CN109697253B - trade data analysis system based on big data - Google Patents

trade data analysis system based on big data Download PDF

Info

Publication number
CN109697253B
CN109697253B CN201811565555.5A CN201811565555A CN109697253B CN 109697253 B CN109697253 B CN 109697253B CN 201811565555 A CN201811565555 A CN 201811565555A CN 109697253 B CN109697253 B CN 109697253B
Authority
CN
China
Prior art keywords
module
data
trade
user
years
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Active
Application number
CN201811565555.5A
Other languages
Chinese (zh)
Other versions
CN109697253A (en
Inventor
袁利峰
林金英
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Zhuhai Hengqin Bringbuys Network Technology Co ltd
Original Assignee
Zhuhai Hengqin Kuajingshuo Network Technology Co Ltd
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Zhuhai Hengqin Kuajingshuo Network Technology Co Ltd filed Critical Zhuhai Hengqin Kuajingshuo Network Technology Co Ltd
Priority to CN201811565555.5A priority Critical patent/CN109697253B/en
Publication of CN109697253A publication Critical patent/CN109697253A/en
Application granted granted Critical
Publication of CN109697253B publication Critical patent/CN109697253B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q40/00—Finance; Insurance; Tax strategies; Processing of corporate or income taxes
    • G06Q40/04—Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

The invention discloses an trade data analysis system based on big data, which comprises a registration and login module, a master control module, a display module, a data acquisition module, a data analysis module, a data sorting module, a drawing module, a data comparison module, a data sending module and a big data calling module, wherein the registration and login module is in communication connection with the master control module, the display module is in communication connection with the master control module, the data acquisition module is in communication connection with the master control module, the data analysis module is in communication connection with the data acquisition module, and the data sorting module is in communication connection with the data analysis module.

