Order violation detection method, device, equipment and storage medium

Abstract

The present invention relates to the field of data processing technology, and discloses an order violation detection method, device, equipment and storage medium. The method sets corresponding monitoring rules according to different merchant types, sets monitoring tasks based on the monitoring rules to regularly monitor the update of logistics data of orders on each electrical commodity platform, obtains logistics data recorded in the logistics update node in each order through the monitoring rules, and checks whether the logistics records of each update record in the detected logistics data meet the conditions specified in the monitoring rules. If not, the order is determined to be in violation, and the violation events in the order are determined. Based on the violation events, the corresponding penalty method is selected to achieve constraints on each merchant, improve the delivery efficiency of the order, and ensure customer satisfaction. In addition, the present invention also relates to blockchain technology, and the monitoring rules and orders can be stored in the blockchain.

Description

Technical Field

[0001] The present application relates to the field of data processing technology, and specifically to an order violation detection method, device, equipment and storage medium. Background Art

[0002] With the development of Internet technology, especially with the normalization of Internet shopping and e-commerce platforms, in order to ensure the user experience, each shopping platform is required to promptly update the order's logistics information after the user places an order.

[0003] In the prior art, each shopping platform mainly monitors the order logistics information update based on the timeliness rules. After the user pays for the order, the system will scan the orders of the most recent period (such as 30 days) every morning according to the set timeliness rules to determine whether the order is a delayed delivery order and whether a penalty is required. However, this monitoring method is too simple and cannot be updated in a timely manner in complex shopping scenarios, thereby reducing the user experience. Summary of the invention

[0004] The main purpose of the present invention is to solve the technical problem that the existing order logistics update monitoring method is single and difficult to achieve compatible use in different scenarios.

[0005] A first aspect of the present invention provides an order violation detection method, characterized in that the order violation detection method comprises:

[0006] Collecting order information of users that have completed payment on the e-commerce platform, and sorting the order information in the order of payment time to obtain an order list to be monitored, wherein the order list includes at least one order information;

[0007] Using an OCR recognition algorithm, identifying the distribution platform corresponding to each order information in the order list, and generating a logistics distribution tree diagram corresponding to the order information based on the distribution plan of the distribution platform, to obtain a logistics update node set including the at least one order information;

[0008] According to the order list, determine the monitoring rules corresponding to each order information from the preset monitoring rule library, and generate a monitoring task list;

[0009] Running the monitoring rules in the monitoring task list, monitoring the logistics update node set of the order list, and obtaining monitoring results;

[0010] The violation events of each order are determined according to the monitoring results, and a corresponding penalty method is selected from the configured violation penalty methods based on the violation events.

[0011] Optionally, in a first implementation of the first aspect of the present invention, the order violation detection method further includes:

[0012] According to the merchant type, configure the first order delivery time limit, first logistics time limit and first violation penalty method corresponding to the merchant type on the rule configuration interface to generate merchant classification rules;

[0013] According to holidays, configure the second order delivery time limit, second logistics time limit and second violation penalty method for different holidays on the rule configuration interface to generate holiday rules;

[0014] According to the delivery area, configure the third-party order delivery time limit, third-party logistics time limit and third-party violation penalty method in different regions on the rule configuration interface to generate the delivery area rules;

[0015] According to the specific product category, the fourth order delivery time limit, fourth logistics time limit and fourth violation penalty method of different products are configured on the rule configuration interface to generate product category rules.

[0016] Optionally, in a second implementation of the first aspect of the present invention, the running of the monitoring rules in the monitoring task list to monitor the logistics update node set of the order list to obtain the monitoring results includes:

[0017] Extracting basic information from the order information, wherein the basic information includes product information and logistics data;

[0018] Calculate the violation time points of the order information based on the product information and logistics data, and merge all violation time points into pending data and add them to the pending queue;

[0019] The monitoring rules are executed regularly by means of a script, the data corresponding to the violation time point that has reached the update time in the queue to be processed is obtained, and it is determined whether the corresponding order is in violation, so as to obtain the monitoring result.

[0020] Optionally, in a third implementation of the first aspect of the present invention, the logistics data includes an order time and an actual delivery time;

[0021] The monitoring rules are executed regularly by means of a script, the data corresponding to the violation time point that has reached the update time in the queue to be processed is obtained, and the corresponding order is determined to be in violation, and the monitoring results obtained include:

[0022] Execute the monitoring rule to detect whether the order time is within a special time period, wherein the special time period is a specific sales time for commodities set by each e-commerce platform;

[0023] If the order placement time is within a special time period, then the logistics update time calculation rule corresponding to the special time period is obtained to calculate the actual update time of the order information within the special time period;

[0024] Compare the actual update time with the actual delivery time to obtain a comparison result;

[0025] Based on the comparison result, it is determined whether the corresponding order is in violation of the regulations, and a monitoring result is obtained.

[0026] Optionally, in a fourth implementation of the first aspect of the present invention, the logistics data further includes a delivery address;

[0027] After detecting that the order placement time is within the special time period, the method further includes:

[0028] Matching the delivery address with the pre-planned delivery area to determine its corresponding configuration area;

[0029] According to the delivery area, a corresponding logistics update rule is selected from a preset logistics update rule library;

[0030] Calculate the latest update time of the order information within the special time period according to the logistics update rule and the logistics update time calculation rule;

[0031] Compare the latest update time with the actual delivery time to obtain a comparison result;

[0032] Based on the comparison result, it is determined whether the corresponding order is in violation of the regulations, and a monitoring result is obtained.

[0033] Optionally, in a fifth implementation of the first aspect of the present invention, determining the violation event of each order according to the monitoring result, and selecting a corresponding penalty method from configured violation penalty methods based on the violation event includes:

[0034] Detecting the category corresponding to the product in the order information;

[0035] When the monitoring result is a violation of the pickup time, the corresponding penalty level classification is queried from the configured violation penalty method according to the category;

[0036] Calculate the percentage by which the actual delivery time exceeds the latest update time;

[0037] According to the percentage, the corresponding penalty level and penalty method are determined from the penalty level classification.

