Abnormal order identification method, system, electronic device and storage medium

Abstract

The present invention provides an abnormal order identification method, system, electronic device and storage medium. The abnormal order identification method includes: determining the first address information and the second address information in the address information of the pending order; the first address information is the administrative division information, and the second address information is the detailed address information; based on the classification algorithm, the second address information is processed to determine whether the address information belongs to suspected abnormal address information; if so, based on the matching algorithm, the first address information and the second address information are matched to determine whether the address information belongs to abnormal address information, thereby identifying whether the pending order belongs to an abnormal order. The present invention realizes the automatic identification of abnormal orders with inconsistent address information, ensuring accurate calculation of the freight of the order and smooth flow of logistics.

Description

Background Art

[0002] When users purchase goods, they need to fill in the delivery address, and the merchant will send the goods according to the delivery address in the order. In the case of uneven development of logistics networks in various regions, some merchants set up "free shipping zones", that is, free shipping for orders with delivery addresses within the "free shipping zones". In practice, some users outside the "free shipping zones" choose addresses within the "free shipping zones" in the administrative division section when filling in the address when purchasing goods, and fill in the real address in the detailed address section, which leads to errors in the freight calculation and logistics flow of the order.

[0003] Therefore, how to automatically identify abnormal orders with inconsistent address information to ensure accurate freight calculation and smooth logistics flow has become a technical problem that needs to be solved urgently in this field. Summary of the invention

[0004] In order to overcome the defects of the above-mentioned related technologies, the present invention provides an abnormal order identification method, system, electronic device and storage medium, thereby realizing automatic identification of abnormal orders with inconsistent address information, ensuring accurate calculation of order freight and smooth logistics flow.

[0005] According to one aspect of the present invention, a method for identifying abnormal orders is provided, comprising:

[0006] Determine the first address information and the second address information in the address information of the order to be processed;

[0007] The first address information is administrative division information, and the second address information is detailed address information;

[0008] Based on the classification algorithm, the second address information is processed to determine whether the address information belongs to suspected abnormal address information;

[0009] If so, based on a matching algorithm, the first address information and the second address information are matched to determine whether the address information is abnormal address information, thereby identifying whether the pending order is an abnormal order.

[0010] In some embodiments of the present invention, the step of processing the second address information based on a classification algorithm to determine whether the address information belongs to suspected abnormal address information includes:

[0011] Determining whether the second address information includes administrative division feature data;

[0012] If so, the address information is classified as suspected abnormal address information.

[0013] In some embodiments of the present invention, the step of matching the first address information and the second address information based on a matching algorithm to determine whether the address information is abnormal address information includes:

[0014] dividing the second address information into a plurality of address fields;

[0015] At least part of the address field is matched with the first address information to determine whether the address information is abnormal address information.

[0016] In some embodiments of the present invention, the step of matching the first address information and the second address information based on a matching algorithm to determine whether the address information is abnormal address information includes:

[0017] Based on a matching algorithm, the first address information and the second address information are matched in combination with at least one of the address standard name, address alias, address abbreviation, and address historical name to determine whether the address information is abnormal address information.

[0018] In some embodiments of the present invention, the step of matching the first address information and the second address information based on a matching algorithm to determine whether the address information is abnormal address information includes:

[0019] Determine an address field of a target address level in the first address information;

[0020] Determine the matching model corresponding to the address field;

[0021] The second address information is input into the matching model to determine whether the second address information matches the address field, so as to determine whether the address information is abnormal address information.

[0022] In some embodiments of the present invention, it further includes:

[0023] For the identified abnormal order, the first address information is updated with at least part of the address field of the second address information.

[0024] In some embodiments of the present invention, it further includes:

[0025] The updated first address information is used to calculate freight and logistics flow for abnormal orders.