Description

trade data analysis system based on big data
Technical Field
The invention belongs to the field of analysis, and relates to a big data utilization technology of trade data, in particular to kinds of trade data analysis systems based on big data.
Background
Trade refers to the generic term of buying and selling or trading behavior, generally refers to cut exchange activities or behaviors using currency as medium, the activity range thereof includes not only the commodity exchange activities engaged in by the trade, but also the commodity buying and selling activities organized by the commodity producer or others, including not only domestic trade, but also international trade between countries, the trade data refers to various information produced in the trade process, the trade data analysis system is a system for analyzing and processing the data produced in the trade process, and the function thereof is to let the user know the trade trend and the like.
The conventional trade data analysis system is easy to count invalid data in the process of analyzing trade data, so that the analyzed data has large deviation, a user cannot recommend a client capable of cooperating with key points when analyzing the trade data, meanwhile, the function is relatively simple , only data analysis is performed, the user cannot visually know the information content stored in the data, and solutions are proposed to solve the defects.
Disclosure of Invention
The invention aims to provide trade data analysis systems based on big data.
The technical problem to be solved by the invention is as follows:
(1) how to remove invalid data in the acquired data;
(2) how to better recommend a trader party capable of cooperating with deepening for a user;
(3) how to make the system have more functions;
the purpose of the invention can be realized by the following technical scheme:
trade data analysis system based on big data, which comprises a registration and login module, a master control module, a display module, a data acquisition module, a data analysis module, a data sorting module, a drawing module, a data comparison module, a data sending module and a big data calling module;
the registration and login module is in communication connection with the master control module, the display module is in communication connection with the master control module, the data acquisition module is in communication connection with the master control module, the data analysis module is in communication connection with the data acquisition module, the data sorting module is in communication connection with the data analysis module, the drawing module is in communication connection with the data sorting module, the data comparison module is in communication connection with the data sorting module, the data sending module is in communication connection with the data comparison module, and the big data calling module is in communication connection with the data comparison module;
the registration and login module is used for a user to register and log in the system, and the specific registration and login process is as follows:
, user needs to register when using the system ;
step two: the user needs to set up own login account number and password when registering the system, need to input repeatedly three times when setting up the password and verify when making things convenient for follow-up login, the concrete verification process when logging in is as follows:
s1: continuously inputting passwords for X times on the login module by a user, wherein X is a preset value, and X =1 … … n;
s2: the registration and login module records the time Qi, i =1 … … n for each password input by the user;
s3: obtaining the total time C of the input password by the formula Q1+ Q2+ Q2 … … + Qi = C;
s4: obtaining the average time S of each password input by the user through a formula C/X = S;
s5: marking the time for inputting the password when the user logs in the system subsequently as V;
s6: obtaining a time difference R through a formula S-V = R;
s7: when the numerical value of R is larger than the preset value, the user can normally log in the system as long as inputting the password;
s8: when R is smaller than a preset value, a user not only needs to input a login password, but also needs to perform short message authentication through the smart phone to normally login;
step three: the user needs to fill in personal name, identification number, company business license content and legal identification number during registration;
step four: after the registration, the user logs in the system through the account and the password set in the second step;
the general control module is used for controlling the data acquisition module, the display module is used for displaying login information of a user, the data acquisition module is used for acquiring company information of registration income of the user, and meanwhile, the data acquisition module can filter the acquired information, and the specific filtering information process is as follows:
step , the data collection module collects the annual transaction amount of the filled company and each trading party when the user registers, and the annual transaction amount of the company and each trading party is marked as Fi, i =1 … … n;
step two: arranging the Fi from large to small according to the numerical value;
step three: extracting the first N minimum Fi according to the formula Fimin+1－FiminK, obtaining a difference value K of the trade amount;
step four: when K is smaller than a preset value, the first N FIs can be filtered out;
