WO2022054165A1 - Dispositif de traitement de données, procédé de traitement de données et programme - Google Patents

Dispositif de traitement de données, procédé de traitement de données et programme Download PDF

Info

Publication number
WO2022054165A1
WO2022054165A1 PCT/JP2020/034103 JP2020034103W WO2022054165A1 WO 2022054165 A1 WO2022054165 A1 WO 2022054165A1 JP 2020034103 W JP2020034103 W JP 2020034103W WO 2022054165 A1 WO2022054165 A1 WO 2022054165A1
Authority
WO
WIPO (PCT)
Prior art keywords
text information
data
past
departments
apportionment
Prior art date
Application number
PCT/JP2020/034103
Other languages
English (en)
Japanese (ja)
Inventor
鴻鵬 葛
顕 松田
智 小俣
啓太郎 森
Original Assignee
ファーストアカウンティング株式会社
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by ファーストアカウンティング株式会社 filed Critical ファーストアカウンティング株式会社
Priority to JP2020547247A priority Critical patent/JP6810306B1/ja
Priority to PCT/JP2020/034103 priority patent/WO2022054165A1/fr
Priority to JP2020205042A priority patent/JP2022045868A/ja
Publication of WO2022054165A1 publication Critical patent/WO2022054165A1/fr

Links

Images

Classifications

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

Definitions

  • the present invention relates to a data processing device, a data processing method and a program for processing voucher data.
  • the read amount may be apportioned to multiple departments.
  • a journal entry rule is provided for voucher data to be apportioned by a plurality of departments, and when journal data is created from the voucher data, journal data is generated based on the journal entry rule. is doing.
  • the voucher data is new voucher data for which journal data has not been registered so far, there is no journal entry rule.
  • the accounting staff can manually apportion the data to multiple departments. It was necessary to create data, which reduced business efficiency.
  • the present invention has been made in view of these points, and an object thereof is to be able to create journal data corresponding to the apportionment to a plurality of departments for new voucher data.
  • the data processing device is extracted from a data acquisition unit for acquiring voucher data, an extraction unit for extracting text information from the voucher data, and voucher data acquired in the past.
  • the text information is based on at least a part of the past text information and the journal data created in the past corresponding to the past text information, in which the proportion of the amount to each of one or more departments is specified. It has an apportionment rate determining unit that determines the apportionment rate of an amount corresponding to at least a part thereof to each of the one or more departments, and an output unit that outputs the determined apportionment rate.
  • the past text information includes a product name or a service name and a transaction amount corresponding to the product name or the service name
  • the apportionment rate determination unit includes the product name or the service name included in the text information. And, the apportionment rate to each of the above-mentioned one or more departments corresponding to the transaction amount corresponding to the product name or the service name may be determined.
  • the past text information includes date information, and the apportionment rate determination unit may determine the apportionment rate for each of the one or more departments corresponding to the dates included in the text information.
  • the apportionment rate determination unit corresponds to at least a part of the text information and information about the business partner corresponding to the text information based on the information about the business partner corresponding to the past text information and the journal data.
  • the apportionment rate to each of the above-mentioned one or more departments may be determined.
  • the apportionment rate determination unit Based on the past text information, the information about the person who entered the journal data, and the journal data, the apportionment rate determination unit has at least a part of the text information and the journal data corresponding to the text information. The apportionment rate to each of the above-mentioned one or more departments corresponding to the input person may be determined.
  • the apportionment rate determination unit is based on the result of learning from the teacher data including the past text information and the journal data registered in the data processing device in the past corresponding to the past text information.
  • the apportionment rate to each of the above-mentioned one or more departments corresponding to the product name or service name included in the above and the transaction amount corresponding to the product name or service name may be determined.
  • the data processing device includes at least a part of journal data registered in the accounting system corresponding to the apportionment rate output by the output unit, and at least a part of the past text information corresponding to the journal data. It may further have a learning unit that performs the learning based on the teacher data.
  • the apportionment rate determination unit When the extracted text information does not correspond to a preset rule for determining the apportionment rate, the apportionment rate determination unit at least the text information based on the result learned from the teacher data. When the apportionment rate to each of the one or more departments corresponding to a part is determined and the extracted text information corresponds to the rule, the apportionment rate to each of the one or more departments is based on the rule. May be determined.
  • the apportionment rate determination unit has at least the text information based on the result of learning from the second teacher data including the past text information and information indicating whether or not the past text information is apportioned to a plurality of departments.
  • the text is based on the result learned from the teacher data.
  • the apportionment rate of information to each of a plurality of departments may be determined.