[0038] A second aspect of the present invention provides an order violation detection device, the order violation detection device comprising:

[0039] A collection module, used to collect order information of users that have completed payment on the e-commerce platform, and sort the order information in the order of payment time to obtain an order list to be monitored, wherein the order list includes at least one order information;

[0040] an identification module, configured to identify the distribution platform corresponding to each order information in the order list by using an OCR recognition algorithm, and generate a logistics distribution tree diagram corresponding to the order information based on the distribution plan of the distribution platform, to obtain a logistics update node set including the at least one order information;

[0041] A generating module, used to determine the monitoring rules corresponding to each of the order information from a preset monitoring rule library according to the order list, and generate a monitoring task list;

[0042] A monitoring module, used to run the monitoring rules in the monitoring task list, monitor the logistics update node set of the order list, and obtain monitoring results;

[0043] A selection module is used to determine the violation events of each order according to the monitoring results, and select a corresponding penalty method from the configured violation penalty methods based on the violation events.

[0044] Optionally, in a first implementation of the second aspect of the present invention, the order violation detection device further includes a rule configuration module, which is specifically used to:

[0045] According to the merchant type, configure the first order delivery time limit, first logistics time limit and first violation penalty method corresponding to the merchant type on the rule configuration interface to generate merchant classification rules;

[0046] According to holidays, configure the second order delivery time limit, second logistics time limit and second violation penalty method for different holidays on the rule configuration interface to generate holiday rules;

[0047] According to the delivery area, configure the third-party order delivery time limit, third-party logistics time limit and third-party violation penalty method in different regions on the rule configuration interface to generate the delivery area rules;

[0048] According to the specific product category, the fourth order delivery time limit, fourth logistics time limit and fourth violation penalty method of different products are configured on the rule configuration interface to generate product category rules.

[0049] Optionally, in a second implementation of the second aspect of the present invention, the monitoring module includes:

[0050] An extraction unit, used to extract basic information from the order information, wherein the basic information includes product information and logistics data;

[0051] A calculation unit calculates the violation time points of the order information according to the commodity information and logistics data, and combines all the violation time points into to-be-processed data and adds them into a to-be-processed queue;

[0052] The violation judgment unit is used to execute the monitoring rules regularly through scripts, obtain the data corresponding to the violation time point that has reached the update time in the queue to be processed, and determine whether the corresponding order is in violation to obtain the monitoring result.

[0053] Optionally, in a third implementation of the second aspect of the present invention, the logistics data includes an order time and an actual delivery time; and the violation judgment unit is specifically configured to:

[0054] Execute the monitoring rule to detect whether the order time is within a special time period, wherein the special time period is a specific sales time for commodities set by each e-commerce platform;

[0055] If the order placement time is within a special time period, then the logistics update time calculation rule corresponding to the special time period is obtained to calculate the actual update time of the order information within the special time period;

[0056] Compare the actual update time with the actual delivery time to obtain a comparison result;

[0057] Based on the comparison result, it is determined whether the corresponding order is in violation of the regulations, and a monitoring result is obtained.

[0058] Optionally, in a fourth implementation manner of the second aspect of the present invention, the logistics data further includes a delivery address; and the violation judgment unit is further specifically configured to:

[0059] Matching the delivery address with the pre-planned delivery area to determine its corresponding configuration area;

[0060] According to the delivery area, a corresponding logistics update rule is selected from a preset logistics update rule library;

[0061] Calculate the latest update time of the order information within the special time period according to the logistics update rule and the logistics update time calculation rule;

[0062] Compare the latest update time with the actual delivery time to obtain a comparison result;

[0063] Based on the comparison result, it is determined whether the corresponding order is in violation of the regulations, and a monitoring result is obtained.

[0064] Optionally, in a fifth implementation of the second aspect of the present invention, the selection module includes:

[0065] A detection unit, used to detect the category corresponding to the commodity in the order information;

[0066] A classification unit, for, when the monitoring result is a pickup violation time, querying a corresponding penalty level classification from the configured violation penalty methods according to the category;

[0067] A calculation unit, used for calculating the percentage by which the actual delivery time exceeds the latest update time;

[0068] A determination unit is used to determine a corresponding penalty level and a penalty method from the penalty level classification according to the percentage.

[0069] A third aspect of the present invention provides an order violation detection device, comprising: a memory and at least one processor, wherein instructions are stored in the memory, and the memory and the at least one processor are interconnected via a line;

[0070] The at least one processor calls the instructions in the memory to enable the order violation detection device to execute the above-mentioned order violation detection method.

[0071] A fourth aspect of the present invention provides a computer-readable storage medium, in which a computer program is stored, which, when executed on a computer, enables the computer to execute the above-mentioned order violation detection method.

[0072] In the technical solution provided by the present invention, corresponding monitoring rules are set according to different merchant types, and monitoring tasks are set based on the monitoring rules to periodically monitor the update of logistics data of orders on each e-commerce platform. Through the monitoring rules, the logistics data recorded in each order is obtained, and the logistics records of each updated record in the detected logistics data meet the conditions specified in the monitoring rules. If not, the order is determined to be in violation, and the violation events in the order are determined. Based on the violation events, the corresponding punishment method is selected to achieve constraints on each merchant, improve the delivery efficiency of the order, and ensure customer satisfaction. BRIEF DESCRIPTION OF THE DRAWINGS

[0073] Figure 1 This is a schematic diagram of a first embodiment of an order violation detection method in an embodiment of the present invention;

[0074] Figure 2 Schematic diagram of a second embodiment of the order violation detection method in an embodiment of the present invention;

[0075] Figure 3 Schematic diagram of a third embodiment of the order violation detection method in an embodiment of the present invention;

[0076] Figure 4Schematic diagram of a fourth embodiment of the order violation detection method in an embodiment of the present invention;

[0077] Figure 5 A schematic diagram of an embodiment of an order violation detection device in an embodiment of the present invention;

[0078] Figure 6 It is a schematic diagram of another embodiment of the order violation detection device in the embodiment of the present invention;

[0079] Figure 7 Schematic diagram of an embodiment of an order violation detection device in an embodiment of the present invention. DETAILED DESCRIPTION

[0080] In response to the above-mentioned problems, the present application proposes a method for monitoring order logistics updates based on multiple rules. First, corresponding monitoring rules are set according to different merchant types, and monitoring tasks are set based on the monitoring rules to periodically monitor the updates of logistics data of orders on each e-commerce platform. Through the monitoring rules, the logistics data recorded in each order is obtained, and the logistics records of each update record in the detected logistics data are checked to see whether they meet the conditions specified in the monitoring rules. If not, the order is determined to be in violation, and the violation events in the order are determined. Based on the violation events, the corresponding penalty method is selected to implement constraints on each merchant.