step five: when K is larger than a preset value, the first N FIs cannot be filtered;
the data analysis module is used for analyzing the information acquired by the data acquisition module and selecting the second party who performs more years in years according to the analyzed information, and the specific selection process is as follows:
, the data acquisition module acquires the annual gross trade volume and the number of trade parties of the filled company when the user registers;
step two: marking the annual total trade amount as Z and the number of trade parties as S;
step three: obtaining the average annual trade amount M of each company through the formula Z/S = M;
step four: obtaining a difference value Pi between the single trade amount and the average trade amount by a formula | M-Fi | = P, wherein i =1 … … n;
arranging Pi from large to small according to the numerical values, and selecting n second parties with the numerical values closest to the front as key cooperation objects in the next years;
step six, the data analysis module extracts company Fimax with the maximum Fi value, and a party B corresponding to the Fimax can also be pushed as an object of key cooperation in years;
step seven: the data analysis module extracts the number of trades of each trading party and the company, and marks the number of trades as Gi, i =1 … … n;
step eight, arranging Gi according to the numerical value, and extracting a second party corresponding to the most front n Gi numerical values to be used as an object of key cooperation in the next years;
the data sorting module is used for sorting data analyzed by the data analysis module, the charting module is used for making contents sorted by the data sorting module into a table, the big data calling module is used for calling trade data in the previous year, the data comparison module can call the data in the previous year from the big data calling module for comparison and analysis to judge the trade trend in years, and the specific comparison and analysis process is as follows:
step , extracting the total amount of trading of each year within n years, and marking the total amount of trading as Ti according to the distance of the year from far to near, wherein i =1 … … n;
step two: extracting the number of trading parties of each year within n years, marking the trading parties as Di according to the distance of the annual fee, wherein i =1 … … n;
step three:by the formula Ti－Ti－1=Q1，Ti－1－Ti－2= Q2 get trade total difference between two years Q1 and Q2;
step four: obtaining a difference Q between trade total difference values by a formula Q1-Q2 = Q;
step five: by the formula Di－Di－1=M1，Di－1－Di－2= M2 get difference M1 and M2 between two years;
step six: obtaining the difference value M of the trade party through the formula M1-M2 = M;
step seven, when q is a positive value and m is a positive value, judging that the trading trend in years is not good enough, and a user needs to carry out the trade carefully;
step eight, when q is a negative value and m is a negative value, judging that the trade trend in years is good, and increasing the trade quantity by a preset value by a user;
step nine: when q is a negative value and m is a positive value and when q is a positive value and m is a negative value, the user needs to control the trade volume according to the current year market;
and the data sending module is used for sending the analyzed and sorted data to the intelligent mobile terminal of the user.
, the general control module is also used to control the data analysis module to analyze data, control the data arrangement module to arrange data, control the data comparison module to compare data, and control the data sending module to send communication information.
And , the chart module produces chart of the type including column chart, line chart, pie chart, bar chart and radar chart, and the display module displays the chart produced by the chart module.
The invention has the beneficial effects that:
(1) through the arranged data acquisition module, the data acquisition module can acquire and acquire the annual transaction amount of a filling company and each trading party when a user registers, mark the annual transaction amount of the filling company and each trading party as Fi (Fi), i =1 … … N, extract the minimum first N FIs, and extract the minimum annual transaction amount of the filling company and each trading party through a formula Fimin+1－FiminK, obtaining a difference value K of the trade amount; when K is smaller than a preset value, the first N FI can be filtered, and when K is larger than the preset value, the first N FI can not be filtered, so that the influence of undersized data on the total data can be effectively reduced, the situation that the total data has larger deviation due to the fact that the undersized data is mixed into the total data is avoided, and the analysis accuracy of the system is higher;
(2) through setting up the data comparison module, the data analysis module can all be analyzed by the data that the data acquisition module was gathered, obtain the difference Q between the total sum of trade difference through formula Q1-Q2 = Q, obtain the difference M of the difference of trade side through formula M1-M2 = M, the trade trend of years under can predicting according to the change of Q value and M value to the data analysis module, thereby let the company can the benefit maximize, this kind of setting up of predicting mode lets this system can evaluate in the while of analytical data, make this system possess more functions, can satisfy user's different user demands.