  • the data processing method is a step of acquiring voucher data executed by a computer, a step of extracting text information from the voucher data, and a voucher data acquired in the past.
  • the text is based on at least a portion of the past text information extracted and journal data created in the past corresponding to the past text information that specifies the proportion of the amount to each of one or more departments. It has a step of determining the apportionment rate of the amount of money corresponding to at least a part of the information to each of the one or more departments, and a step of outputting the determined apportionment rate.
  • the computer is extracted from the data acquisition unit for acquiring voucher data, the extraction unit for extracting text information from the voucher data, and the voucher data acquired in the past. At least some of the past text information and at least the text information, based on the journal data created in the past corresponding to the past text information, with the apportionment rate of the amount to each of one or more departments specified. It functions as an apportionment rate determination unit that determines the apportionment rate of the corresponding amount of money to each of the one or more departments, and an output unit that outputs the determined apportionment rate.
  • journal data corresponding to the apportionment to a plurality of departments for new voucher data.
  • FIG. 1 is a diagram for explaining an outline of the data processing device 1.
  • the data processing device 1 generates journal data using the result of analyzing a character string included in the voucher data generated by reading the voucher by a reading device 2 such as a scanner or a digital camera, and registers the journal data in the accounting system 3.
  • It is a device for, for example, a computer.
  • the data processing device 1 may be configured by one computer or may be configured by a plurality of computers.
  • a voucher is a voucher that shows information about a product such as a product name and a price of the product, such as an invoice or a purchase order. In the present embodiment, the description will proceed by taking as an example the case where the voucher is an invoice received by the user of the data processing device 1 as the demandee.
  • FIG. 2 is a diagram showing an example of an invoice received by the demandee.
  • the invoice shown in FIG. 2 describes the name, address, and contact information of the business operator that issued the invoice, that is, the requester who charges the price in the transaction.
  • the invoice includes the subject (January 2020 shown in Fig. 2), the purchase date of the product to be billed, the product name, the price of the product (that is, the subtotal), and the total price of multiple products (that is, the billing amount). ) Is described.
  • the data processing device 1 extracts text information by performing OCR processing from the invoice data generated by the reading device 2 reading the invoice, and based on the extracted text information, the amount of money to each of one or more departments. Create journal data with a specified apportionment rate.
  • the data processing device 1 has at least a part of past text information extracted from invoice data acquired in the past and one or more departments created in the past corresponding to the past text information. Determine the apportionment rate for each of one or more departments corresponding to at least a portion of the textual information, based on the results learned from the teacher data, including at least a portion of the specified journal data. .. By doing so, the data processing device 1 can create journal data including the amount corresponding to the apportionment to a plurality of departments and the department information of the apportionment destination for the new invoice data.
  • FIG. 3 is a diagram showing a functional configuration of the data processing device 1.
  • the data processing device 1 includes a communication unit 11, an operation unit 12, a display unit 13, a storage unit 14, and a control unit 15.
  • the control unit 15 includes a data acquisition unit 151, an extraction unit 152, an account item determination unit 153, a proportional division rate determination unit 154, a journal data creation unit 155 as an output unit, a registration unit 156, and a learning unit 157.
  • the communication unit 11 is a communication interface for connecting to a network (for example, an intranet or the Internet), and provides a communication controller for receiving data from the reading device 2 and transmitting / receiving data to / from another computer.
  • a network for example, an intranet or the Internet
  • the operation unit 12 performs an operation of registering the journal data created from the invoice data by the data processing device 1, a keyboard, a mouse, a display, etc. for correcting the apportionment ratio of the journal data to one or more departments.
  • the display unit 13 is a display for displaying information.
  • the display unit 13 displays information based on the instructions of the control unit 15.
  • the storage unit 14 has a storage medium such as a ROM (ReadOnlyMemory), a RAM (RandomAccessMemory), and a hard disk.
  • the storage unit 14 stores a program executed by the control unit 15. Further, the storage unit 14 stores the invoice data generated by the reading device 2 reading the invoice.
  • the storage unit 14 further stores a journal database for storing journal data created from the invoice data.
  • FIG. 4 is a diagram showing an example of a journal database.
  • the journal database stores, for example, the same information as the information registered in the accounting system or some information among the information registered in the accounting system.
  • the journal database is used for learning the account item determination model, the apportionment determination model, and the apportionment rate determination model, which will be described later.
