting recommended product information, recommendations are only made according to the sales information of the product or the user's interest information (for example: clicks or page views). For example, if the historical purchase volume of a certain product exceeds a certain value , then recommend the product information to the user, or, if the number of clicks on a certain product exceeds a cert...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06Q30/00G06F17/30H04L29/06
CPCG06Q30/00G06Q30/0631G06F16/24578
Inventor 肖铨武苏宁军谭昶刘淇张金银陈恩红
Owner ALIBABA GRP HLDG LTD
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