Drawings
To facilitate understanding by those skilled in the art, the present invention will be further described in conjunction with the accompanying drawings.
FIG. 1 is a block diagram of the system of the present invention.
Detailed Description
As shown in fig. 1, trade data analysis systems based on big data include a registration and login module, a master control module, a display module, a data acquisition module, a data analysis module, a data sorting module, a drawing module, a data comparison module, a data sending module, and a big data retrieving module;
the registration and login module is in communication connection with the master control module, the display module is in communication connection with the master control module, the data acquisition module is in communication connection with the master control module, the data analysis module is in communication connection with the data acquisition module, the data sorting module is in communication connection with the data analysis module, the drawing module is in communication connection with the data sorting module, the data comparison module is in communication connection with the data sorting module, the data sending module is in communication connection with the data comparison module, and the big data calling module is in communication connection with the data comparison module;
the registration and login module is used for a user to register and log in the system, and the specific registration and login process is as follows:
, user needs to register when using the system ;
step two: the user needs to set up own login account number and password when registering the system, need to input repeatedly three times when setting up the password and verify when making things convenient for follow-up login, the concrete verification process when logging in is as follows:
s1: continuously inputting passwords for X times on the login module by a user, wherein X is a preset value, and X =1 … … n;
s2: the registration and login module records the time Qi, i =1 … … n for each password input by the user;
s3: obtaining the total time C of the input password by the formula Q1+ Q2+ Q2 … … + Qi = C;
s4: obtaining the average time S of each password input by the user through a formula C/X = S;
s5: marking the time for inputting the password when the user logs in the system subsequently as V;
s6: obtaining a time difference R through a formula S-V = R;
s7: when the numerical value of R is larger than the preset value, the user can normally log in the system as long as inputting the password;
s8: when R is smaller than a preset value, a user not only needs to input a login password, but also needs to perform short message authentication through the smart phone to normally login;
step three: the user needs to fill in personal name, identification number, company business license content and legal identification number during registration;
step four: after the registration, the user logs in the system through the account and the password set in the second step;
the general control module is used for controlling the data acquisition module, the display module is used for displaying login information of a user, the data acquisition module is used for acquiring company information of registration income of the user, and meanwhile, the data acquisition module can filter the acquired information, and the specific filtering information process is as follows:
step , the data collection module collects the annual transaction amount of the filled company and each trading party when the user registers, and the annual transaction amount of the company and each trading party is marked as Fi, i =1 … … n;
step two: arranging the Fi from large to small according to the numerical value;
step three: extracting the first N minimum Fi according to the formula Fimin+1－FiminK, obtaining a difference value K of the trade amount;
step four: when K is smaller than a preset value, the first N FIs can be filtered out;
step five: when K is larger than a preset value, the first N FIs cannot be filtered;
the data analysis module is used for analyzing the information acquired by the data acquisition module and selecting the second party who performs more years in years according to the analyzed information, and the specific selection process is as follows:
, the data acquisition module acquires the annual gross trade volume and the number of trade parties of the filled company when the user registers;
step two: marking the annual total trade amount as Z and the number of trade parties as S;
step three: obtaining the average annual trade amount M of each company through the formula Z/S = M;
step four: obtaining a difference value Pi between the single trade amount and the average trade amount by a formula | M-Fi | = P, wherein i =1 … … n;
arranging Pi from large to small according to the numerical values, and selecting n second parties with the numerical values closest to the front as key cooperation objects in the next years;
step six, the data analysis module extracts company Fimax with the maximum Fi value, and a party B corresponding to the Fimax can also be pushed as an object of key cooperation in years;
step seven: the data analysis module extracts the number of trades of each trading party and the company, and marks the number of trades as Gi, i =1 … … n;
step eight, arranging Gi according to the numerical value, and extracting a second party corresponding to the most front n Gi numerical values to be used as an object of key cooperation in the next years;
