WO2022262114A1 - Procédé de traitement d'informations de déclaration en douane combinant la rpa et l'ia et dispositif de traitement - Google Patents

Procédé de traitement d'informations de déclaration en douane combinant la rpa et l'ia et dispositif de traitement Download PDF

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WO2022262114A1
WO2022262114A1 PCT/CN2021/114323 CN2021114323W WO2022262114A1 WO 2022262114 A1 WO2022262114 A1 WO 2022262114A1 CN 2021114323 W CN2021114323 W CN 2021114323W WO 2022262114 A1 WO2022262114 A1 WO 2022262114A1
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customs declaration
commodity
customs
entry
item
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PCT/CN2021/114323
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English (en)
Chinese (zh)
Inventor
潘庚生
汪冠春
胡一川
褚瑞
李玮
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北京来也网络科技有限公司
来也科技(北京)有限公司
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Publication of WO2022262114A1 publication Critical patent/WO2022262114A1/fr

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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/3331—Query processing
    • G06F16/334—Query execution
    • G06F16/3343—Query execution using phonetics
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/38—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/383—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content

Definitions

  • the present disclosure relates to the technical fields of RPA and AI, and in particular to a processing method and processing device combining RPA and AI for customs declaration information.
  • Robotic Process Automation uses specific "robot software” to simulate human operations on computers and automatically execute process tasks according to rules.
  • AI Artificial Intelligence
  • the customs declaration personnel of Sinotrans need to declare hundreds of thousands of freight manifests every day, and it is required to input the customs declaration forms with different formats from each consignment company into the unified standard customs declaration form, and the business personnel need to spend a lot of money More human and material resources are invested in this work, resulting in poor timeliness, low efficiency, and error-prone.
  • the present disclosure aims to solve one of the technical problems in the related art at least to a certain extent.
  • the first purpose of this disclosure is to propose a processing method combining RPA and AI customs declaration information, which can improve timeliness, save labor costs, reduce the risk of input errors, and improve efficiency.
  • the second purpose of the present disclosure is to propose a processing device combining RPA and AI customs declaration information.
  • the third object of the present disclosure is to provide an electronic device.
  • a fourth object of the present disclosure is to propose a non-transitory computer-readable storage medium.
  • a fifth object of the present disclosure is to provide a computer program product.
  • the embodiment of the first aspect of the present disclosure proposes a processing method combining RPA and AI customs declaration information, including the following steps: based on optical character recognition OCR (Optical Character Recognition, optical character recognition) to carry out the content of the target customs declaration document Identification, to obtain the customs declaration data of multiple customs declaration items in the target customs declaration document; the public items in the multiple customs declaration items, according to the preset first robot process automation RPA operation process, the customs declaration of the public items Entering the data into the corresponding first standard entry in the customs declaration interface; querying the commodity identification from the multiple customs declaration entries; according to the commodity identification, determining the commodity entry associated with the commodity identification from the multiple customs declaration entries, And enter the customs declaration data of the commodity item into the second standard item corresponding to the customs declaration interface.
  • OCR Optical Character Recognition, optical character recognition
  • content recognition is performed on the target customs declaration document based on optical character recognition (OCR), so as to obtain the customs declaration data of multiple customs declaration items in the target customs declaration document;
  • OCR optical character recognition
  • the customs declaration data of public entries is entered into the corresponding first standard entry in the customs declaration interface;
  • the commodity identification is queried from multiple customs declaration entries;
  • the commodity identification from multiple Determine the commodity entry associated with the commodity identifier in the first customs declaration entry, and enter the customs declaration data of the commodity entry into the second standard entry corresponding to the customs declaration interface. Therefore, the method can improve timeliness, save labor costs, reduce the risk of input errors, and improve efficiency.
  • processing method combining RPA and AI customs declaration information proposed in the first aspect of the present disclosure may also have the following additional technical features:
  • the commodity item associated with the commodity identifier is determined from the plurality of customs declaration entries, and the customs declaration data of the commodity entry is entered into the corresponding customs declaration interface.