[0026] According to another aspect of the present invention, there is also provided an abnormal order identification system, comprising:

[0027] A determination module is configured to determine first address information and second address information in the address information of the order to be processed; the first address information is administrative division information, and the second address information is detailed address information;

[0028] A classification module is configured to process the second address information based on a classification algorithm to determine whether the address information belongs to suspected abnormal address information;

[0029] The matching module is configured to, if the address information belongs to suspected abnormal address information, match the first address information and the second address information based on a matching algorithm to determine whether the address information belongs to abnormal address information, thereby identifying whether the to-be-processed order is an abnormal order.

[0030] According to another aspect of the present invention, there is also provided an electronic device, comprising: a processor; and a storage medium on which a computer program is stored, and when the computer program is executed by the processor, the steps described above are executed.

[0031] According to another aspect of the present invention, there is further provided a storage medium on which a computer program is stored. When the computer program is executed by a processor, the steps described above are executed.

[0032] Compared with the prior art, the advantages of the present invention are:

[0033] The present invention determines the first address information and the second address information in the address information of the pending order, the first address information is the administrative division information, and the second address information is the detailed address information, thus, firstly based on the classification algorithm, the second address information is processed to determine whether the address information belongs to the suspected abnormal address information, if so, further based on the matching algorithm, the first address information and the second address information are matched to determine whether the address information belongs to the abnormal address information, thereby identifying whether the pending order belongs to the abnormal order. The present invention realizes the automatic identification of abnormal orders with inconsistent address information, and ensures that the freight calculation of the order is accurate and the logistics flow is smooth. BRIEF DESCRIPTION OF THE DRAWINGS

[0034] The above and other features and advantages of the present invention will become more apparent by describing in detail exemplary embodiments thereof with reference to the attached drawings.

[0035] Figure 1 A flowchart of an abnormal order identification method according to an embodiment of the present invention is shown;

[0036] Figure 2 A flow chart showing processing the second address information based on a classification algorithm according to an embodiment of the present invention to determine whether the address information belongs to suspected abnormal address information;

[0037] Figure 3 A flowchart is shown of matching the first address information and the second address information based on a matching algorithm according to an embodiment of the present invention to determine whether the address information is abnormal address information;

[0038] Figure 4 A flowchart is shown of matching the first address information and the second address information based on a matching algorithm according to an embodiment of the present invention to determine whether the address information is abnormal address information;

[0039] Figure 5 A module diagram of an abnormal order identification system according to an embodiment of the present invention is shown;

[0040] Figure 6 A schematic diagram of an electronic device in an exemplary embodiment of the present invention is schematically shown;

[0041] Figure 7 A schematic diagram of a computer-readable storage medium in an exemplary embodiment of the present invention is schematically shown. DETAILED DESCRIPTION

[0042] Example embodiments will now be described more fully with reference to the accompanying drawings. However, example embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided so that the present invention will be more comprehensive and complete and fully convey the concepts of the example embodiments to those skilled in the art. The described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.

[0043] In addition, the accompanying drawings are only schematic illustrations of the present invention and are not necessarily drawn to scale. The same reference numerals in the figures represent the same or similar parts, and their repeated description will be omitted. Some of the block diagrams shown in the accompanying drawings are functional entities and do not necessarily correspond to physically or logically independent entities. These functional entities can be implemented in software form, or implemented in one or more hardware modules or integrated circuits, or implemented in different networks and / or processor devices and / or microcontroller devices.

[0044] The flowcharts shown in the accompanying drawings are only exemplary and do not necessarily include all the steps. For example, some steps may be decomposed, while some steps may be combined or partially combined. Therefore, the actual execution order may be changed according to the actual situation.

[0045] In various embodiments of the present invention, the abnormal order identification method provided by the present invention can be applied to e-commerce, logistics or any third-party scenario that requires the use of address information, but the application scenarios of the present invention are not limited to this and will not be elaborated here.

[0046] Figure 1 A flow chart of an abnormal order identification method according to an embodiment of the present invention is shown.