the data sorting module is used for sorting data analyzed by the data analysis module, the charting module is used for making contents sorted by the data sorting module into a table, the big data calling module is used for calling trade data in the previous year, the data comparison module can call the data in the previous year from the big data calling module for comparison and analysis to judge the trade trend in years, and the specific comparison and analysis process is as follows:
step , extracting the total amount of trading of each year within n years, and marking the total amount of trading as Ti according to the distance of the year from far to near, wherein i =1 … … n;
step two: extracting the number of trading parties of each year within n years, marking the trading parties as Di according to the distance of the annual fee, wherein i =1 … … n;
step three: by the formula Ti－Ti－1=Q1，Ti－1－Ti－2= Q2 get trade total difference between two years Q1 and Q2;
step four: obtaining a difference Q between trade total difference values by a formula Q1-Q2 = Q;
step five: by the formula Di－Di－1=M1，Di－1－Di－2= M2 get difference M1 and M2 between two years;
step six: obtaining the difference value M of the trade party through the formula M1-M2 = M;
step seven, when q is a positive value and m is a positive value, judging that the trading trend in years is not good enough, and a user needs to carry out the trade carefully;
step eight, when q is a negative value and m is a negative value, judging that the trade trend in years is good, and increasing the trade quantity by a preset value by a user;
step nine: when q is a negative value and m is a positive value and when q is a positive value and m is a negative value, the user needs to control the trade volume according to the current year market;
and the data sending module is used for sending the analyzed and sorted data to the intelligent mobile terminal of the user.
The master control module is also used for controlling the data analysis module to perform data analysis, the data arrangement module to arrange data, the data comparison module to perform data comparison and the data sending module to send communication information; the types of the charts made by the drawing module comprise column charts, line charts, pie charts, bar charts and radar charts, and the display module displays the charts made by the drawing module.
trade data analysis system based on big data, in operation, the user logs on the system through the register and login module first, the register and login module can verify the user 'S identity in the login process, time difference R is obtained through formula S-V = R, the authenticity of the user' S identity is judged according to the value of R, after the verification is passed, the user can start to use the system, the master control module can control the data acquisition system to acquire the corresponding data of the user company first after the system starts to use, the data acquisition process can be realized through the Fi formulamin＋1－FiminK, to obtain a difference value K of the trade amount, and filter the invalid data according to the value K, the filtered data is sent to a data analysis module for data analysis, after the data is analyzed, the data analysis module feeds back the whole trade data to recommend a trading party with a higher added value to the user, the analyzed data is sent to the charting module to make a chart, the user selects to make a corresponding chart according to the own requirements, the made chart is displayed on the display module, the analyzed data is also sent to the data comparison module, the data comparison module can call the data stored in the big data storage module and combine the existing data for analysis, therefore, the future trade trend is analyzed, all feedback information can be summarized and sent to the intelligent mobile terminal of the user through the data sending module.
The invention has the following beneficial effects:
(1) by settingThe data acquisition module acquires and acquires the annual transaction amount of a filling company and each trading party when a user registers, marks the annual transaction amount of the filling company and each trading party as Fi (Fi), i =1 … … N, extracts the minimum first N FIs, and extracts the minimum first N FIs according to a formula Fimin+1－FiminThe difference K of the trade amount is obtained, the first N FIs can be filtered when the K is smaller than a preset value, and the first N FIs cannot be filtered when the K is larger than the preset value;
(2) through setting up the data comparison module, the data analysis module can all be analyzed by the data that the data acquisition module was gathered, obtain the difference Q between the total sum of trade difference through formula Q1-Q2 = Q, obtain the difference M of the difference of trade side through formula M1-M2 = M, the trade trend of years under can predicting according to the change of Q value and M value to the data analysis module, thereby let the company can the benefit maximize, this kind of setting up of predicting mode lets this system can evaluate in the while of analytical data, make this system possess more functions, can satisfy user's different user demands.
The foregoing is merely exemplary and illustrative of the present invention and various modifications, additions and substitutions may be made by those skilled in the art to the specific embodiments described without departing from the scope of the invention as defined in the following claims.