  • the second standard entry includes: querying the relationship between the commodity identifier and the commodity entry according to the commodity identifier; if the commodity entry associated with the commodity identifier is found, according to the preset second RPA operation process, Enter the customs declaration data of the commodity entry into the second standard entry corresponding to the customs declaration interface; if no commodity entry associated with the commodity identifier is found, according to the second standard entry in the customs declaration interface, from the Searching for a customs declaration item with similar semantics among the plurality of customs declaration items is used as the commodity item, and entering the customs declaration data of the commodity item into the second standard item corresponding to the customs declaration interface.
  • searching for customs declaration items with similar semantics from the plurality of customs declaration items as the commodity item includes: searching the customs declaration interface In the second standard entry, determine the semantic similarity with each of the customs declaration entries based on natural language processing NLP; according to the customs declaration entry with the highest semantic similarity, determine the semantic similarity with the second standard entry Product entry.
  • the commodity identifiers from the multiple customs declaration entries after querying the commodity identifiers from the multiple customs declaration entries, it further includes: inputting the commodity identifiers into the corresponding standard entries in the customs declaration interface, so as to display all items in the customs declaration interface. Describe the second standard item.
  • the target customs declaration document before performing content recognition on the target customs declaration document based on optical character recognition (OCR) to obtain the customs declaration data of multiple customs declaration items in the target customs declaration document, it further includes: according to the target customs declaration document The document type identifies each of the said customs declaration items to be identified.
  • OCR optical character recognition
  • the OCR-based optical character recognition is used to perform content recognition on the target customs declaration document, so as to obtain customs declarations of multiple customs declaration items in the target customs declaration document
  • the data includes: performing content identification on the customs declaration form based on OCR, so as to obtain customs declaration data of multiple customs declaration items contained in the customs declaration form.
  • the commodity item associated with the commodity identifier is determined from the plurality of customs declaration entries, and the customs declaration data of the commodity entry is entered into the corresponding customs declaration interface.
  • the second standard item it also includes: if there is the first standard item and/or the second standard item not entered in the customs declaration interface, based on OCR, the rest of the customs declaration form Target customs declaration documents for content identification.
  • the embodiment of the second aspect of the present disclosure proposes a processing device combining RPA and AI customs declaration information, including: a first recognition module, used to perform content recognition on the target customs declaration document based on optical character recognition (OCR), to obtain The customs declaration data of multiple customs declaration entries in the target customs declaration document; the first entry module is used to use the public entries in the multiple customs declaration entries according to the preset first robotic process automation RPA operation process, and transfer the public entries The customs declaration data of the entry is entered into the corresponding first standard entry in the customs declaration interface; the query module is used to query the commodity identification from the multiple customs declaration entries; the second input module is used to select from the multiple Determine the commodity entry associated with the commodity identifier in the first customs declaration entry, and enter the customs declaration data of the commodity entry into the second standard entry corresponding to the customs declaration interface.
  • OCR optical character recognition
  • the first recognition module performs content recognition on the target customs declaration document based on optical character recognition (OCR), so as to obtain the customs declaration data of multiple customs declaration items in the target customs declaration document, and through the second An input module inputs the public items among the multiple customs declaration items into the corresponding first standard item in the customs declaration interface according to the pre-set first robotic process automation RPA operation process, and uses the query module to select from multiple items
  • OCR optical character recognition
  • the commodity identification is queried in the customs declaration entry, and the commodity entry associated with the commodity identification is determined from the multiple customs declaration entries through the second input module according to the commodity logo, and the customs declaration data of the commodity entry is entered into the second standard entry corresponding to the customs declaration interface. Therefore, the device can improve timeliness, save labor costs, reduce the risk of input errors, and improve efficiency.