  • the journal database the date on which the transaction corresponding to the journal was made, the debit account, the debit sub-item, the debit amount, the credit account, the credit sub-item, and the credit amount are displayed. It is associated.
  • the journal database may further include voucher identification information (eg, invoice number, etc.) for identifying vouchers such as invoices.
  • the control unit 15 is, for example, a CPU (Central Processing Unit). By executing the program stored in the storage unit 14, the control unit 15 executes the data acquisition unit 151, the extraction unit 152, the account item determination unit 153, the apportionment rate determination unit 154, the journal data creation unit 155, the registration unit 156, and the control unit 15. And functions as a learning unit 157.
  • a CPU Central Processing Unit
  • the data acquisition unit 151 acquires the invoice data generated by the reading device 2 reading the invoice as a voucher.
  • the data acquisition unit 151 may directly acquire the invoice data from the reading device 2, or may acquire the invoice data from a terminal communicably connected to the data processing device 1.
  • the extraction unit 152 extracts text information from the voucher data acquired by the data acquisition unit 151.
  • the extraction unit 152 extracts the character string included in the invoice indicated by the invoice data, for example, by executing the OCR process.
  • the extraction unit 152 includes date information indicating the issue date of the invoice, a product name or service name, and a transaction amount corresponding to the product name or service name.
  • extract extract.
  • the extraction unit 152 extracts a plurality of product names or service names and transaction amounts included in the invoice indicated by the invoice data line by line, thereby extracting the product name or service name and the product name or service name. Extract the transaction amount corresponding to.
  • the account item determination unit 153 determines an account item corresponding to at least a part of the text information extracted from the invoice data by the extraction unit 152.
  • the account determination unit 153 determines an account using an account determination model that outputs an account.
  • the account item determination model is a model that outputs a debit account item and a credit account item when a part of the text information extracted by the extraction unit 152 is input.
  • the account item determination model is generated by learning in advance using the first teacher data in which the input information to the model and the output information corresponding to the input information are set.
  • the input information included in the first teacher data is, for example, information obtained by combining date information extracted from invoice data acquired in the past, a product or service name, and a transaction amount corresponding to the product or service name. Is.
  • the output information is a debit account and a credit account corresponding to the input information.
  • the generated account determination model is stored in the storage unit 14.
  • the account item determination unit 153 selects one product name or service name from a plurality of product names or service names extracted by the extraction unit 152, and specifies the transaction amount corresponding to the selected product name or service name.
  • the account item determination unit 153 inputs the combination of the date information indicating the date of the invoice, the selected product name or service name, and the specified transaction amount into the account item determination model as input information.
  • the account determination unit 153 determines the debit account and the credit account by acquiring the debit account and the credit account output from the account determination model.
  • the account item determination unit 153 sequentially selects each of the plurality of product names or service names extracted by the extraction unit 152, and determines the debit account item and the credit account item using the account item determination model.
  • the account determination unit 153 uses the account rule information. Accounts may be determined based on. Then, the account item determination unit 153 may determine an account item by using the account item determination model when it does not correspond to the preset account item rule information.
  • the storage unit 14 stores at least a part of the text information extracted from the invoice data and the account rule information associated with the debit account and the credit account. At least a portion of the textual information is, for example, a combination of customer information indicating the business partner corresponding to the invoice, date information indicating the date of the invoice, and goods or services contained in the invoice.
  • the account item determination unit 153 stores the customer information corresponding to the invoice data, the date information of the invoice extracted by the extraction unit 152, and the selected product name or service name in association with each other in the storage unit 14. It is determined whether or not it is stored in the account rule information. When the account determination unit 153 determines that it is stored in the account rule information, the debit account and the credit account associated with the account information, date information, product name or service name are set to the product. Determine the debit and credit accounts that correspond to the name or service name. By doing so, the account item determination unit 153 can accurately identify the account item for the invoice received from the business partner who has made a transaction in the past.
  • the apportionment rate determination unit 154 determines the apportionment rate for each of one or more departments corresponding to at least a part of the text information extracted by the extraction unit 152.
  • the apportionment rate determination unit 154 is based on the past text information and the journal data for which the apportionment rate of the amount to each of one or more departments is specified, which was created in the past in response to the past text information. Determine the apportionment rate for each of one or more departments of the amount corresponding to at least a part of.