[0047] Abnormal order identification methods include:

[0048] Step S110: determining the first address information and the second address information in the address information of the order to be processed; the first address information is the administrative division information, and the second address information is the detailed address information;

[0049] Specifically,

[0050] There may be many types of pending orders, such as pending payment orders, pending shipment orders, pending receipt orders, refund / after-sales orders, pending evaluation orders, etc. Therefore, there may be many execution times for the abnormal order identification method of the present invention, such as when the user selects a product to confirm the order, after the user completes the payment and generates the order, etc., and the present invention does not limit this.

[0051] There may be a variety of ways to obtain the address information of pending orders, for example, first obtain the pending orders and then extract the address information of the pending orders, or directly obtain the address information of the pending orders; actively obtain the pending orders and / or the address information of the pending orders, or passively receive the pending orders and / or the address information of the pending orders, etc.

[0052] The address information of the pending order may refer to the address information such as the receiving address, the sending address, etc. selected or input by the user in the pending order.

[0053] Taking the recipient address filled in by the user as an example, one scenario is that the system provides an option control for the user to select the first address information, and the user manually enters the second address information. At this time, the system can directly determine the first address information and the second address information that have been divided, and can directly determine the address level and address field of the first address information. At the same time, in order to facilitate subsequent processing, the second address information can also be pre-processed and / or standardized, for example, eliminating redundant data, completing missing data, dividing the address information to obtain address levels and address fields, correcting typos in the address information, and other one or more processing methods.

[0054] In another case, the first address information and the second address information are both manually input by the user. For example, the system can set two blank fields for the user to manually input the first address information and the second address information. In this case, the system can also directly determine the first address information and the second address information that have been divided. At the same time, in order to facilitate subsequent processing, the first address information and / or the second address information can also be pre-processed and / or standardized.

[0055] It is understandable that the present invention can be implemented in more variations and is not limited thereto.

[0056] Step S120: Processing the second address information based on the classification algorithm to determine whether the address information belongs to suspected abnormal address information;

[0057] Specifically,

[0058] Step S120 may be, based on a classification algorithm, classifying the second address information, classifying the second address information as suspected abnormal address information or preliminary normal address information, thereby classifying the address information as suspected abnormal address information or preliminary normal address information; or, based on a classification algorithm, classifying the address information according to the second address information, classifying the address information as suspected abnormal address information or preliminary normal address information.

[0059] As described above, when the second address information is processed based on the classification algorithm, the second address information may be pre-processed and / or standardized first.

[0060] There may be multiple classification algorithms for implementing step S120. For example, a two-class classification algorithm may be used. Furthermore, an SVM (Support Vector Machine) classification algorithm may be used. When training the classification algorithm, a standard address library and / or address information of historical orders that have been successfully delivered may be used as training samples. For example, an address data set of a standard address library may be obtained as a training sample, and the training sample may be preprocessed, feature items may be extracted, and then processed to construct an SVM classification model. When executing step S120, the second address information that has been preprocessed and / or standardized is input into the constructed SVM classification model, and the result that the second address information is suspected abnormal address information or preliminary normal address information is output, or the result that the address information is directly output as suspected abnormal address information or preliminary normal address information is output.

[0061] It is understandable that the present invention can be implemented in more variations and is not limited thereto.

[0062] Step S130: If yes, based on a matching algorithm, the first address information and the second address information are matched to determine whether the address information is abnormal address information, thereby identifying whether the pending order is an abnormal order.

[0063] Specifically,

[0064] The first address information and the second address information are matched by matching at least part of the first address information with at least part of the second address information to determine whether the second address information is abnormal address information, thereby determining whether the address information is abnormal information, or directly determining whether the address information is abnormal address information. If the address information is abnormal address information, the pending order is an abnormal order.

[0065] As described above, when matching the first address information and the second address information, the first address information and / or the second address information may be preprocessed and / or standardized first.

[0066] When matching the first address information and the second address information, one address field of the first address information and the second address information may be extracted for matching, or multiple address fields of the first address information and the second address information may be extracted for matching in sequence or simultaneously according to the address level.