  • processing device combining RPA and AI customs declaration information proposed in the second aspect of the present disclosure may also have the following additional technical features:
  • the second entry module includes: a query unit, configured to query the relationship between the commodity identifier and the commodity entry according to the commodity identifier; In the case of a commodity item associated with the commodity identifier, according to the preset second RPA operation process, the customs declaration data of the commodity entry is entered into the second standard entry corresponding to the customs declaration interface; the second input unit is used to If no commodity item associated with the commodity identifier is found, according to the second standard entry in the customs declaration interface, query a customs declaration entry with similar semantics from the plurality of customs declaration entries as the commodity entry, and Entering the customs declaration data of the commodity item into the second standard item corresponding to the customs declaration interface.
  • the second entry unit includes: a first determining subunit, configured to determine, based on natural language processing (NLP), the items related to each of the customs declarations for the second standard item in the customs declaration interface. Semantic similarity between items; a second determining subunit, configured to determine commodity items semantically similar to the second standard item according to the customs declaration item with the highest semantic similarity.
  • NLP natural language processing
  • the above-mentioned processing device further includes: a display module, configured to enter the commodity identifier into a corresponding standard item in the customs declaration interface, so as to display the second standard item on the customs declaration interface .
  • the above processing device further includes: a determining module configured to determine each of the customs declaration items to be identified according to the document type of the target customs declaration document.
  • the first identification module includes: an identification unit, configured to perform content identification on the customs declaration form based on OCR, so as to obtain the The customs declaration data of multiple customs declaration items included in the customs declaration form.
  • the above-mentioned processing device further includes: a second identification module, configured to have the first standard item and/or the second standard item not entered in the customs declaration interface Next, based on OCR, perform content identification on the rest of the target customs declaration documents except the customs declaration form.
  • a second identification module configured to have the first standard item and/or the second standard item not entered in the customs declaration interface Next, based on OCR, perform content identification on the rest of the target customs declaration documents except the customs declaration form.
  • the embodiment of the third aspect of the present disclosure provides an electronic device, including: at least one processor; and a memory connected to the at least one processor in communication; wherein, the memory stores information that can be used by the Instructions executed by at least one processor, the instructions are executed by the at least one processor, so that the at least one processor can execute the above-mentioned processing method combining RPA and AI customs declaration information.
  • the embodiment of the fourth aspect of the present disclosure proposes a non-transitory computer-readable storage medium on which a computer program is stored, and when the program is executed by a processor, the above-mentioned processing of combining RPA and AI customs declaration information is realized method.
  • the embodiment of the fifth aspect of the present disclosure proposes a computer program product.
  • the instructions in the computer program product are executed by the processor, the above-mentioned processing method combining RPA and AI customs declaration information is executed.
  • FIG. 1 is a schematic flow diagram of a processing method combining RPA and AI customs declaration information provided by an embodiment of the present disclosure
  • FIG. 2 is a schematic flow diagram of a processing method combining RPA and AI customs declaration information provided by an embodiment of the present disclosure
  • Fig. 3 is a schematic flow diagram of a processing method combining RPA and AI customs declaration information provided by a specific embodiment of the present disclosure
  • FIG. 4 is an overall business flow chart of a processing method combining RPA and AI customs declaration information provided by a specific embodiment of the present disclosure
  • FIG. 5 is a schematic block diagram of a processing device combining RPA and AI customs declaration information provided by an embodiment of the present disclosure
  • FIG. 6 shows a block diagram of an exemplary electronic device suitable for use in implementing embodiments of the present disclosure.
  • the customs declaration personnel of Sinotrans need to declare hundreds of thousands of freight manifests every day, requiring the customs declaration data of various shipping companies to be input into a unified standard customs declaration form, and the business personnel need to spend a lot of money Human and material resources are invested in this work, and the specific process is as follows: manually check the customs declaration list data, and reply to the supplier's customs declaration data after the verification is correct; manually log in to the customs declaration system according to the data of the customs declaration documents, and the corresponding fields The data needs to be entered into the customs declaration system one by one; the customs declaration system will perform verification according to the entered data, and complete the submission after the verification is passed.
  • Customs declaration personnel need to collect customs declaration forms every day, and then input them into the customs declaration system according to the customs declaration forms.
