WO2019000133A1

WO2019000133A1 - E-commerce data processing method

Info

Publication number: WO2019000133A1
Application number: PCT/CN2017/089913
Authority: WO
Inventors: 李楚斌
Original assignee: 深圳市秀趣品牌文化传播有限公司
Priority date: 2017-06-28
Filing date: 2017-06-28
Publication date: 2019-01-03

Abstract

An e-commerce data processing method, the method comprising: acquiring, from a telecommunication operator, access data of users using Internet services by means of a client (S10); classifying the access data according to a preset age division rule, and extracting access data corresponding to each age group (S11); acquiring, from the access data corresponding to each age group, keywords inputted by users using a search engine (S12); parsing the keywords inputted by users in the each age group using the search engine so as to obtain product keywords inputted by the users using the search engine (S13); calculating the probability of the product keywords inputted by the users in the each age group using the search engine (S14); calculating the product preferences of users in the each age group according to the probability of the product keywords (S15); and sending product information to users according to the product preferences thereof (S16). By using the described method, product information may be sent to users according to the product preferences thereof.

Description

Invention Name: E-commerce data processing method

Technical field

[0001] The present invention relates to the field of electronic commerce information technology, and in particular, to an e-commerce data processing method.

Background technique

[0002] In recent years, with the rapid development of the Internet, cloud computing, mobile communications, and the Internet of Things, ubiquitous mobile devices, RFID, and wireless sensors are generating data every minute, and hundreds of millions of users' Internet services吋吋Engraved in the production of huge amounts of interaction, the amount of data to be processed is huge, the data has been growing at a rate of 50% per year, and business demand and competitive pressure put forward higher requirements for the practicality and effectiveness of data processing. Traditional traditional techniques cannot be dealt with at all. Therefore, Big Data has become a recent technology hotspot and has attracted widespread attention.

[0003] Big data technology can speed up the search for information that is valuable to users. However, the current e-commerce system analyzes and processes e-commerce data, and does not consider the factors that users use the search engine. In the era of big data on the network, the risk of e-commerce companies is increased.

technical problem

[0004] The main object of the present invention is to provide an e-commerce data processing method, which aims to solve the technical problem that the existing e-commerce system does not perform commodity push based on the search engine.

Problem solution

Technical solution

[0005] In order to achieve the above object, the present invention provides an e-commerce data processing method, which is applied to a data center, the data center is connected to a telecommunication operator through a network, and the telecommunication operator communicates with the customer through the network. End connection, the method includes:

Obtaining, from a telecommunications carrier, access data of a user using an Internet service through the client;

[0007] classifying the access data according to a preset annual segmentation rule, and extracting access data corresponding to each year segment;

[0008] obtaining a keyword input by the user using the search engine from the access data corresponding to each year; [0009] parsing the keyword input by the user in each year segment using the search engine to obtain each year The product keyword entered by the user in the segment using the search engine;

[0010] calculating a probability of a product keyword entered by a user using a search engine in each year; and

[0011] calculating, according to the probability of the commodity keyword, the user preference of the user in each year segment;

[0012] The product information is transmitted to the user according to the user's product preferences.

[0013] Preferably, the access data includes an access time, a visiting website, a keyword input by using a search engine, network traffic, and user information using an Internet service, where the user information includes a user name, an age, and a height. , occupation, education, home address, telephone number and email address.

[0014] Preferably, the preset annual segment division rule refers to dividing a person's life into a plurality of years by using a preset year.

Advantageous effects of the invention

Beneficial effect

[0015] The e-commerce data processing method of the present invention combines the keywords input by the user using the search engine to understand the user's product preferences, and transmits the product information to the user according to the user's product preferences.

Brief description of the drawing

DRAWINGS

1 is a flow chart of a preferred embodiment of an e-commerce data processing method of the present invention.

BEST MODE FOR CARRYING OUT THE INVENTION

[0017] Referring to FIG. 1, a flow chart of a preferred embodiment of the e-commerce data processing method of the present invention is shown. In this embodiment, the e-commerce data processing method is applied to a data center, and the method includes the following steps:

[0018] Step S10: Obtaining, by the telecommunication operator, access data of the user using the Internet service through the client

[0019] Specifically, the telecommunication operator provides an API interface, and the device or system that accesses the API interface can obtain the access data from the telecommunication carrier. The API interface provided by the telecommunications carrier is invoked to obtain the access data.

[0020] It should be noted that, since the access data belongs to private information, in order to ensure information security, the access data is sent to the data center, and the encryption and decryption algorithm is adopted (for example, the MD5 encryption and decryption algorithm, RSA) The encryption and decryption algorithm, the DES encryption and decryption algorithm, the DSA encryption and decryption algorithm, the AES encryption and decryption algorithm, etc.) first encrypt the access data and then transmit it to the data center.

[0021] Step S11: classify the access data according to a preset annual segmentation rule, and extract access data corresponding to each year segment. The predetermined year-end division rule is to divide the life of a person into a plurality of years by starting with a preset age (for example, 18 years old). For example, at the age of 18, the starting point is divided. Among them, 18-34 years old are young, 35-45 years old are middle-aged, 45-60 are middle-aged, and 60-year old are old. The extracting module 210 extracts the years in the user information, and classifies the access data according to a preset annual segmentation rule, because the user data is included in the access data.

[0022] Step S12: Obtain a keyword input by the user using the search engine from the access data corresponding to each year.

[0023] Step S13: Parsing the keywords input by the user in the search engine using the keyword input by the search engine in each year segment to obtain the product keyword input by the user in each year. Specifically, the keywords input by the user in each year segment are compared with the preset product keywords, and if the input keyword is the same as the preset product keyword, the keyword is Product keyword.

[0024] Step S14: Calculate the probability of the product keyword input by the user in the search engine using the search engine in each year.

[0025] Step S15: Calculate the user preference of the user in each year segment according to the probability of the commodity keyword.

[0026] Step S16: Send the product information to the user according to the user's product preference.

[0027] The e-commerce data processing method of the present invention combines the keywords input by the user using the search engine to understand the user's product preferences, and transmits the product information to the user according to the user's product preferences.

Industrial applicability

[0028] The e-commerce data processing method of the present invention combines the keywords input by the user with the search engine to understand the user's product preferences, and transmits the product information to the user according to the user's product preferences.

Claims

Claim

[Claim 1] An e-commerce data processing method is applied to a data center, wherein the data center is connected to a telecommunication operator through a network, and the telecommunication operator connects to the client through the network, The method includes:

Obtaining, by the telecommunication operator, access data of the user using the Internet service by the client; classifying the access data according to a preset annual segmentation rule, and extracting access data corresponding to each year segment;

Obtaining keywords input by the user using the search engine from the access data corresponding to each year;

The keywords input by the user in the search engine are used in each year to obtain the keyword of the product input by the user in each year segment using the search engine;

Calculating the probability of the product keyword input by the user in each year segment using the search engine; and calculating the user preference of the user in each year segment according to the probability of the product keyword; sending the product information to the user according to the user's product preference .

[Claim 2] The e-commerce data processing method according to claim 1, wherein the access data includes an access time, a visiting web address, a keyword input using a search engine, network traffic, and use of an Internet service. User information, wherein the user information includes a user name, age, height, occupation, education, home address, telephone number, and email address.

[Claim 3] The quotient data processing method according to claim 1, wherein the preset annual segmentation rule refers to dividing a person's life into a plurality of years by using a preset year.