CN112598431A - Transaction platform list-swiping detection system - Google Patents
Transaction platform list-swiping detection system Download PDFInfo
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- CN112598431A CN112598431A CN202011629319.2A CN202011629319A CN112598431A CN 112598431 A CN112598431 A CN 112598431A CN 202011629319 A CN202011629319 A CN 202011629319A CN 112598431 A CN112598431 A CN 112598431A
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- G06Q30/00—Commerce
- G06Q30/06—Buying, selling or leasing transactions
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Abstract
The invention discloses a transaction platform bill-swiping detection system, and relates to the technical field of bill-swiping detection. The system comprises a transaction platform background data unit, a shop data unit and a user APP data unit, wherein the transaction platform background data unit is connected with the user APP data unit, the transaction platform background data unit is connected with the shop data unit, the transaction platform background data unit comprises a shop data collection module, a user APP data collection module and a data comparison module, and the shop data unit comprises a shop visit amount module, a shop transaction amount data module, a shop collected data module, a shop commodity collected data module and a shop data uploading module. The method and the system are convenient for simultaneously collecting the background data of the shop and the APP data of the user, carrying out comparison on various data, comprehensively comparing the abnormal behaviors of the user and the shop, and further improving the probability of detecting the order swiping.
Description
Technical Field
The invention belongs to the technical field of bill-swiping detection, and particularly relates to a bill-swiping detection system of a transaction platform.
Background
With the rapid development of the e-commerce industry, online shopping gradually becomes a new life style, the competition of the e-commerce industry is more and more intense, the e-commerce behavior gradually becomes a 'latent rule' of the e-commerce platform under the drive of benefits, and as the e-commerce service is developing and various constraint specifications are incomplete, the brushing of the e-commerce platform is more serious, and the network market balance is seriously damaged.
Disclosure of Invention
The invention aims to provide a transaction platform bill-swiping detection system which is convenient for collecting shop background data and user APP data at the same time, carrying out comparison on various data and comprehensively comparing abnormal behaviors of a user and a shop, further improving the probability of detecting the bill-swiping and solving the problems in the prior art.
In order to achieve the purpose, the invention is realized by the following technical scheme:
a transaction platform bill-swiping detection system comprises a transaction platform background data unit, a shop data unit and a user APP data unit;
the transaction platform background data unit is connected with the user APP data unit and the shop data unit;
the transaction platform background data unit comprises a shop data collection module, a user APP data collection module and a data comparison module;
the shop data unit comprises a shop visit amount module, a shop transaction amount data module, a shop collected data module, a shop commodity collected data module and a shop data uploading module;
the user APP data unit comprises a commodity collection data module, a shop collection data module, a comment data collection module, an offline frequency statistical data module, a commodity purchasing type data module and a user APP data uploading module;
the data comparison module compares data and judges that the data is abnormal when the data exceeds a set threshold, and the data is suspected to be refreshed when the abnormal behavior reaches an abnormal time threshold, and judges that the data is refreshed when the data exceeds a multiple threshold of the abnormal time threshold;
and when the suspicion frequency of the bill brushing exceeds the suspicion frequency threshold value, judging to brush the bill.
Optionally, the shop visit amount module is used for collecting visit time data, hourly visit amount data and daily visit amount data;
the shop trading volume data module is used for collecting trading time data, hourly trading volume data and daily trading data.
Optionally, the store collected data module is used for collecting store collected time data, store collected number data per hour and store collected data per day;
the store commodity collection data module is used for collecting store commodity collection time data, store commodity collection number per hour data and store commodity collection data per day.
Optionally, the commodity collection data module is configured to collect total data of the commodities collected in the last thirty days and total data of the commodities collected in the current day.
Optionally, the store collection data module is configured to collect data of total number of stores collected in the last thirty days and data of total number of stores collected in the current day.
Optionally, the offline frequency statistical data module is configured to collect the number of times that the user APP is offline for a short time due to switching between other applications when the user APP checks the product but does not purchase the product, and the number of times that the user APP is offline for a short time due to switching between the user APP checking the product and purchasing the product and switching between other applications.
Optionally, the favorable comment data collection module is configured to collect historical manual favorable comment total data and manual favorable comment total data in the last thirty days;
the purchased commodity category data module is used for collecting historical purchased commodity category data.
Optionally, the store data uploading module uploads the collected data to the store data collecting module, and the store data collecting module receives the data uploaded by the store data uploading module.
Optionally, the user APP data uploading module uploads the collected data to the user APP data collecting module, and the user APP data collecting module receives the data uploaded by the user APP data uploading module.
Optionally, the data comparison module compares the time of the time data with the working time, compares the current hourly data with the historical hourly average data, and compares the current-day data with the historical daily average data;
comparing the total data of the commodities collected on the same day with the average of the total data of the commodities collected in the last thirty days divided by thirty;
comparing the total data of the commodities collected on the same day with the average of the total data of the stores collected in the last thirty days divided by thirty;
dividing the historical manual favorable total data by the number of using days and multiplying by thirty to compare with the manual favorable total data of the last thirty days;
comparing the offline times with the set times;
comparing the current purchased commodity type with historical purchased commodity type data;
the data for the day is working day data, and the data for the day is rest day data.