Claims (3)

  1. The trade data analysis system based on big data is characterized by comprising a registration and login module, a master control module, a display module, a data acquisition module, a data analysis module, a data sorting module, a drawing module, a data comparison module, a data sending module and a big data calling module;
    the registration and login module is in communication connection with the master control module, the display module is in communication connection with the master control module, the data acquisition module is in communication connection with the master control module, the data analysis module is in communication connection with the data acquisition module, the data sorting module is in communication connection with the data analysis module, the drawing module is in communication connection with the data sorting module, the data comparison module is in communication connection with the data sorting module, the data sending module is in communication connection with the data comparison module, and the big data calling module is in communication connection with the data comparison module;
    the registration and login module is used for a user to register and log in the system, and the specific registration and login process is as follows:
    , user needs to register when using the system ;
    step two: the user needs to set up own login account number and password when registering the system, need to input repeatedly three times when setting up the password and verify when making things convenient for follow-up login, the concrete verification process when logging in is as follows:
    s1: continuously inputting passwords for X times on the login module by a user, wherein X is a preset value, and X =1 … … n;
    s2: the registration and login module records the time Qi, i =1 … … n for each password input by the user;
    s3: obtaining the total time C of the input password by the formula Q1+ Q2+ Q2 … … + Qi = C;
    s4: obtaining the average time S of each password input by the user through a formula C/X = S;
    s5: marking the time for inputting the password when the user logs in the system subsequently as V;
    s6: obtaining a time difference R through a formula S-V = R;
    s7: when the numerical value of R is larger than the preset value, the user can normally log in the system as long as inputting the password;
    s8: when R is smaller than a preset value, a user not only needs to input a login password, but also needs to perform short message authentication through the smart phone to normally login;
    step three: the user needs to fill in personal name, identification number, company business license content and legal identification number during registration;
    step four: after the registration, the user logs in the system through the account and the password set in the second step;
    the general control module is used for controlling the data acquisition module, the display module is used for displaying login information of a user, the data acquisition module is used for acquiring company information of registration income of the user, and meanwhile, the data acquisition module can filter the acquired information, and the specific filtering information process is as follows:
    step , the data collection module collects the annual transaction amount of the filled company and each trading party when the user registers, and the annual transaction amount of the company and each trading party is marked as Fi, i =1 … … n;
    step two: arranging the Fi from large to small according to the numerical value;
    step three: extracting the first N minimum Fi according to the formula Fimin+1－FiminK, obtaining a difference value K of the trade amount;
    step four: when K is smaller than a preset value, the first N FIs can be filtered out;
    step five: when K is larger than a preset value, the first N FIs cannot be filtered;
    the data analysis module is used for analyzing the information acquired by the data acquisition module and selecting the second party who performs more years in years according to the analyzed information, and the specific selection process is as follows:
    , the data acquisition module acquires the annual gross trade volume and the number of trade parties of the filled company when the user registers;
    step two: marking the annual total trade amount as Z and the number of trade parties as S;
    step three: obtaining the average annual trade amount M of each company through the formula Z/S = M;
    step four: obtaining a difference value Pi between the single trade amount and the average trade amount by a formula | M-Fi | = P, wherein i =1 … … n;
    arranging Pi from large to small according to the numerical values, and selecting n second parties with the numerical values closest to the front as key cooperation objects in the next years;
    step six, the data analysis module extracts company Fimax with the maximum Fi value, and a party B corresponding to the Fimax can also be pushed as an object of key cooperation in years;
    step seven: the data analysis module extracts the number of trades of each trading party and the company, and marks the number of trades as Gi, i =1 … … n;
    step eight, arranging Gi according to the numerical value, and extracting a second party corresponding to the most front n Gi numerical values to be used as an object of key cooperation in the next years;
    the data sorting module is used for sorting data analyzed by the data analysis module, the charting module is used for making contents sorted by the data sorting module into a table, the big data calling module is used for calling trade data in the previous year, the data comparison module can call the data in the previous year from the big data calling module for comparison and analysis to judge the trade trend in years, and the specific comparison and analysis process is as follows:
    step , extracting the total amount of trading of each year within n years, and marking the total amount of trading as Ti according to the distance of the year from far to near, wherein i =1 … … n;
    step two: extracting the number of trading parties of each year within n years, marking the trading parties as Di according to the distance of the annual fee, wherein i =1 … … n;
    step three: by the formula Ti－Ti－1=Q1，Ti－1－Ti－2= Q2 get trade total difference between two years Q1 and Q2;
    step four: obtaining a difference Q between trade total difference values by a formula Q1-Q2 = Q;
    step five: by the formula Di－Di－1=M1，Di－1－Di－2= M2 get difference M1 and M2 between two years;
    step six: obtaining the difference value M of the trade party through the formula M1-M2 = M;
    step seven, when q is a positive value and m is a positive value, judging that the trading trend in years is not good enough, and a user needs to carry out the trade carefully;
    step eight, when q is a negative value and m is a negative value, judging that the trade trend in years is good, and increasing the trade quantity by a preset value by a user;
    step nine: when q is a negative value and m is a positive value and when q is a positive value and m is a negative value, the user needs to control the trade volume according to the current year market;
    and the data sending module is used for sending the analyzed and sorted data to the intelligent mobile terminal of the user.
  2. 2. The kinds of big data based trade data analysis systems of claim 1, wherein the general control module is further configured to control the data analysis module to perform data analysis, control the data arrangement module to arrange data, control the data comparison module to perform data comparison, and control the data transmission module to transmit communication information.
  3. 3. The big data-based trading data analysis system of claim 1, wherein the types of charts produced by the charting module include column charts, line charts, pie charts, bar charts, and radar charts, and the display module displays the charts produced by the charting module.
CN201811565555.5A 2018-12-20 2018-12-20 trade data analysis system based on big data Active CN109697253B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201811565555.5A CN109697253B (en) 2018-12-20 2018-12-20 trade data analysis system based on big data