  • the apportionment rate determination unit 154 extracts based on the result of learning from the teacher data including the past text information and at least a part of the journal data acquired in the past corresponding to the past text information.
  • the proportion of the amount of money corresponding to at least a part of the text information extracted by the department 152 to one or more departments is determined.
  • the past text information is at least a part of the information extracted from the invoice data of the invoice acquired in the past by the data acquisition unit 151.
  • the journal data is journal data in which the proportion of the amount of money to each of one or more departments is specified.
  • the apportionment rate determination unit 154 is based on the result of learning from the second teacher data including the past text information and the information indicating whether or not the past text information is apportioned to a plurality of departments. Determine whether to apportion the text information to multiple departments for at least a part of. Then, when the apportionment rate determination unit 154 determines that the text information is apportioned to a plurality of departments, the apportionment rate determination unit 154 includes the past text information and at least a part of the journal data created in the past corresponding to the past text information. Based on the result of learning from the third teacher data, the apportionment rate of the text information to each of the plurality of departments is determined.
  • the apportionment rate determination unit 154 has an apportionment determination model that determines whether or not to apportion each of a plurality of departments when at least a part of the text information extracted by the extraction unit 152 is input, and an extraction unit.
  • the apportionment rate is determined by using the apportionment rate determination model that outputs the apportionment rate corresponding to each of the plurality of departments.
  • the apportionment determination model is generated by learning in advance from the second teacher data in which the input information to the model and the output information corresponding to the input information are set.
  • the input information included in the second teacher data is, for example, past text information extracted from invoice data acquired in the past.
  • the output information is determination information indicating whether or not to apportion the input information to a plurality of departments.
  • the generated apportionment determination model is stored in the storage unit 14.
  • the apportionment rate determination model is generated by learning in advance from the third teacher data, which is a set of the input information to the model and the output information corresponding to the input information.
  • the input information included in the third teacher data is, for example, past text information.
  • the output information is a proportional division rate corresponding to each of the plurality of departments corresponding to the input information.
  • the generated apportionment rate determination model is stored in the storage unit 14.
  • the past text information included in the teacher data used for learning the apportionment rate determination model corresponds to the product name or service name extracted from the invoice data of the invoice acquired in the past and the product name or service name. It contains the transaction amount to be processed and date information indicating the date of the invoice.
  • the apportionment rate determination unit 154 selects one product name or service name from a plurality of product names or service names extracted by the extraction unit 152, and specifies the transaction amount corresponding to the selected product name or service name.
  • the apportionment rate determination unit 154 inputs the date information indicating the date of the invoice, the selected product name or service name, and the specified transaction amount into the apportionment determination model stored in the storage unit 14, and the apportionment determination unit Based on the determination result output from the model, it is determined whether or not to perform proportional division.
  • the apportionment rate determination unit 154 determines that the apportionment is to be performed, the apportionment rate storing the date information indicating the date of the invoice, the selected product name or service name, and the specified transaction amount in the storage unit 14. Enter in the decision model. Then, the apportionment rate determination unit 154 obtains the apportionment rate corresponding to each of the plurality of departments output from the apportionment rate determination model, so that the selected product name or service name and the product name or service name can be obtained. Determine the apportionment rate for each of the corresponding transaction amounts and one or more departments.
  • the apportionment rate determination unit 154 is the text information extracted by the extraction unit 152 based on the result of learning from the teacher data including the past text information, the information about the business partner corresponding to the past text information, and the journal data. The apportionment rate to at least a part and one or more departments corresponding to the information about the business partner corresponding to the text information may be determined.
  • the apportionment determination model and the apportionment rate determination model are generated by learning the past text information and the information about the business partner corresponding to the past text information as input information.
  • the apportionment rate determination unit 154 inputs date information indicating the date of the invoice, the selected product name or service name, the specified transaction amount, and information on the business partner corresponding to the invoice into the apportionment determination model. Acquire the judgment result.