[0067] When matching, at least one of the address standard name, address alias, address abbreviation, and address historical name can also be combined. For example, "Xin", "Xinjiang", and "Xinjiang Uygur Autonomous Region" can be considered a successful match, and "Min", "Fujian", and "Fujian Province" can also be considered a successful match.

[0068] When outputting the result, when the first match fails, the second address information or the result that the address information belongs to abnormal address information can be output. A threshold of one time can also be set, and when the number of failed matches reaches the threshold of the number of times, the result that the second address information or the address information belongs to abnormal address information is output. A weight value can also be set for each match, and the final output result is calculated with the weight value.

[0069] There may be multiple algorithms for implementing step S130, for example, a regular matching algorithm may be used. When training the matching algorithm, a standard address library and / or address information of historical orders that have been successfully delivered may be used as training samples.

[0070] It is understandable that the present invention can be implemented in more variations and is not limited thereto.

[0071] In actual applications, after step S130 identifies that the order to be processed is an abnormal order, the abnormal order can be marked, and an early warning reminder can be issued to the user, merchant, and system for subsequent processing.

[0072] In addition, at least part of the address fields of the second address information in the abnormal order can be extracted, for example, one or more address fields of the administrative division information part, and the first address information can be updated accordingly to obtain the first address information that is consistent with the second address information, and the updated first address information can be used to calculate the freight and logistics flow of the abnormal order.

[0073] The abnormal order identification method provided by the present invention determines the first address information and the second address information in the address information of the pending order, the first address information is the administrative division information, and the second address information is the detailed address information, thereby firstly processing the second address information based on the classification algorithm to determine whether the address information belongs to the suspected abnormal address information, and if so, further matching the first address information and the second address information based on the matching algorithm to determine whether the address information belongs to the abnormal address information, thereby identifying whether the pending order belongs to the abnormal order. The present invention realizes the automatic identification of abnormal orders with inconsistent address information, and ensures that the freight calculation of the order is accurate and the logistics flow is smooth.

[0074] Figure 2 A flow chart of processing the second address information based on a classification algorithm to determine whether the address information belongs to suspected abnormal address information according to an embodiment of the present invention is shown.

[0075] Step S120: Based on the classification algorithm, the second address information is processed to determine whether the address information belongs to suspected abnormal address information, including:

[0076] Step S1201: determining whether the second address information contains administrative division feature data;

[0077] Specifically,

[0078] As described above, when determining whether the second address information contains administrative division characteristic data, the second address information may be preprocessed and / or standardized first.

[0079] Administrative division feature data may include a variety of situations, for example, address-level feature data such as "province", "city", "district", "township" that represent the administrative division level, address field feature data such as "Guangdong", "Shandong", "Shanghai" that represent the administrative division name, and may also include the fusion of the two, such as "Guangdong Province". Administrative division feature data may also include address-level feature data, address field feature data, and the standardized name, alias, abbreviation, historical name, etc. that are the fusion of the two, such as "Special Zone", "Fujian", etc.

[0080] In addition, specific administrative division characteristic data can also be set. For example, the administrative division characteristic data is limited to the first and second level address level characteristic data, address field characteristic data and their fusion, while excluding the "West Lake District" at the third level, or the administrative division characteristic data is limited to the first, second and third level address level characteristic data, address field characteristic data and their fusion, while excluding the "Xixi Street" at the fourth level.

[0081] The administrative division characteristic data may be obtained based on a standard address database and / or address information of historical orders that have been successfully delivered.

[0082] It is understandable that the present invention can be implemented in more variations and is not limited thereto.

[0083] Step S1202: If yes, classify the address information as suspected abnormal address information.

[0084] Specifically,

[0085] When the second address information contains administrative division feature data, the second address information is classified as suspected abnormal address information, thereby classifying the address information as suspected abnormal address information, or directly classifying the address information as suspected abnormal address information.