  • customs declaration documents there are many styles of customs declaration documents, and the fields of each commodity code are in different positions. It is very troublesome to find, and the font is also small ,
  • the commodity code is very long, and 3,000 customs declaration forms need to be entered every day.
  • the work tasks are heavy, and the work efficiency and job satisfaction are not high.
  • this disclosure proposes a processing method combining RPA and AI customs declaration information, which can improve timeliness, save labor costs, reduce the risk of input errors, and improve efficiency.
  • FIG. 1 is a schematic flowchart of a processing method combining RPA and AI customs declaration information provided by an embodiment of the present disclosure.
  • the processing method of combining RPA and AI customs declaration information in the embodiment of the present disclosure includes the following steps:
  • S11 performing content recognition on the target customs declaration document based on optical character recognition (OCR), so as to obtain customs declaration data of multiple customs declaration items in the target customs declaration document.
  • OCR optical character recognition
  • target customs declaration documents such as including at least one of customs declaration form, packing list, waybill, various licenses, export collection verification and write-off form, power of attorney, contract, certificate of origin, etc. .
  • the target customs declaration document needs to be of the same quality as the sample, such as a clear scan.
  • What OCR can do is to recognize the frame line of the target customs declaration document, extract the content of each cell, and return the position of each item in the cell.
  • what needs to be done for extraction is to structure the frameless table, such as aligning rows and columns to extract structured information. It should be noted that during the extraction process, if the unit of measurement of an object in the target customs declaration document is different, normalization processing is required, that is, the unit of measurement is unified.
  • Multiple customs declaration entries include public entries and commodity entries, where the public entry is a public field extracted through OCR, including at least one of the domestic consignor, overseas consignee, exit customs, export date, declaration date, etc. ;
  • Commodity entries are commodity identifiers and element fields extracted through OCR, wherein the element fields include at least one of brand type, export preference, use, material, brand, specification or model.
  • the pre-set first robot process automation RPA operation process is the order in which the first robot fills in the customs declaration data of public items, for example, public items such as domestic consignor, overseas consignee, exit customs, export date 1.
  • the customs declaration data of the declaration date is entered into the corresponding first standard entry (public column) in the customs declaration interface.
  • the first standard entry can be shown in Table 1 below.
  • the domestic consignor and overseas consignee After obtaining the domestic consignor, overseas consignee, exit customs, export date, and declaration date, according to the pre-set first robotic process automation RPA operation process, the domestic consignor and overseas consignee
  • the customs declaration data of , exit customs, export date, and declaration date are entered in the corresponding first standard entry in the customs declaration interface in sequence.
  • Commodity identification refers to the collective term of various expressions and instructions used to identify a commodity or its characteristics and performance, for example, it may be a commodity number.
  • the product identification select the product item associated with the product identification from multiple customs declaration items, such as at least one of brand type, export preference, use, material, brand, specification or model, and submit the specific customs declaration data Enter the second standard entry corresponding to the customs declaration interface, the second standard entry can be shown in Table 2 below.
  • Form 2 After completing Form 1, Form 2 and Form 3, the customs declaration form in standard format can be exported.
  • the processing method of customs declaration information combined with RPA and AI in the embodiment of the present disclosure based on optical character recognition (OCR), performs content recognition on the target customs declaration document to obtain customs declaration data of multiple customs declaration items in the target customs declaration document, and multiple customs declaration items
  • OCR optical character recognition
  • the public entry in the public entry will enter the customs declaration data of the public entry into the corresponding first standard entry in the customs declaration interface, and query the commodity identification from multiple customs declaration entries.
  • a commodity entry associated with the commodity identifier is determined from the multiple customs declaration entries, and the customs declaration data of the commodity entry is entered into a second standard entry corresponding to the customs declaration interface.
  • this method can save manual operation steps, save labor costs, greatly improve efficiency, and greatly reduce the work pressure of personnel; because before the need to see with eyes, human errors are prone to occur during the data entry process, and In terms of data review, the system and paper-based document data are often inconsistent, which increases the risk of customs declaration.