[0081] The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of the present invention and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchanged where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0082] For ease of understanding, the specific process of the embodiment of the present invention is described below. Figure 1 The first embodiment of the order violation detection method in the embodiment of the present invention includes:

[0083] 101. Collect order information of users that have completed payment on the e-commerce platform, and sort the order information in order of payment time to obtain an order list to be monitored, wherein the order list includes at least one order information;

[0084] In this embodiment, the interactive data in the transaction interface on the e-commerce platform is monitored through the order monitoring interface to collect the corresponding order information. Of course, it can also be obtained by monitoring the payment interface on the e-commerce platform.

[0085] In actual applications, the order data of a certain time period is retrieved from the backend database of the e-commerce platform by setting a timing, and some orders that have completed payment are filtered out from the order data, and these orders are sorted in chronological order of payment time to obtain a list of orders to be monitored.

[0086] Furthermore, when generating an order list, it also includes planning a corresponding delivery route for the delivery address in the order, setting monitoring nodes based on the delivery route, calculating the monitoring time of each monitoring node according to the monitoring rules of the order, and after sorting by payment time to obtain a first monitoring sequence, sorting the order data according to the monitoring time to obtain a second monitoring sequence, and combining the first monitoring sequence and the second monitoring sequence into an order list.

[0087] 102. Using an OCR recognition algorithm, identify the distribution platform corresponding to each order information in the order list, and generate a logistics distribution tree diagram corresponding to the order information based on the distribution plan of the distribution platform to obtain a logistics update node set containing at least one order information;

[0088] Among them, the OCR recognition algorithm is an optical symbol recognition technology. Specifically, the order information is scanned by a scanning device to obtain the distribution platform of each order information, that is, the express company, and then the corresponding logistics data update site is queried based on the delivery address of each order in the express company. The logistics distribution tree diagram of the order information is constructed based on the update site, and finally the logistics update nodes of all orders are integrated into a set. Furthermore, while forming the set, all logistics update nodes can be connected in series in chronological order to obtain a monitoring task sequence.

[0089] 103. According to the order list, determine the monitoring rule corresponding to each order information from a preset monitoring rule library, and generate a monitoring task list;

[0090] In this embodiment, the monitoring rule library is specifically implemented by configuring the merchant type's order delivery time, logistics time and violation penalty method, and then generating a monitoring task list based on the order delivery time and logistics time, wherein the monitoring task list includes at least one monitoring rule.

[0091] In this embodiment, when configuring the order delivery time limit, logistics time limit and violation penalty method, it can be specifically implemented through the configuration interface on the e-commerce platform, specifically by selecting different merchant types on the configuration interface, and filling in the product, monitoring node information, and the penalty items after the violation. Based on the selection and filling in the content on the configuration interface, the monitoring rules are generated, and optionally, the monitoring tasks are generated.

[0092] In actual applications, in addition to the above-mentioned custom configuration rules, it can also be achieved through automatic generation. First, the order information generated after the customer places an order is obtained, and the product information, delivery address, delivery amount and payment time in the order information are extracted. In addition, the merchant type of the merchant of the order is also required. Based on the above information, the corresponding monitoring rule template is matched, and the information obtained from the order is entered based on the monitoring rule template to generate the monitoring rules corresponding to the order.

[0093] Furthermore, before generating the monitoring rules, the latest update time of the logistics data of each node of the order is calculated based on the merchant type, product information and delivery address, and the monitoring rule template is filled in based on the latest update time to obtain a complete monitoring rule, which of course also includes the penalty method for the order after the monitoring violation.

[0094] In this step, the monitoring rules include at least one of merchant classification rules, holiday rules, delivery area rules, effective time rules and commodity category rules. The order delivery time refers to the latest delivery time of the platform or merchant after the customer places an order, or the latest time to update the logistics data after delivery, which is generally set to 24h and 48h. The logistics time refers to the latest time to update the logistics when the express flows to each node after delivery, which is generally set to 48h, 72h and 96h. Of course, in some embodiments, the logistics time can also be the latest time when the express is delivered to the customer, that is, the end time of the logistics.

[0095] A monitoring rule is generated based on the two information, and then the monitoring rule is added to the monitoring task list to obtain the monitoring task of the order.

[0096] In actual applications, the monitoring task may be a monitoring task formed by one monitoring rule in the monitoring list, or may be a monitoring task formed by multiple monitoring rules. Of course, one order information may also have multiple monitoring rules.

[0097] 104. Run the monitoring rules in the monitoring task list to monitor the order logistics corresponding to the order list to obtain monitoring results;

[0098] In this embodiment, the monitoring rules in the monitoring task list refer to monitoring the entry time of the logistics data record nodes in the order. Specifically, the logistics data in the order information is first collected. In actual applications, each logistics information in the order information is collected, and the entry time and corresponding node in each logistics information are extracted. The entry time and node are compared with the requirements in the monitoring rules, and the monitoring results are determined based on the comparison results.

[0099] In actual applications, when making a comparison, the monitoring rules are first executed. According to the time calculation method or calculation formula specified for each node in the rules, the latest logistics update time of each node in the order is calculated based on the payment time. The latest update time is compared with the entry time. If they are consistent, a monitoring result without abnormalities is output. If they are inconsistent, the latest update time is subtracted from the entry time. It is determined whether the difference is negative or an integer. A negative number is an abnormality, and an integer is not an abnormality. The monitoring result is output.

[0100] 105. Determine the violation events of each order according to the monitoring results, and select a corresponding penalty method from the configured violation penalty methods based on the violation events.