[0086] When outputting the result, when the first administrative division feature data is matched, the second address information or the address information is output as a result of suspected abnormal address information. A number threshold may also be set, and when the number of administrative division feature data contained in the second address information reaches the number threshold, the second address information or the address information is output as a result of suspected abnormal address information. A weight value may also be set for each administrative division feature data, and the final output result may be calculated using the weight value.

[0087] It is understandable that the present invention can be implemented in more variations and is not limited thereto.

[0088] Figure 3 A flow chart is shown for matching first address information and second address information based on a matching algorithm according to an embodiment of the present invention to determine whether the address information is abnormal address information.

[0089] In step S130, based on a matching algorithm, the first address information and the second address information are matched to determine whether the address information is abnormal address information, including:

[0090] Step S1301: Divide the second address information into a plurality of address fields;

[0091] Specifically,

[0092] As described above, when the second address information is divided into a plurality of address fields, the second address information may be preprocessed and / or standardized.

[0093] When dividing the address field of the second address information, the second address information can be divided into an administrative division information part and a detailed address information part according to the administrative division characteristic data in the second address information, and the administrative division information part in the second address information can be divided into multiple levels as needed. In this process, the administrative division information part in the second address information can be corrected and supplemented according to the first address information so that they at least partially correspond to each other.

[0094] It is understandable that the present invention can be implemented in more variations and is not limited thereto.

[0095] Step S1302: Match at least part of the address field with the first address information to determine whether the address information is abnormal address information.

[0096] Specifically,

[0097] As described above, when matching at least part of the address fields of the second address information with the first address information, the first address information and / or the second address information may be preprocessed and / or standardized first.

[0098] At least part of the address field of the second address information is matched with at least part of the first address information. As described above, when performing the matching and outputting the results, the present invention can implement a variety of variations, which will not be described in detail here.

[0099] Figure 4 A flow chart is shown for matching first address information and second address information based on a matching algorithm according to an embodiment of the present invention to determine whether the address information is abnormal address information.

[0100] In step S130, based on a matching algorithm, the first address information and the second address information are matched to determine whether the address information is abnormal address information, including:

[0101] Step S1301': determining the address field of the target address level in the first address information;

[0102] Specifically,

[0103] As described above, when determining the address field of the target address level in the first address information, the first address information may be preprocessed and / or standardized first.

[0104] The first address information may include multiple address levels and their corresponding address fields. A target address level is selected to determine its corresponding address field. For example, if the first address information is "Zhejiang Province - Hangzhou City - Xihu District", and the target address level is the second level, the second level address level is selected to determine its corresponding address field "Hangzhou City" (or "Hangzhou").

[0105] Step S1302': Determine the matching model corresponding to the address field;

[0106] Specifically,

[0107] For each address field corresponding to the target address level, a corresponding matching model is set. The matching model is configured to determine whether the input address information matches the address field. Of course, it can also be configured to determine whether the input address information matches the address field of the next address level of the address field. The present invention does not impose any restrictions on this.

[0108] There are many situations in which the input address information matches an address field, for example, part of the input address information is the same as the address field or represents the same geographical area, the input address information belongs to the address field, etc.

[0109] In the above example, for the address field "Hangzhou City" corresponding to the second-level address level in the first address information, a matching model corresponding to "Hangzhou City" can be set, and the matching model is used to determine whether the input address information matches "Hangzhou City".

[0110] When training the matching model, a standard address library and / or the address information of historical orders that have been successfully delivered can be used as training samples. For example, to determine whether the input address information belongs to "Hangzhou City" or its next address level "West Lake District", all address data under "Hangzhou City" in a standard address library can be collected, and the influence relationship between each address element and "Hangzhou City" or its next address level address field "West Lake District" can be analyzed in these address data to complete the feature design, and an SVM classification model can be constructed based on this.