The embodiment of the invention has the following beneficial effects:
according to the embodiment of the invention, the store background data and the user APP data can be conveniently collected at the same time, multiple data comparison can be carried out, the abnormal behaviors of the user and the store can be comprehensively compared, and the probability of detecting the order swiping is further improved.
Of course, it is not necessary for any product in which the invention is practiced to achieve all of the above-described advantages at the same time.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this application, illustrate embodiments of the invention and, together with the description, serve to explain the invention and not to limit the invention. In the drawings:
FIG. 1 is a system flow diagram of an embodiment of the present invention;
FIG. 2 is a diagram of a background data unit of a transaction platform according to an embodiment of the invention;
FIG. 3 is a schematic diagram of a store data unit according to an embodiment of the invention;
fig. 4 is a schematic diagram of a user APP data unit according to an embodiment of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. The following description of at least one exemplary embodiment is merely illustrative in nature and is in no way intended to limit the invention, its application, or uses.
To maintain the following description of the embodiments of the present invention clear and concise, a detailed description of known functions and known components of the invention have been omitted.
Referring to fig. 1-4, in the present embodiment, a transaction platform billing detection system is provided, including: the system comprises a transaction platform background data unit, a shop data unit and a user APP data unit;
the transaction platform background data unit is connected with the user APP data unit and the shop data unit;
the transaction platform background data unit comprises a shop data collection module, a user APP data collection module and a data comparison module;
the shop data unit comprises a shop visit amount module, a shop transaction amount data module, a shop collected data module, a shop commodity collected data module and a shop data uploading module;
the user APP data unit comprises a commodity collection data module, a shop collection data module, a comment data collection module, an offline frequency statistical data module, a commodity purchasing type data module and a user APP data uploading module;
the data comparison module compares data and judges that the data is abnormal when the data exceeds a set threshold, and the data is suspected to be refreshed when the abnormal behavior reaches an abnormal time threshold, and judges that the data is refreshed when the data exceeds a multiple threshold of the abnormal time threshold;
and when the suspicion frequency of the bill brushing exceeds the suspicion frequency threshold value, judging to brush the bill.
The method is convenient for simultaneously collecting the background data of the shop and the APP data of the user, carries out comparison of various data, comprehensively compares the abnormal behaviors of the user and the shop, and then improves the probability of detecting the order swiping.
The shop visit amount module is used for collecting visit time data, hourly visit amount data and daily visit amount data;
the shop trading volume data module is used for collecting trading time data, hourly trading volume data and daily trading data.
The store collected data module of the embodiment is used for collecting store collected time data, store collected data per hour and store collected data per day;
the store commodity collection data module is used for collecting store commodity collection time data, store commodity collection number per hour data and store commodity collection data per day.
The commodity collection data module of the embodiment is used for collecting total data of commodities collected in the last thirty days and total data of commodities collected in the current day.
The store collection data module of the embodiment is used for collecting total data of stores collected in the last thirty days and total data of stores collected in the current day.
The offline frequency statistical data module of the embodiment is used for collecting the short-time offline times of the user APP caused by switching other applications when the user APP checks the commodity but does not purchase the commodity, and the short-time offline times of the user APP caused by switching other applications from the commodity checking of the user APP to the purchasing of the user APP.
The favorable comment data collection module is used for collecting historical manual favorable comment total data and manual favorable comment total data in the last thirty days;
the purchased commodity category data module is used for collecting historical purchased commodity category data.
The store data uploading module uploads the collected data to the store data collecting module, and the store data collecting module receives the data uploaded by the store data uploading module.
The user APP data upload module of this embodiment uploads the collected data to the user APP data collection module, and the user APP data collection module receives the user APP data upload module upload data.
The data comparison module of the embodiment compares the time of time data with the duty time, compares the current hourly data with the historical hourly average data, and compares the current day data with the historical daily average data;
comparing the total data of the commodities collected on the same day with the average of the total data of the commodities collected in the last thirty days divided by thirty;
comparing the total data of the commodities collected on the same day with the average of the total data of the stores collected in the last thirty days divided by thirty;
dividing the historical manual favorable total data by the number of using days and multiplying by thirty to compare with the manual favorable total data of the last thirty days;
comparing the offline times with the set times;
comparing the current purchased commodity type with historical purchased commodity type data;
the data for the day is working day data, and the data for the day is rest day data.
The above embodiments may be combined with each other.
It should be noted that the terms "first," "second," and the like in the description and claims of this application and in the drawings described above are used for distinguishing between similar elements and not necessarily for describing a particular sequential or chronological order. It is to be understood that the data so used is interchangeable under appropriate circumstances such that the embodiments of the application described herein are capable of operation in sequences other than those illustrated or described herein.