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201811565555.5A CN109697253B (en) 2018-12-20 2018-12-20 trade data analysis system based on big data

Publications (2)

Publication Number Publication Date
CN109697253A CN109697253A (en) 2019-04-30
CN109697253B true CN109697253B (en) 2020-01-31

Family

ID=66232783

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201811565555.5A Active CN109697253B (en) 2018-12-20 2018-12-20 trade data analysis system based on big data

Country Status (1)

Country Link
CN (1) CN109697253B (en)

Families Citing this family (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112650317A (en) * 2020-12-18 2021-04-13 合肥阿格德信息科技有限公司 Integrated computer measurement and control system

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN102054025B (en) * 2010-12-01 2013-04-17 北京中交通信科技有限公司 Traffic information resource integration processing method and system
CN105760989A (en) * 2016-02-04 2016-07-13 济南市工商行政管理局历城分局 Geographic information system monitoring economic operation data
CN105809482A (en) * 2016-03-11 2016-07-27 郑州师范学院 Big data analysis system and method for cross-border trade
CN107633327A (en) * 2017-09-19 2018-01-26 飞友科技有限公司 A kind of terminal display system based on course line transport power big data

Also Published As

Publication number Publication date
CN109697253A (en) 2019-04-30

Similar Documents

Publication Publication Date Title
CN110263024A (en) Data processing method, terminal device and computer storage medium
CN108090823A (en) accounting data management system based on SaaS
US20050154769A1 (en) Systems and methods for benchmarking business performance data against aggregated business performance data
CN104123324B (en) Positioning and obtaining method and device for unread messages
CN1592901A (en) Systems and methods for monitoring credit of trading couterparties
CN111611487A (en) Stock information application analysis system
CN109697253B (en) trade data analysis system based on big data
CN112000862B (en) Data processing method and device
CN105956810A (en) Weighing manager
CN116611947A (en) Financial management audit system based on big data analysis
CN107944841A (en) Emolument computing system and method
CN108712463A (en) A kind of page interactive system
CN108108901A (en) Weekly wage delivery system and method
CN113610674A (en) Method, device and system for screening high-asset-value patents
CN115562964A (en) Simplified transmission system for electronic table card information
Zahrnt Domestic constituents and the formulation of WTO negotiating positions: what the delegates say
CN112632381B (en) Information query method and device, computer equipment and storage medium
WO2002099756A1 (en) Unified method for evaluating the efficiency of large-scale systems and automated device for carrying out said method
CN113435740A (en) Method, system, terminal and medium for client allocation according to service provider capacity
CN112053248A (en) Insurance exhibition system
CN107403503B (en) Invoice checking and comparing system
CN111667251A (en) Salary issuing method and device based on real-name system attendance data
Bıçakçı et al. The historical development of public relations in Turkey: The rise of a profession in times of social transformation
US20110112983A1 (en) Program trading platform
JP2020197811A (en) Safety awareness evaluation system

Legal Events

Date Code Title Description
PB01 Publication
PB01 Publication
SE01 Entry into force of request for substantive examination
SE01 Entry into force of request for substantive examination
TA01 Transfer of patent application right
TA01 Transfer of patent application right

Effective date of registration: 20200103

Address after: 519000 Guangdong city of Zhuhai province Hengqin Baohua Road No. 6, room 105 -9513

Applicant after: ZHUHAI HENGQIN BRINGBUYS NETWORK TECHNOLOGY Co.,Ltd.

Address before: 510000 Longan Cave Trade City C18-19, No. 1 Nandafen, Longdong Guangshan Road, Tianhe District, Guangzhou City, Guangdong Province

Applicant before: GUANGZHOU YUE'AN TRADING Co.,Ltd.

Applicant before: Lin Jinying

GR01 Patent grant
GR01 Patent grant
EE01 Entry into force of recordation of patent licensing contract
EE01 Entry into force of recordation of patent licensing contract

Application publication date: 20190430

Assignee: Hengqin Financial Investment International Finance Leasing Co.,Ltd.

Assignor: ZHUHAI HENGQIN BRINGBUYS NETWORK TECHNOLOGY Co.,Ltd.

Contract record no.: X2022980020392

Denomination of invention: A trade data analysis system based on big data

Granted publication date: 20200131

License type: Exclusive License

Record date: 20221108

PE01 Entry into force of the registration of the contract for pledge of patent right
PE01 Entry into force of the registration of the contract for pledge of patent right

Denomination of invention: A trade data analysis system based on big data

Effective date of registration: 20221110

Granted publication date: 20200131

Pledgee: Hengqin Financial Investment International Finance Leasing Co.,Ltd.

Pledgor: ZHUHAI HENGQIN BRINGBUYS NETWORK TECHNOLOGY Co.,Ltd.

Registration number: Y2022980021646

PC01 Cancellation of the registration of the contract for pledge of patent right
PC01 Cancellation of the registration of the contract for pledge of patent right

Date of cancellation: 20231228

Granted publication date: 20200131

Pledgee: Hengqin Financial Investment International Finance Leasing Co.,Ltd.

Pledgor: ZHUHAI HENGQIN BRINGBUYS NETWORK TECHNOLOGY Co.,Ltd.

Registration number: Y2022980021646

EC01 Cancellation of recordation of patent licensing contract
EC01 Cancellation of recordation of patent licensing contract

Assignee: Hengqin Financial Investment International Finance Leasing Co.,Ltd.

Assignor: ZHUHAI HENGQIN BRINGBUYS NETWORK TECHNOLOGY Co.,Ltd.

Contract record no.: X2022980020392

Date of cancellation: 20240103