[0111] Step S1303 ′: input the second address information into the matching model to determine whether the second address information matches the address field, so as to determine whether the address information is abnormal address information.

[0112] Specifically,

[0113] As described above, when the second address information is input into the matching model, the second address information may be preprocessed and / or standardized first.

[0114] The second address information input into the matching model can be the administrative division information part of the second address information, the detailed address information part of the second address information, or the complete second address information. As described above, when matching and outputting results, the present invention can implement multiple variations, which will not be repeated here.

[0115] The above are only a number of specific implementations of the abnormal order identification method of the present invention. Each implementation can be implemented independently or in combination, and the present invention is not limited to this. Furthermore, the flowchart of the present invention is only illustrative, and the execution order between the steps is not limited to this. The splitting, merging, order exchange, and other synchronous or asynchronous execution methods of the steps are all within the protection scope of the present invention.

[0116] Figure 5 The module diagram of the abnormal order identification system according to the embodiment of the present invention is shown. The abnormal order identification system 200 includes a determination module 210 , a classification module 220 , and a matching module 230 .

[0117] The determination module 210 is configured to determine the first address information and the second address information in the address information of the order to be processed; the first address information is the administrative division information, and the second address information is the detailed address information;

[0118] The classification module 220 is configured to process the second address information based on a classification algorithm to determine whether the address information belongs to suspected abnormal address information;

[0119] The matching module 230 is configured to, if the address information belongs to suspected abnormal address information, match the first address information and the second address information based on a matching algorithm to determine whether the address information belongs to abnormal address information, thereby identifying whether the to-be-processed order is an abnormal order.

[0120] The abnormal order identification system provided by the present invention determines the first address information and the second address information in the address information of the pending order, the first address information is the administrative division information, and the second address information is the detailed address information, thereby firstly processing the second address information based on the classification algorithm to determine whether the address information belongs to the suspected abnormal address information, and if so, further matching the first address information and the second address information based on the matching algorithm to determine whether the address information belongs to the abnormal address information, thereby identifying whether the pending order belongs to the abnormal order. The present invention realizes the automatic identification of abnormal orders with inconsistent address information, ensuring accurate calculation of the freight of the order and smooth flow of logistics.

[0121] Figure 5 The abnormal order identification system 200 provided by the present invention is only schematically shown. Without violating the concept of the present invention, the splitting, merging and adding of modules are all within the protection scope of the present invention. The abnormal order identification system 200 provided by the present invention can be implemented by software, hardware, firmware, plug-ins and any combination thereof, and the present invention is not limited thereto.

[0122] In an exemplary embodiment of the present invention, an electronic device is further provided, which may include a processor and a memory for storing executable instructions of the processor, wherein the processor is configured to execute the steps of the abnormal order identification method in any of the above embodiments by executing the executable instructions.

[0123] It will be appreciated by those skilled in the art that various aspects of the present invention may be implemented as a system, method or program product. Therefore, various aspects of the present invention may be specifically implemented in the following forms, namely: a complete hardware implementation, a complete software implementation (including firmware, microcode, etc.), or a combination of hardware and software, which may be collectively referred to herein as a "circuit", "module" or "system".

[0124] Refer to the following Figure 6 The electronic device 600 according to this embodiment of the present invention is described. Figure 6 The electronic device 600 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0125] like Figure 6 As shown, the electronic device 600 is in the form of a general computing device. The components of the electronic device 600 may include, but are not limited to: at least one processing unit 610, at least one storage unit 620, a bus 630 connecting different system components (including the storage unit 620 and the processing unit 610), a display unit 640, etc.

[0126] The storage unit stores program codes, which can be executed by the processing unit 610, so that the processing unit 610 executes the steps according to various exemplary embodiments of the present invention described in the above-mentioned abnormal order identification method of this specification. For example, the processing unit 610 can execute the following steps: Figures 1 to 4 Any step shown in any one or more of the accompanying drawings.