  • This disclosure optimizes the process, which reduces the risk to a certain extent and makes the entry error rate controllable.
  • step S14 may include the following steps:
  • search for customs declaration entries with similar semantics as commodity entries from multiple customs declaration entries including: for the second standard entry in the customs declaration interface, based on natural language processing NLP Determine the semantic similarity with each customs declaration item; determine the commodity item semantically similar to the second standard item according to the customs declaration item with the highest semantic similarity.
  • the text needs to be segmented first.
  • the original text may consist of hundreds of thousands of Chinese entries, and the latitude is very high.
  • the words with little significance for decision-making are generally eliminated first, which is the purpose of feature word extraction.
  • the relationship between the commodity identifier and the commodity entry is queried from multiple customs declaration entries according to the commodity identifier.
  • the specific customs declaration data is entered into the second standard entry corresponding to the interface;
  • the semantic similarity between the customs declaration entry and each customs declaration entry is determined based on natural language processing NLP, and the customs declaration with the highest semantic similarity is selected entry, as a commodity entry semantically similar to the second standard entry.
  • the second standard item after querying the commodity identification from the multiple customs declaration items, it also includes: entering the commodity identification into the corresponding standard item in the customs declaration interface, so as to display the second standard item on the customs declaration interface.
  • OCR optical character recognition
  • customs declaration There are many types of documents that need to be reviewed for customs declaration, such as customs declaration, packing list, waybill, various licenses, export collection verification and write-off form, power of attorney, contract, certificate of origin, etc.
  • Each type of document requires different data to be extracted.
  • the format of each type of document may be different, and the packaging and unit price of the same product may be different.
  • target customs declaration documents For different types of target customs declaration documents, you can first determine the customs declaration items to be identified. For example, when the target customs declaration document is a customs declaration form, determine the customs declaration items to be identified as: domestic consignor, overseas consignee, exit customs Type, export date, declaration date, brand type, export preference, use, material, brand, specification or model; when the target customs declaration document is a contract or invoice, determine the customs declaration items to be identified as: brand, specification or model . In this way, customs declaration items can be identified more quickly based on the target customs declaration documents, further improving efficiency.
  • Fig. 3 is a schematic flowchart of a processing method combining RPA and AI customs declaration information provided by a specific embodiment of the present disclosure. As shown in Figure 3, when the target customs declaration document includes a customs declaration form, the processing method of combining RPA and AI customs declaration information according to the embodiment of the present disclosure includes the following steps:
  • the packing list, waybill, various licenses, and export collection checks other than the customs declaration form can be checked.
  • Content identification of target customs declaration documents such as sales order, power of attorney, contract, certificate of origin, etc., to obtain the first standard item and/or the second standard item that needs to be entered.
  • customers such as customer 1, customer 2, customer 3...etc. send their own company's customs declaration to Sinotrans company.
  • the format of the customs declaration form of each customer may be different, for example, customer 1 uses the customs declaration form 1, customer 2 uses the customs declaration form 2, customer 3 uses the customs declaration form 3, ....
  • the first robot recognizes the content of the customs declaration form based on optical character recognition (OCR) to extract the public fields and commodity numbers.
  • OCR optical character recognition
  • the public fields include domestic consignor, overseas consignee, exit customs, export date, declaration date, ...
  • the element fields are extracted from the customs declaration form according to the commodity number, where the element fields include brand type, export preference, use, material, ....
  • the processing method of customs declaration information combined with RPA and AI in the embodiment of the present disclosure based on optical character recognition (OCR), performs content recognition on the customs declaration form, so as to obtain the customs declaration data of multiple customs declaration items in the target customs declaration document.
  • OCR optical character recognition
  • the customs declaration data of the public entry is entered into the corresponding first standard entry in the customs declaration interface, and the commodity identification is queried from multiple customs declaration entries.
  • the commodity identification from Determine the commodity entry associated with the commodity identifier among the multiple customs declaration entries, and enter the customs declaration data of the commodity entry into the second standard entry corresponding to the customs declaration interface.