[0101] In this step, the monitoring results here are delayed calculation judgments, so the monitoring results can include multiple conclusions, each of which corresponds to an event. The corresponding violation events are determined by extracting the conclusions in the monitoring results. The violation events specifically refer to the node locations where logistics violations exist in the order, and the violation specifically refers to the update time timeout. The penalty method is determined based on the extracted records.

[0102] In actual applications, when determining the penalty method, it can be specifically determined by judging the violation level of the violation event, and selecting the corresponding penalty method based on the violation level. For example: if the goods are not shipped within 24 hours of payment, the merchant will be fined 10 yuan of deposit, and this amount will be returned to the buyer of the order in the form of a shopping fund. If the goods are not shipped within 48 hours of payment, the order will be closed directly, and the payment will be returned to the buyer in a timely manner. If there is no logistics information within 48 hours of payment, the merchant will be fined 10 yuan of deposit, and this amount will be returned to the buyer of the order in the form of a shopping fund. If there is no logistics information within 96 hours of payment, the order will be closed directly, and the payment will be returned to the buyer in a timely manner. If there is the first logistics information within 48 hours of payment, but there is no transit information within 72 hours of payment, the merchant will be fined 20 yuan of deposit, and this amount will be returned to the buyer of the order in the form of a shopping fund.

[0103] By implementing the method provided above, using delayed statistical calculations and diversified rule templates, it is possible to handle violations for specific business types, formulate rules according to the time limit for violations, and handle logistics-related scenarios such as major events, holidays, and major activities more fairly and reasonably. Merchants can be managed and punished more reasonably and fairly, which improves the accuracy of logistics violation judgments, improves the calculation efficiency of breach of contract processing, reduces operating labor costs, and also helps encourage merchants to improve the quality of delivery logistics services and increase customer satisfaction.

[0104] See also Figure 2 , a second embodiment of the order violation detection method in the embodiment of the present invention includes:

[0105] 201. Collecting order information of users that have completed payment on the e-commerce platform, and sorting the order information in order of payment time to obtain a list of orders to be monitored;

[0106] In this step, the order list includes at least one order information;

[0107] 202. According to the order list, determine the monitoring rule corresponding to each order information from a preset monitoring rule library, and generate a monitoring task list;

[0108] After this step, it also includes using an OCR recognition algorithm to identify the distribution platform corresponding to each order information in the order list, and generating a logistics distribution tree diagram corresponding to the order information based on the distribution plan of the distribution platform, and obtaining a logistics update node set containing at least one order information, wherein the OCR recognition algorithm is an optical symbol recognition technology, specifically scanning the order information through a scanning device to obtain the distribution platform of each order information, that is, the express company, and then querying the corresponding logistics data update site based on the delivery address of each order in the express company, and constructing a logistics distribution tree diagram of the order information based on the update site, and finally integrating the logistics update nodes of all orders into a set. Further, while forming a set, all logistics update nodes can also be connected in series in chronological order to obtain a monitoring task sequence.

[0109] 203. Extract basic information from the order information;

[0110] In this step, the basic information includes product information and logistics data;

[0111] 204. Calculate the violation time points of the order information according to the product information and logistics data, and merge all violation time points into to-be-processed data and add them into a to-be-processed queue;

[0112] In this embodiment, the product information is extracted by extracting the name and model of the product purchased by the customer and the information of the merchant described by the product from the order information based on text recognition technology. The name of the product and the information of the merchant determine the specific update time calculation rules.

[0113] For extracting logistics data, specifically, it is to extract the entry time and corresponding processing personnel information of the logistics information when the commodity express flow recorded in the order information is transferred to each node.

[0114] In actual applications, the possible violation time points in the logistics data of possible orders are calculated based on the extracted product names and entry times, and then all the violation time points are correspondingly related to the orders. Finally, the violation time points marked with order information are merged to form a queue to be processed.

[0115] 205. Regularly execute the monitoring rules by means of a script, obtain data corresponding to the violation time point in the queue to be processed that has reached the update time, and determine whether the corresponding order is in violation, and obtain the monitoring result;

[0116] The execution of monitoring rules is controlled by script timing. During execution, the latest update time of each node in the order is calculated, and the latest update time is compared with the entry time of the logistics information collected from the order information to obtain the comparison result. The comparison result is divided into three types: greater than, equal to, and less than. The monitoring result is output based on the comparison result, and the result specifically points to violation or non-violation.

[0117] Furthermore, after determining that an order is in violation, it also includes calculating the violation level of the corresponding node in the order, and outputting the monitoring result based on the violation level. The monitoring result at this time includes the violation mark and the level of violation alarm processing.

[0118] 206. Determine the violation events of each order according to the monitoring results, and select a corresponding penalty method from the configured violation penalty methods based on the violation events.

[0119] Through the implementation of the above scheme, corresponding monitoring rules are set according to different merchant types, and monitoring tasks are set based on the monitoring rules to regularly monitor the update of logistics data of orders on each e-commerce platform. Through the monitoring rules, the logistics data recorded in each order is obtained, and the logistics records of each update record in the detected logistics data meet the conditions specified in the monitoring rules. If not, the order is determined to be in violation, and the violation events in the order are determined. Based on the violation events, the corresponding punishment method is selected to achieve constraints on each merchant.

[0120] See also Figure 3 , a third embodiment of the order violation detection method in the embodiment of the present invention includes:

[0121] 301. Collecting order information of users that have completed payment on the e-commerce platform, and sorting the order information in order of payment time to obtain a list of orders to be monitored;

[0122] 302. According to the order list, determine the monitoring rule corresponding to each order information from a preset monitoring rule library, and generate a monitoring task list;

[0123] In this embodiment, the monitoring rule library includes merchant classification rules, holiday rules, delivery area rules and commodity category rules. In practical applications, the above rules can be constructed in the following ways:

[0124] According to the merchant type, configure the first order delivery time limit, first logistics time limit and first violation penalty method corresponding to the merchant type on the rule configuration interface to generate merchant classification rules;

[0125] According to holidays, configure the second order delivery time limit, second logistics time limit and second violation penalty method for different holidays on the rule configuration interface to generate holiday rules;

[0126] According to the delivery area, configure the third-party order delivery time limit, third-party logistics time limit and third-party violation penalty method in different regions on the rule configuration interface to generate the delivery area rules;

[0127] According to the specific product category, the fourth order delivery time limit, fourth logistics time limit and fourth violation penalty method of different products are configured on the rule configuration interface to generate product category rules.