[0127] The storage unit 620 may include a readable medium in the form of a volatile storage unit, such as a random access memory unit (RAM) 6201 and / or a cache memory unit 6202 , and may further include a read-only memory unit (ROM) 6203 .

[0128] The storage unit 620 may also include a program / utility 6204 having a set (at least one) of program modules 6205, such program modules 6205 including but not limited to: an operating system, one or more application programs, other program modules and program data, each of which or some combination may include the implementation of a network environment.

[0129] Bus 630 may represent one or more of several types of bus structures, including a memory unit bus or memory unit controller, a peripheral bus, an accelerated graphics port, a processing unit, or a local bus using any of a variety of bus architectures.

[0130] The electronic device 600 may also communicate with one or more external devices 700 (e.g., keyboards, pointing devices, Bluetooth devices, etc.), may communicate with one or more devices that enable tenants to interact with the electronic device 600, and / or may communicate with any device that enables the electronic device 600 to communicate with one or more other computing devices (e.g., routers, modems, etc.). Such communication may be performed via an input / output (I / O) interface 650. In addition, the electronic device 600 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 660. The network adapter 660 may communicate with other modules of the electronic device 600 via a bus 630. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the electronic device 600, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems.

[0131] Through the description of the above implementation methods, it is easy for those skilled in the art to understand that the example implementation methods described here can be implemented by software or by combining software with necessary hardware. Therefore, the technical solution according to the implementation method of the present invention can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (which can be a CD-ROM, a USB flash drive, a mobile hard disk, etc.) or on a network, and includes a number of instructions to enable a computing device (which can be a personal computer, a server, or a network device, etc.) to execute the above-mentioned abnormal order identification method according to the implementation method of the present invention.

[0132] In an exemplary embodiment of the present invention, a computer-readable storage medium is also provided, on which a computer program is stored, and when the program is executed by, for example, a processor, the steps of the abnormal order identification method described in any of the above embodiments can be implemented. In some possible implementations, various aspects of the present invention can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of various exemplary embodiments of the present invention described in the above abnormal order identification method section of this specification.

[0133] Figure 7A program product 700 for implementing the above method according to an embodiment of the present invention is shown, which can adopt a portable compact disk read-only memory (CD-ROM) and include program code, and can be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited thereto, and in this document, a readable storage medium can be any tangible medium containing or storing a program, which can be used by or in combination with an instruction execution system, an apparatus or a device.

[0134] The program product may use any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples (non-exhaustive list) of readable storage media include: an electrical connection with one or more wires, a portable disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above.

[0135] The computer readable storage medium may include a data signal propagated in a baseband or as part of a carrier wave, wherein a readable program code is carried. This propagated data signal may take a variety of forms, including but not limited to an electromagnetic signal, an optical signal, or any suitable combination of the above. The readable storage medium may also be any readable medium other than a readable storage medium, which may send, propagate, or transmit a program for use by an instruction execution system, an apparatus, or a device or used in combination with it. The program code contained on the readable storage medium may be transmitted with any appropriate medium, including but not limited to wireless, wired, optical cable, RF, etc., or any suitable combination of the above.

[0136] Program code for performing the operations of the present invention may be written in any combination of one or more programming languages, including object-oriented programming languages ​​such as Java, C++, etc., and conventional procedural programming languages ​​such as "C" or similar programming languages. The program code may be executed entirely on the tenant computing device, partially on the tenant device, as a separate software package, partially on the tenant computing device and partially on a remote computing device, or entirely on a remote computing device or server. In cases involving remote computing devices, the remote computing device may be connected to the tenant computing device via any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computing device (e.g., via the Internet using an Internet service provider).

[0137] Compared with the prior art, the advantages of the present invention are:

[0138] The present invention determines the first address information and the second address information in the address information of the pending order, the first address information is the administrative division information, and the second address information is the detailed address information, thus, firstly based on the classification algorithm, the second address information is processed to determine whether the address information belongs to the suspected abnormal address information, if so, further based on the matching algorithm, the first address information and the second address information are matched to determine whether the address information belongs to the abnormal address information, thereby identifying whether the pending order belongs to the abnormal order. The present invention realizes the automatic identification of abnormal orders with inconsistent address information, and ensures that the freight calculation of the order is accurate and the logistics flow is smooth.