  • the method can save manual operation steps and labor costs, greatly improve efficiency, greatly reduce the work pressure of personnel, and control the input error rate.
  • the present disclosure also proposes a processing device combining RPA and AI customs declaration information.
  • Fig. 5 is a schematic block diagram of a processing device combining RPA and AI customs declaration information provided by an embodiment of the present disclosure.
  • the processing device combining RPA and AI customs declaration information in the embodiment of the present disclosure includes: a first identification module 51 , a first entry module 52 , a query module 53 and a second entry module 54 .
  • the first recognition module 51 is configured to perform content recognition on the target customs declaration document based on optical character recognition (OCR), so as to obtain customs declaration data of multiple customs declaration items in the target customs declaration document.
  • the first input module 52 is used to input the public items among the multiple customs declaration items into the corresponding first standard items in the customs declaration interface according to the preset first robotic process automation RPA operation process.
  • the inquiry module 53 is used for inquiring commodity identifiers from multiple customs declaration entries.
  • the second input module 54 is used to determine the commodity item associated with the commodity identifier from multiple customs declaration entries according to the commodity identifier, and enter the customs declaration data of the commodity item into the second standard entry corresponding to the customs declaration interface.
  • the second input module 54 includes: a query unit, a first input unit and a second input unit.
  • the query unit is used to query the relationship between the commodity identifier and the commodity entry according to the commodity identifier;
  • the first entry unit is used to query the commodity entry associated with the commodity identifier according to the preset second RPA
  • the operation process is to enter the customs declaration data of the commodity entry into the second standard entry corresponding to the customs declaration interface;
  • the second entry unit is used to, according to the second standard entry in the customs declaration interface, if no commodity entry associated with the commodity identifier is found, Query customs declaration entries with similar semantics from multiple customs declaration entries as commodity entries, and enter the customs declaration data of the commodity entries into the second standard entry corresponding to the customs declaration interface.
  • the second entry unit includes: a first determination subunit and a second determination subunit.
  • the first determining subunit is configured to determine the semantic similarity between the second standard item in the customs declaration interface and each customs declaration item based on natural language processing (NLP).
  • the second determination subunit is configured to determine commodity items semantically similar to the second standard item according to the customs declaration item with the highest semantic similarity.
  • the above-mentioned processing device combining RPA and AI customs declaration information further includes: a display module, configured to enter the commodity identifier into the corresponding standard item in the customs declaration interface, so as to display the second standard item on the customs declaration interface.
  • the above-mentioned processing device combining RPA and AI customs declaration information further includes: a determination module configured to determine each customs declaration item to be identified according to the document type of the target customs declaration document.
  • the first identification module 51 includes: an identification unit for performing content identification on the customs declaration form based on OCR, so as to obtain multiple items contained in the customs declaration form; The customs declaration data of the customs declaration item.
  • the above-mentioned processing device combining RPA and AI customs declaration information further includes: a second identification module, used for unrecorded first standard items and/or second standard items in the customs declaration interface In this case, based on OCR, perform content identification on the rest of the target customs declaration documents except the customs declaration form.
  • the first recognition module performs content recognition on the target customs declaration document based on optical character recognition (OCR), so as to obtain the customs declaration data of multiple customs declaration items in the target customs declaration document, and through the second An input module inputs the public items among the multiple customs declaration items into the corresponding first standard item in the customs declaration interface according to the pre-set first robotic process automation RPA operation process, and uses the query module to select from multiple items
  • OCR optical character recognition
  • the commodity identification is queried in the customs declaration entry, and the commodity entry associated with the commodity identification is determined from the multiple customs declaration entries through the second input module according to the commodity logo, and the customs declaration data of the commodity entry is entered into the second standard entry corresponding to the customs declaration interface. Therefore, the device can improve timeliness, save labor costs, reduce the risk of input errors, and improve efficiency.
  • the present disclosure also proposes an electronic device.