[0128] 303. Extract basic information from the order information;

[0129] In this step, the basic information includes product information and logistics data. In actual applications, the logistics data includes order time and actual delivery time.

[0130] 304. Calculate the violation time points of the order information according to the product information and logistics data, and merge all violation time points into to-be-processed data and add them into a to-be-processed queue;

[0131] 305. Execute the monitoring rule to detect whether the order time is within a special time period, where the special time period is a specific sales time for commodities set by each e-commerce platform;

[0132] 306. If the order placement time is within a special time period, obtain a logistics update time calculation rule corresponding to the special time period, and calculate the actual update time of the order information within the special time period;

[0133] 307. Compare the actual update time with the actual delivery time to obtain a comparison result;

[0134] 308. Determine whether the corresponding order is in violation of the rules based on the comparison result, and obtain a monitoring result;

[0135] In this embodiment, the monitoring rules include timeout rules and holiday rules. When executing the rules to detect order violations, it is first determined whether the entry time of the logistics information recorded in the order information at the violation time point exceeds the latest update time calculated according to the monitoring rules. If so, it is determined whether the payment time of the order belongs to the special time period specified in the holiday rules. If so, the latest update time is recalculated according to the holiday rules, and the entry time is compared again based on the latest update time. Based on the comparison, it is determined whether there is a violation to obtain the monitoring result.

[0136] In actual application, holiday rules: set the latest delivery time according to the type of holiday (Labor Day, National Day, Spring Festival, etc.). For example, set the exemption from October 1st to October 7th for National Day. Overtime rules: set the graded penalty ratio according to the time nodes of 2 days, 3 days, 5 days, etc.

[0137] 309. Determine the violation events of each order according to the monitoring results, and select a corresponding penalty method from the configured violation penalty methods based on the violation events.

[0138] In practical applications, the logistics data also includes a delivery address;

[0139] After detecting that the order placement time is within the special time period, the method further includes:

[0140] Matching the delivery address with the pre-planned delivery area to determine its corresponding configuration area;

[0141] According to the delivery area, a corresponding logistics update rule is selected from a preset logistics update rule library;

[0142] Calculate the latest update time of the order information within the special time period according to the logistics update rule and the logistics update time calculation rule;

[0143] Compare the latest update time with the actual delivery time to obtain a comparison result;

[0144] Based on the comparison result, it is determined whether the corresponding order is in violation of the regulations, and a monitoring result is obtained.

[0145] In this embodiment, the delivery time of express parcels is affected not only by holidays but also by the delivery area, which is specifically divided into remote areas and developed areas. The delivery efficiency of the two remote areas is far lower than that of developed areas due to the transportation routes. Therefore, in order to ensure the friendship between merchants or platforms and buyers, this embodiment also provides for adjusting the update time of shipping or distribution logistics according to the delivery address, such as through the delivery area rule, which sets the latest delivery time according to different delivery areas (Yangtze River Delta, remote areas, etc.).

[0146] Specifically, firstly, based on the delivery address or the delivery address, a match is performed from the pre-divided distribution area map to determine the corresponding distribution area number or the delivery area number, and based on the number, the corresponding rule is queried from the logistics update rule library, and the latest update time is calculated based on the rule. A comparison is performed based on the latest update time to obtain a comparison result, and based on the comparison result, it is determined whether there is a violation, and finally the monitoring result is output.

[0147] In actual applications, the above-mentioned timeout duration rules, holiday rules and delivery area rules can be used in combination or separately. If used in combination, they are calculated based on the delay time specified in the three rules to obtain the final update time. If used separately, they are consistent with the above records and will not be repeated here.

[0148] In practical applications, if the latest update time is calculated using an overlay calculation method, the query rule calculation can be performed based on the following three fields in the breach rule data structure, as shown in Table 1 below.

[0149] Table 1 Monitoring rules

[0150]

[0151]

[0152] In this embodiment, the violation of the order is detected based on the above-mentioned monitoring rules. During the detection process, the time limit of the corresponding order needs to be calculated according to different rules, which can be specifically understood as the delay statistical calculation logic. The specific implementation steps are as follows:

[0153] A. Daily logistics overtime calculation scheduled task is started;

[0154] B. Obtain the applicable logistics timeout rule set;

[0155] C. Calculate the set of TX days required for default calculation based on the applicable rule set;

[0156] D. Traverse the TX day set. If the order on that day meets the delay calculation conditions, skip it. Otherwise, extract all order data on that day, traverse the order data set to perform physical default calculation, and generate default orders for default orders.

[0157] In summary, corresponding monitoring rules are set according to different merchant types, and monitoring tasks are set based on the monitoring rules to regularly monitor the updates of logistics data of orders on each e-commerce platform. Through the monitoring rules, the logistics data recorded in each order is obtained, and the logistics records of each update record in the detected logistics data meet the conditions specified in the monitoring rules. If not, the order is determined to be in violation, and the violation events in the order are determined. Based on the violation events, the corresponding punishment method is selected to achieve constraints on each merchant, improve the delivery efficiency of orders, and ensure customer satisfaction.

[0158] See also Figure 4 , a fourth embodiment of the order violation detection method in the embodiment of the present invention, wherein configuration can be performed through a rule template, and the order is monitored regularly based on the configured rules, and the method includes:

[0159] 401. Configure the timeout penalty rule set based on the diversified rule template;

[0160] 402. Daily scheduled tasks are started, and default orders are screened through delayed statistical calculation logic;

[0161] 403. Traverse the order data set and generate a default order for the orders that match the default rules.