[0139] Those skilled in the art will readily appreciate other embodiments of the present invention after considering the specification and practicing the invention disclosed herein. This application is intended to cover any variations, uses or adaptations of the present invention, which follow the general principles of the present invention and include common knowledge or customary techniques in the art that are not disclosed by the present invention. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present invention are indicated by the appended claims.

Claims

1. A method for identifying abnormal orders, characterized in that: include: Determine the first address information and the second address information in the address information of the order to be processed; The first address information is administrative division information, and the second address information is detailed address information; Based on the classification algorithm, the second address information is processed to determine whether the address information belongs to suspected abnormal address information; If so, matching the first address information and the second address information based on a matching algorithm to determine whether the address information belongs to abnormal address information, thereby identifying whether the pending order belongs to an abnormal order; The classification algorithm processes the second address information to determine whether the address information belongs to suspected abnormal address information, which specifically includes: Determining whether the second address information includes administrative division characteristic data; If so, classify the address information as suspected abnormal address information; The step of matching the first address information and the second address information based on a matching algorithm to determine whether the address information is abnormal address information includes: Determine an address field of a target address level in the first address information; Determining a matching model corresponding to the address field; The second address information is input into the matching model to determine whether the second address information matches the address field, so as to determine whether the address information is abnormal address information.

2. The abnormal order identification method according to claim 1, characterized in that: The step of matching the first address information and the second address information based on a matching algorithm to determine whether the address information is abnormal address information includes: dividing the second address information into a plurality of address fields; At least part of the address field is matched with the first address information to determine whether the address information is abnormal address information.

3. The abnormal order identification method according to claim 1, characterized in that: The step of matching the first address information and the second address information based on a matching algorithm to determine whether the address information is abnormal address information includes: Based on a matching algorithm, the first address information and the second address information are matched in combination with at least one of the address standard name, address alias, address abbreviation, and address historical name to determine whether the address information is abnormal address information.

4. The abnormal order identification method according to claim 1, characterized in that: Also includes: For the identified abnormal order, the first address information is updated with at least part of the address field of the second address information.

5. The abnormal order identification method according to claim 4, characterized in that: Also includes: The updated first address information is used to calculate the freight and logistics flow of the abnormal order.

6. An abnormal order identification system, characterized in that: include: A determination module configured to determine the first address information and the second address information in the address information of the order to be processed; The first address information is administrative division information, and the second address information is detailed address information; a classification module configured to process the second address information based on a classification algorithm to determine whether the address information belongs to suspected abnormal address information; The classification algorithm processes the second address information to determine whether the address information belongs to suspected abnormal address information, which specifically includes: Determining whether the second address information includes administrative division characteristic data; If so, classify the address information as suspected abnormal address information; The matching module is configured to, if the address information belongs to suspected abnormal address information, match the first address information and the second address information based on a matching algorithm to determine whether the address information belongs to abnormal address information, thereby identifying whether the to-be-processed order belongs to an abnormal order; the step of matching the first address information and the second address information based on a matching algorithm to determine whether the address information belongs to abnormal address information includes: Determine an address field of a target address level in the first address information; Determining a matching model corresponding to the address field; The second address information is input into the matching model to determine whether the second address information matches the address field, so as to determine whether the address information is abnormal address information.

7. An electronic device, characterized in that: include: processor; A memory having a computer program stored thereon, wherein the computer program is executed by the processor when it is executed: The abnormal order identification method as described in any one of claims 1 to 5.

8. A storage medium, characterized in that: The storage medium stores a computer program, which is executed by the processor when it is run: The abnormal order identification method as described in any one of claims 1 to 5.

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