  • An electronic device includes: at least one processor; and a memory communicatively connected to the at least one processor; wherein, the memory stores instructions executable by the at least one processor, and the instructions are executed by the at least one processor to Enabling at least one processor to execute the above-mentioned processing method combining RPA and AI customs declaration information.
  • the present disclosure also proposes a non-transitory computer-readable storage medium.
  • the non-transitory computer-readable storage medium of the embodiment of the present disclosure stores a computer program thereon, and when the program is executed by a processor, the above-mentioned processing method combining RPA and AI customs declaration information is realized.
  • the present disclosure also proposes a computer program product.
  • the computer program product of the embodiment of the present disclosure when the instructions in the computer program product are executed by the processor, executes the above-mentioned processing method combining RPA and AI customs declaration information.
  • FIG. 6 shows a block diagram of an exemplary electronic device suitable for use in implementing embodiments of the present disclosure.
  • the electronic device 12 shown in FIG. 6 is only an example, and should not limit the functions and scope of use of the embodiments of the present disclosure.
  • electronic device 12 takes the form of a general-purpose computing device.
  • Components of electronic device 12 may include, but are not limited to, one or more processors or processing units 16, system memory 28, bus 18 connecting various system components including system memory 28 and processing unit 16.
  • Bus 18 represents one or more of several types of bus structures, including a memory bus or memory controller, a peripheral bus, an accelerated graphics port, a processor, or a local bus using any of a variety of bus structures.
  • these architectures include but are not limited to Industry Standard Architecture (Industry Standard Architecture; hereinafter referred to as: ISA) bus, Micro Channel Architecture (Micro Channel Architecture; hereinafter referred to as: MAC) bus, enhanced ISA bus, video electronics Standards Association (Video Electronics Standards Association; hereinafter referred to as: VESA) local bus and Peripheral Component Interconnection (hereinafter referred to as: PCI) bus.
  • Electronic device 12 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by electronic device 12 and include both volatile and nonvolatile media, removable and non-removable media.
  • the memory 28 may include a computer system readable medium in the form of a volatile memory, such as a random access memory (Random Access Memory; hereinafter referred to as: RAM) 30 and/or a cache memory 32 .
  • RAM Random Access Memory
  • the electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media.
  • storage system 34 may be used to read from and write to non-removable, non-volatile magnetic media (not shown in Figure 7, commonly referred to as "hard drives").
  • a disk drive for reading and writing to a removable nonvolatile disk may be provided, as well as a disk drive for removable nonvolatile disks (such as a CD-ROM (Compact Disc Read Only Memory; hereinafter referred to as: CD-ROM), Digital Video Disc Read Only Memory (hereinafter referred to as: DVD-ROM) or other optical media).
  • each drive may be connected to bus 18 via one or more data media interfaces.
  • Memory 28 may include at least one program product having a set (eg, at least one) of program modules configured to perform the functions of various embodiments of the present disclosure.
  • a program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in memory 28, such program modules 42 including but not limited to an operating system, one or more application programs, other program modules, and program data , each or some combination of these examples may include implementations of network environments.
  • the program modules 42 generally perform the functions and/or methods of the embodiments described in this disclosure.
  • Electronic device 12 may also communicate with one or more external devices 14 (e.g., a keyboard, pointing device, display 24, etc.), and with one or more devices that enable a user to interact with the computer system/server 12, and/or Or communicate with any device (eg, network card, modem, etc.) that enables the computer system/server 12 to communicate with one or more other computing devices. Such communication may occur through input/output (I/O) interface 22 .
  • external devices 14 e.g., a keyboard, pointing device, display 24, etc.
  • any device eg, network card, modem, etc.
  • I/O input/output
  • the electronic device 12 can also communicate with one or more networks (such as a local area network (Local Area Network; hereinafter referred to as: LAN), a wide area network (Wide Area Network; hereinafter referred to as: WAN) and/or a public network, such as the Internet, through the network adapter 20. ) communication.
  • network adapter 20 communicates with other modules of electronic device 12 via bus 18 .