[0162] In this embodiment, determining the violation event of each order according to the monitoring result, and selecting a corresponding penalty method from the configured violation penalty methods based on the violation event includes:

[0163] Detecting the category corresponding to the product in the order information;

[0164] When the monitoring result is a violation of the pickup time, the corresponding penalty level classification is queried from the configured violation penalty method according to the category;

[0165] Calculate the percentage by which the actual delivery time exceeds the latest update time;

[0166] According to the percentage, the corresponding penalty level and penalty method are determined from the penalty level classification.

[0167] In actual application, it is divided into three levels, namely delivery, logistics availability and the time to update logistics at each node. For example, if the goods are not shipped within 24 hours of payment, the merchant will be fined 10 yuan in deposit and this amount will be returned to the buyer of the order in the form of a shopping fund. If the goods are not shipped within 48 hours of payment, the order will be closed directly and the payment will be returned to the buyer in a timely manner.

[0168] If there is no logistics information within 48 hours of payment, the merchant will be fined a deposit of 10 yuan, and this amount will be returned to the buyer of the order in the form of shopping funds. If there is no logistics information within 96 hours of payment, the order will be closed directly and the payment will be returned to the buyer in a timely manner.

[0169] If there is the first logistics information within 48 hours of payment, but no transfer information within 72 hours of payment, the merchant will be fined 20 yuan in deposit and this amount will be returned to the buyer of the order in the form of shopping funds.

[0170] Specifically, if the first logistics information is available within 48 hours of payment, but the collection time of the order logistics information is earlier than the order review time, it will be judged that the collection time is abnormal, and the merchant will be fined 20 yuan deposit, and this amount will be returned to the buyer of the order in the form of a shopping fund; if the first logistics information is available within 48 hours of payment, and there is transit information within 72 hours, but there are two collection information in the first four information, the merchant will be fined 20 yuan deposit, and this amount will be returned to the buyer of the order in the form of a shopping fund; if the first logistics information is available within 48 hours of payment, and there is transit information within 72 hours, but the transit time interval of the logistics information exceeds 96 hours, the merchant and the buyer will be prompted at the same time that the transit time is abnormal; if the first logistics information is available within 48 hours of payment, and there is transit information within 72 hours, but the logistics sending and receiving place, transit place and order sending and receiving place are different, the merchant and the buyer will be prompted at the same time that the transit place is abnormal.

[0171] Through the implementation of the above solution, the logistics update time of the order can be monitored by monitoring rules. This method can give the platform administrator enough time to import the corresponding punishment and exemption rules; it can formulate the calculation rules of the violation orders according to the specific business type, receiving area, and timeout gradient; it can deal with various force majeure situations that occur during the merchant's delivery or user's signing, such as: major events in the place of delivery or the place of receipt delay, slow logistics processing during statutory holidays, and slow logistics delivery due to the explosion of orders for major events. It can greatly reduce the amount of calculation for breach of contract processing and improve calculation efficiency.

[0172] The new solution can manage and punish merchants more reasonably and fairly, improve the accuracy of logistics violation judgments, improve the calculation efficiency of breach of contract processing, reduce operating labor costs, and help encourage merchants to improve the quality of delivery logistics services and increase customer satisfaction.

[0173] The above describes the order violation detection method in the embodiment of the present invention. The following describes the order violation detection device in the embodiment of the present invention. Figure 5 The first embodiment of the order violation detection device in the embodiment of the present invention includes:

[0174] The collection module 501 is used to collect the order information of the user who has completed the payment on the e-commerce platform, and sort the order information according to the order of payment time to obtain an order list to be monitored, wherein the order list includes at least one order information;

[0175] The identification module 502 is used to identify the distribution platform corresponding to each order information in the order list by using an OCR recognition algorithm, and generate a logistics distribution tree diagram corresponding to the order information based on the distribution plan of the distribution platform to obtain a logistics update node set including the at least one order information;

[0176] A generating module 503 is used to determine the monitoring rules corresponding to each of the order information from a preset monitoring rule library according to the order list, and generate a monitoring task list;

[0177] A monitoring module 504 is used to run the monitoring rules in the monitoring task list, monitor the logistics update node set of the order list, and obtain monitoring results;

[0178] The selection module 505 is used to determine the violation events of each order according to the monitoring results, and select a corresponding penalty method from the configured violation penalty methods based on the violation events.

[0179] In this embodiment, the order violation detection device runs the above-mentioned order violation detection method, which sets corresponding monitoring rules according to different merchant types, and sets monitoring tasks based on the monitoring rules to perform regular monitoring on the update of logistics data of orders on each electrical commodity platform. Through the monitoring rules, the logistics data recorded in each order is obtained, and whether the logistics records of each update record in the detected logistics data meet the conditions specified in the monitoring rules. If not, the order is determined to be in violation, and the violation events in the order are determined. Based on the violation events, the corresponding punishment method is selected to implement constraints on each merchant.

[0180] See also Figure 6 , a second embodiment of the order violation detection device in the embodiment of the present invention, the order violation detection device specifically comprises:

[0181] The collection module 501 is used to collect the order information of the user who has completed the payment on the e-commerce platform, and sort the order information according to the order of payment time to obtain an order list to be monitored, wherein the order list includes at least one order information;

[0182] The identification module 502 is used to identify the distribution platform corresponding to each order information in the order list by using an OCR recognition algorithm, and generate a logistics distribution tree diagram corresponding to the order information based on the distribution plan of the distribution platform to obtain a logistics update node set including the at least one order information;

[0183] A generating module 503 is used to determine the monitoring rules corresponding to each of the order information from a preset monitoring rule library according to the order list, and generate a monitoring task list;

[0184] A monitoring module 504 is used to run the monitoring rules in the monitoring task list to monitor the logistics update node set of the order list to obtain a monitoring result;

[0185] The selection module 505 is used to determine the violation events of each order according to the monitoring results, and select a corresponding penalty method from the configured violation penalty methods based on the violation events.

[0186] Optionally, the order violation detection device further includes a rule configuration module 506, which is specifically used to:

[0187] According to the merchant type, configure the first order delivery time limit, first logistics time limit and first violation penalty method corresponding to the merchant type on the rule configuration interface to generate merchant classification rules;

[0188] According to holidays, configure the second order delivery time limit, second logistics time limit and second violation penalty method for different holidays on the rule configuration interface to generate holiday rules;

[0189] According to the delivery area, configure the third-party order delivery time limit, third-party logistics time limit and third-party violation penalty method in different regions on the rule configuration interface to generate the delivery area rules;

[0190] According to the specific product category, the fourth order delivery time limit, fourth logistics time limit and fourth violation penalty method of different products are configured on the rule configuration interface to generate product category rules.