In the description of the present invention, it is to be understood that the orientation or positional relationship indicated by the orientation words such as "front, rear, upper, lower, left, right", "lateral, vertical, horizontal" and "top, bottom", etc. are usually based on the orientation or positional relationship shown in the drawings, and are only for convenience of description and simplicity of description, and in the case of not making a reverse description, these orientation words do not indicate and imply that the device or element being referred to must have a specific orientation or be constructed and operated in a specific orientation, and therefore, should not be considered as limiting the scope of the present invention; the terms "inner and outer" refer to the inner and outer relative to the profile of the respective component itself.
Claims (10)
1. A transaction platform billing detection system, comprising: the system comprises a transaction platform background data unit, a shop data unit and a user APP data unit;
the transaction platform background data unit is connected with the user APP data unit and the shop data unit;
the transaction platform background data unit comprises a shop data collection module, a user APP data collection module and a data comparison module;
the shop data unit comprises a shop visit amount module, a shop transaction amount data module, a shop collected data module, a shop commodity collected data module and a shop data uploading module;
the user APP data unit comprises a commodity collection data module, a shop collection data module, a comment data collection module, an offline frequency statistical data module, a commodity purchasing type data module and a user APP data uploading module;
the data comparison module compares data and judges that the data is abnormal when the data exceeds a set threshold, and the data is suspected to be refreshed when the abnormal behavior reaches an abnormal time threshold, and judges that the data is refreshed when the data exceeds a multiple threshold of the abnormal time threshold;
and when the suspicion frequency of the bill brushing exceeds the suspicion frequency threshold value, judging to brush the bill.
2. The trading platform billing detection system of claim 1, wherein the store visit volume module is configured to collect visit time data, hourly visit volume data, daily visit volume data;
the shop trading volume data module is used for collecting trading time data, hourly trading volume data and daily trading data.
3. The trading platform billing detection system of claim 2, wherein the store collected data module is configured to collect store collected time data, store collected number per hour data, and store collected data per day;
the store commodity collection data module is used for collecting store commodity collection time data, store commodity collection number per hour data and store commodity collection data per day.
4. The trading platform billing detection system of claim 3, wherein the commodity collection data module is configured to collect data on a total number of commodities collected in the last thirty days and a total number of commodities collected in the current day.
5. The trading platform billing detection system of claim 4, wherein the store collection data module is configured to collect data on the total number of stores collected in the last thirty days and the total number of stores collected in the current day.
6. The transaction platform billing detection system of claim 5, wherein the offline frequency statistics module is configured to collect the number of times that the user APP is offline for a short time due to the user APP viewing the merchandise but switching to another application for non-purchase, and the number of times that the user APP is offline for a short time due to the user APP viewing the merchandise and switching to another application for purchase.
7. The trading platform billing detection system of claim 6, wherein the opinion data collection module is configured to collect historical manual opinion total data, the last thirty days manual opinion total data;
the purchased commodity category data module is used for collecting historical purchased commodity category data.
8. The trading platform billing detection system of claim 7, wherein the store data upload module uploads the collected data to the store data collection module, and the store data collection module receives the store data uploaded by the store data upload module.
9. The transaction platform billing detection system of claim 8, wherein the user APP data upload module uploads the collected data to the user APP data collection module, and the user APP data collection module receives the user APP data upload module upload data.
10. The trading platform billing detection system of claim 9, wherein the data comparison module compares time data time to work time, current hourly data to historical hourly average data, and current-day data to historical daily average data;
comparing the total data of the commodities collected on the same day with the average of the total data of the commodities collected in the last thirty days divided by thirty;
comparing the total data of the commodities collected on the same day with the average of the total data of the stores collected in the last thirty days divided by thirty;
dividing the historical manual favorable total data by the number of using days and multiplying by thirty to compare with the manual favorable total data of the last thirty days;
comparing the offline times with the set times;
comparing the current purchased commodity type with historical purchased commodity type data;
the data for the day is working day data, and the data for the day is rest day data.
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| Application Number | Priority Date | Filing Date | Title |
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| CN202011629319.2A CN112598431A (en) | 2020-12-31 | 2020-12-31 | Transaction platform list-swiping detection system |
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| CN202011629319.2A CN112598431A (en) | 2020-12-31 | 2020-12-31 | Transaction platform list-swiping detection system |
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| CN112598431A true CN112598431A (en) | 2021-04-02 |
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- 2020-12-31 CN CN202011629319.2A patent/CN112598431A/en active Pending
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| CN106708476A (en) * | 2015-07-20 | 2017-05-24 | 腾讯科技（深圳）有限公司 | Stand-alone application instruction processing method and device |
| CN106204157A (en) * | 2016-07-24 | 2016-12-07 | 广东聚联电子商务股份有限公司 | Behavior processing method evaluated by a kind of brush list based on big data collection and analysis |
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