  • other hardware and/or software modules may be used in conjunction with electronic device 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID (Redundant Arrays of Independent Disks, disk array) systems, tape drives, and data backup storage systems.
  • the processing unit 16 executes various functional applications and data processing by running the programs stored in the system memory 28 , such as implementing the methods mentioned in the foregoing embodiments.
  • first and second are used for descriptive purposes only, and cannot be interpreted as indicating or implying relative importance or implicitly specifying the quantity of indicated technical features. Thus, features defined as “first” and “second” may explicitly or implicitly include at least one of these features. In the description of the present disclosure, “plurality” means at least two, such as two, three, etc., unless otherwise specifically defined.
  • a "computer-readable medium” may be any device that can contain, store, communicate, propagate or transmit a program for use in or in conjunction with an instruction execution system, device or device.
  • computer-readable media include the following: electrical connection with one or more wires (electronic device), portable computer disk case (magnetic device), random access memory (RAM), Read Only Memory (ROM), Erasable and Editable Read Only Memory (EPROM or Flash Memory), Fiber Optic Devices, and Portable Compact Disc Read Only Memory (CDROM).
  • the computer-readable medium may even be paper or other suitable medium on which the program can be printed, since the program can be read, for example, by optically scanning the paper or other medium, followed by editing, interpretation or other suitable processing if necessary.
  • the program is processed electronically and stored in computer memory.
  • various parts of the present disclosure may be implemented in hardware, software, firmware or a combination thereof.
  • various steps or methods may be implemented by software or firmware stored in memory and executed by a suitable instruction execution system.
  • a suitable instruction execution system For example, if implemented in hardware as in another embodiment, it can be implemented by any one or a combination of the following techniques known in the art: a discrete Logic circuits, ASICs with suitable combinational logic gates, Programmable Gate Arrays (PGA), Field Programmable Gate Arrays (FPGA), etc.
  • each functional unit in each embodiment of the present disclosure may be integrated into one processing module, each unit may exist separately physically, or two or more units may be integrated into one module.
  • the above-mentioned integrated modules can be implemented in the form of hardware or in the form of software function modules. If the integrated modules are realized in the form of software function modules and sold or used as independent products, they can also be stored in a computer-readable storage medium.
  • the storage medium mentioned above may be a read-only memory, a magnetic disk or an optical disk, and the like.

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Abstract

La présente invention concerne un procédé et un dispositif de traitement d'informations de déclaration en douane combinant l'automatisation des processus robotiques (RPA) et l'IA. Le procédé comprend les étapes suivantes : réalisation d'une reconnaissance de contenu sur un document de déclaration en douane cible sur la base d'une reconnaissance optique de caractères (OCR) afin d'obtenir des données de déclaration en douane d'une pluralité d'articles de déclaration en douane dans le document de déclaration en douane cible ; pour un article public dans la pluralité d'articles de déclaration en douane, selon un premier processus d'opération de RPA prédéfini, saisie des données de déclaration en douane de l'article public dans un premier article standard correspondant dans une interface de déclaration en douane ; interrogation d'un identifiant de marchandise à partir de la pluralité d'articles de déclaration en douane ; et en fonction de l'identifiant de marchandise, détermination, à partir de la pluralité d'articles de déclaration en douane, d'un article de marchandise associé à l'identifiant de marchandise, et saisie des données de déclaration en douane de l'article de marchandise dans un deuxième article standard correspondant dans l'interface de déclaration en douane. De cette manière, le procédé peut améliorer la rapidité d'exécution, économiser des coûts de main d'œuvre, réduire le risque d'erreurs d'entrée et améliorer l'efficacité.
PCT/CN2021/114323 2021-06-16 2021-08-24 Procédé de traitement d'informations de déclaration en douane combinant la rpa et l'ia et dispositif de traitement WO2022262114A1 (fr)

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CN117236310B (zh) * 2023-10-26 2024-08-02 湖南中拓信息科技有限公司 基于ocr技术的账单识别方法、系统和可读存储介质

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