[0191] Optionally, the monitoring module 504 includes:

[0192] An extraction unit 5041 is used to extract basic information from the order information, wherein the basic information includes product information and logistics data;

[0193] The calculation unit 5042 calculates the violation time points of the order information according to the commodity information and logistics data, and combines all the violation time points into to-be-processed data and adds them into a to-be-processed queue;

[0194] The violation judgment unit 5043 is used to execute the monitoring rules regularly through scripts, obtain the data corresponding to the violation time point that has reached the update time in the queue to be processed, and determine whether the corresponding order is in violation to obtain the monitoring result.

[0195] Optionally, the logistics data includes the order time and the actual delivery time; the violation judgment unit 5043 is specifically used to:

[0196] Execute the monitoring rule to detect whether the order time is within a special time period, wherein the special time period is a specific sales time for commodities set by each e-commerce platform;

[0197] If the order placement time is within a special time period, then the logistics update time calculation rule corresponding to the special time period is obtained to calculate the actual update time of the order information within the special time period;

[0198] Compare the actual update time with the actual delivery time to obtain a comparison result;

[0199] Based on the comparison result, it is determined whether the corresponding order is in violation of the regulations, and a monitoring result is obtained.

[0200] Optionally, the logistics data also includes a delivery address; the violation judgment unit 5043 is further specifically used for:

[0201] Matching the delivery address with the pre-planned delivery area to determine its corresponding configuration area;

[0202] According to the delivery area, a corresponding logistics update rule is selected from a preset logistics update rule library;

[0203] Calculate the latest update time of the order information within the special time period according to the logistics update rule and the logistics update time calculation rule;

[0204] Compare the latest update time with the actual delivery time to obtain a comparison result;

[0205] Based on the comparison result, it is determined whether the corresponding order is in violation of the regulations, and a monitoring result is obtained.

[0206] Optionally, the selection module 505 includes:

[0207] The detection unit 5051 is used to detect the category corresponding to the commodity in the order information;

[0208] The classification unit 5052 is used to query the corresponding penalty level classification from the configured violation penalty methods according to the category when the monitoring result is the pickup violation time;

[0209] A calculation unit 5053, used for calculating the percentage by which the actual delivery time exceeds the latest update time;

[0210] The determination unit 5054 is used to determine the corresponding penalty level and penalty method from the penalty level classification according to the percentage.

[0211] above Figure 5 and Figure 6 The order violation detection device in the embodiment of the present invention is described in detail from the perspective of modular functional entities. The order violation detection device in the embodiment of the present invention is described in detail from the perspective of hardware processing. The order violation detection device can be set in the form of a plug-in to realize the recognition of dialogue with the order violation detection device.

[0212] Figure 7 8 is a schematic diagram of the structure of an order violation detection device provided by an embodiment of the present invention. The order violation detection device 800 may have relatively large differences due to different configurations or performances, and may include one or more processors (central processing units, CPU) 810 (for example, one or more processors) and a memory 820, and one or more storage media 830 (for example, one or more mass storage devices) storing application programs 833 or data 832. Among them, the memory 820 and the storage medium 830 may be temporary storage or permanent storage. The program stored in the storage medium 830 may include one or more modules (not shown in the figure), and each module may include a series of instruction operations in the order violation detection device 800. Furthermore, the processor 810 may be configured to communicate with the storage medium 830, and execute a series of instruction operations in the storage medium 830 on the order violation detection device 800 to implement the steps of the above-mentioned order violation detection method.

[0213] The order violation detection device 800 may also include one or more power supplies 840, one or more wired or wireless network interfaces 850, one or more input and output interfaces 860, and / or one or more operating systems 831, such as Windows Serve, Mac OS X, Unix, Linux, FreeBSD, etc. It will be appreciated by those skilled in the art that Figure 7 The structure of the order violation detection device shown does not constitute a limitation on the order violation detection device provided in the present application, and may include more or fewer components than shown in the figure, or a combination of certain components, or a different arrangement of components.

[0214] The blockchain referred to in this invention is a new application mode of computer technologies such as distributed data storage, peer-to-peer transmission, consensus mechanism, encryption algorithm, etc. Blockchain is essentially a decentralized database, a string of data blocks generated by cryptographic methods. Each data block contains a batch of network transaction information, which is used to verify the validity of its information (anti-counterfeiting) and generate the next block. Blockchain can include the underlying blockchain platform, platform product service layer, and application service layer.

[0215] The present invention also provides a computer-readable storage medium, which may be a non-volatile computer-readable storage medium or a volatile computer-readable storage medium. Instructions are stored in the computer-readable storage medium. When the instructions are executed on a computer, the computer executes the steps of the order violation detection method provided in the above-mentioned embodiments.

[0216] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0217] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product. The computer software product is stored in a storage medium, including a number of instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the method described in each embodiment of the present invention. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk and other media that can store program codes.

[0218] As described above, the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit the same. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that the technical solutions described in the aforementioned embodiments may still be modified, or some of the technical features thereof may be replaced by equivalents. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for detecting order violations, characterized in that: The order violation detection method comprises: Collecting order information of users that have completed payment on the e-commerce platform, and sorting the order information in the order of payment time to obtain an order list to be monitored, wherein the order list includes at least one order information; Using an OCR recognition algorithm, identifying the distribution platform corresponding to each order information in the order list, and generating a logistics distribution tree diagram corresponding to the order information based on the distribution plan of the distribution platform, to obtain a logistics update node set including the at least one order information; According to the order list, determine the monitoring rules corresponding to each order information from a preset monitoring rule library, and generate a monitoring task list, wherein the monitoring rule library includes merchant classification rules, holiday rules, delivery area rules, and commodity category rules; Running the monitoring rules in the monitoring task list, monitoring the logistics update node set of the order list, and obtaining monitoring results; The monitoring rules in the monitoring task list are run to monitor the logistics update node set in the order list, and the monitoring results obtained include: Extracting basic information from the order information, wherein the basic information includes product information and logistics data, and the logistics data also includes a delivery address; Calculate the violation time points of the order information based on the product information and logistics data, and merge all violation time points into pending data and add them to the pending queue; Determine whether the entry time of the order logistics information at the time of the violation exceeds the latest update time determined according to the monitoring rules; If so, determining whether the payment time of the order is within the holiday time period specified by the holiday rule; If yes, determine a new latest update time according to the holiday rule, and determine whether there is a violation based on the new latest update time to obtain a monitoring result; Determine the violation event of each order according to the monitoring result, and select a corresponding penalty method from the configured violation penalty methods based on the violation event; Before determining the monitoring rule corresponding to each of the order information from a preset monitoring rule library according to the order list, the order violation detection method further includes: Calculate the latest update time of the logistics data of each node corresponding to each order information according to the merchant type, the product information and the delivery address; Fill in the monitoring rule template based on the latest update time and the penalty method corresponding to each of the order information to obtain the monitoring rule corresponding to each of the order information.

2. The order violation detection method according to claim 1, characterized in that: The order violation detection method further includes: According to the merchant type, the first order delivery time limit, the first logistics time limit and the first violation penalty method corresponding to the merchant type are configured on the rule configuration interface to generate merchant classification rules; According to holidays, configure the second order delivery time limit, second logistics time limit and second violation penalty method for different holidays on the rule configuration interface to generate holiday rules; According to the delivery area, configure the third-party order delivery time limit, third-party logistics time limit and third-party violation penalty method in different regions on the rule configuration interface to generate the delivery area rules; According to the specific product category, the fourth order delivery time limit, fourth logistics time limit and fourth violation penalty method of different products are configured on the rule configuration interface to generate product category rules.

3. The order violation detection method according to claim 2, characterized in that: The monitoring rule in the monitoring task list is run to monitor the logistics update node set of the order list, and the monitoring result obtained includes: The monitoring rules are executed regularly by means of a script, the data corresponding to the violation time point that has reached the update time in the queue to be processed is obtained, and it is determined whether the corresponding order is in violation, so as to obtain the monitoring result.

4. The order violation detection method according to claim 3 is characterized in that: The logistics data includes the order time and the actual delivery time; The monitoring rules are executed regularly by means of a script, the data corresponding to the violation time point that has reached the update time in the queue to be processed is obtained, and the corresponding order is determined to be in violation, and the monitoring results obtained include: Execute the monitoring rule to detect whether the order time is within a special time period, wherein the special time period is a specific sales time for commodities set by each e-commerce platform; If the order placement time is within a special time period, the logistics update time calculation rule corresponding to the special time period is obtained to calculate the actual update time of the order information within the special time period; Compare the actual update time with the actual delivery time to obtain a comparison result; Based on the comparison result, it is determined whether the corresponding order is in violation of the regulations, and a monitoring result is obtained.

5. The order violation detection method according to claim 4 is characterized in that: After detecting that the order placement time is within the special time period, the method further includes: Match the delivery address with the pre-planned delivery area to determine its corresponding configuration area; According to the delivery area, a corresponding logistics update rule is selected from a preset logistics update rule library; Calculate the latest update time of the order information within the special time period according to the logistics update rule and the logistics update time calculation rule; Compare the latest update time with the actual delivery time to obtain a comparison result; Based on the comparison result, it is determined whether the corresponding order is in violation of the regulations, and a monitoring result is obtained.

6. The order violation detection method according to claim 5, characterized in that: Determining the violation events of each order according to the monitoring results, and selecting a corresponding penalty method from the configured violation penalty methods based on the violation events includes: Detecting the category corresponding to the product in the order information; When the monitoring result is a violation of the pickup time, the corresponding penalty level classification is queried from the configured violation penalty method according to the category; Calculate the percentage by which the actual delivery time exceeds the latest update time; According to the percentage, the corresponding penalty level and penalty method are determined from the penalty level classification.

7. An order violation detection device, executing the order violation detection method according to any one of claims 1 to 6, characterized in that: The order violation detection device comprises: A collection module, used to collect order information of users that have completed payment on the e-commerce platform, and sort the order information in the order of payment time to obtain an order list to be monitored, wherein the order list includes at least one order information; an identification module, configured to identify the distribution platform corresponding to each order information in the order list by using an OCR recognition algorithm, and generate a logistics distribution tree diagram corresponding to the order information based on the distribution plan of the distribution platform, to obtain a logistics update node set including the at least one order information; A generating module, used to determine the monitoring rules corresponding to each of the order information from a preset monitoring rule library according to the order list, and generate a monitoring task list; A monitoring module, used to run the monitoring rules in the monitoring task list, monitor the logistics update node set of the order list, and obtain monitoring results; A selection module is used to determine the violation events of each order according to the monitoring results, and select a corresponding penalty method from the configured violation penalty methods based on the violation events.

8. The order violation detection device according to claim 7, characterized in that: The order violation detection device also includes a rule configuration module, which is specifically used to: According to the merchant type, the first order delivery time limit, the first logistics time limit and the first violation penalty method corresponding to the merchant type are configured on the rule configuration interface to generate merchant classification rules; According to holidays, configure the second order delivery time limit, second logistics time limit and second violation penalty method for different holidays on the rule configuration interface to generate holiday rules; According to the delivery area, configure the third-party order delivery time limit, third-party logistics time limit and third-party violation penalty method in different regions on the rule configuration interface to generate the delivery area rules; According to the specific product category, the fourth order delivery time limit, fourth logistics time limit and fourth violation penalty method of different products are configured on the rule configuration interface to generate product category rules.

9. An order violation detection device, characterized in that: The order violation detection device comprises: a memory and at least one processor, the memory stores instructions, and the memory and the at least one processor are interconnected via a line; The at least one processor calls the instructions in the memory to enable the order violation detection device to execute the order violation detection method according to any one of claims 1 to 6.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the order violation detection method according to any one of claims 1 to 6 is implemented.

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