  • the apportionment rate determination unit 154 determines that the specified transaction amount is apportioned to a plurality of departments based on the determination result, the date information indicating the date of the invoice, the selected product name or service name, and the specified transaction amount are determined.
  • the apportionment rate determination model determines that the specified transaction amount is apportioned to a plurality of departments based on the determination result.
  • the apportionment rate determination unit 154 is based on the result of learning from the past text information, the information regarding the input person of the journal data corresponding to the past text information, and the teacher data including the journal data, and at least one of the text information.
  • the apportionment rate to each of one or more departments corresponding to the department and the person who inputs the journal data corresponding to the text information may be determined.
  • Information about the person who entered the journal data corresponding to the past text information includes, for example, user identification information for identifying the person, a department code for identifying the department to which the person belongs, and a project in charge of the person. Project code for identification.
  • the apportionment determination model and the apportionment rate determination model are generated by learning past text information and information about an input person of journal data corresponding to the past text information as input information.
  • the apportionment rate determination unit 154 inputs the date information indicating the date of the invoice, the selected product name or service name, the specified transaction amount, and the user ID of the input person who inputs the text information into the apportionment determination model. And get the judgment result.
  • the apportionment rate determination unit 154 determines that the apportionment rate is to be apportioned to a plurality of departments based on the determination result, the date information indicating the date of the invoice, the selected product name or service name, the specified transaction amount, and the data processing device 1
  • One or more departments by inputting the user ID for identifying the user who is operating the Determine the apportionment rate for each.
  • the apportionment rate determination unit 154 can determine the apportionment rate to a plurality of departments according to the relationship between the journal data input person, the department to which the journal data belongs, the project to which the journal data belongs, and the text information.
  • the apportionment rate determination unit 154 corresponds to the apportionment rate rule information.
  • the apportionment rate may be determined based on the apportionment rate rule information, and when the apportionment rate rule information is not supported, the apportionment rate may be determined using the apportionment determination model and the apportionment rate determination model.
  • the storage unit 14 stores at least a part of the text information extracted from the invoice data and the apportionment rate rule information in which the apportionment rate to each of one or more departments is associated with each other.
  • At least a portion of the textual information is, for example, a combination of customer information indicating the business partner corresponding to the invoice, date information indicating the date of the invoice, and goods or services contained in the invoice.
  • the apportionment rate determination unit 154 stores the customer information corresponding to the invoice data, the date information of the invoice extracted by the extraction unit 152, and the selected product name or service name in association with each other in the storage unit 14. By determining whether or not the information is stored in the apportionment rate rule information, it is determined whether or not these information correspond to the apportionment rate determination rule.
  • the apportionment rate determination unit 154 when the customer information, the date information, and the selected product name or service name correspond to the apportionment rate determination rule, each of one or more departments based on the apportionment rate rule information. Determine the apportionment rate to.
  • the apportionment rate determination unit 154 determines the apportionment rate to the customer information corresponding to the invoice data, the date information, and the apportionment rate to one or more departments associated with the selected product name or service name. , Determine the proportion to one or more departments corresponding to the product name or service name. By doing so, the apportionment rate determination unit 154 can accurately specify the apportionment rate for the invoice received from the business partner who has made a transaction in the past.
  • the journal data creation unit 155 outputs the account item determined by the account item determination unit 153 and the apportionment rate determined by the apportionment rate determination unit 154. For example, the journal data creation unit 155 prorates the date information extracted by the extraction unit 152 and the account items determined by the account item determination unit 153 for each of the one or more goods or services extracted by the extraction unit 152. Journal data including the apportionment rate determined by the rate determination unit 154 and the department name of the apportionment destination is created.
  • the journal data creation unit 155 outputs a registration screen for accepting registration of the created journal data to the accounting system to the display unit 13.
  • FIG. 5 is a diagram showing an example of a registration screen output by the journal data creation unit 155.
  • the journal data shown in FIG. 5 is the journal data generated based on the invoice corresponding to FIG.
  • the registration unit 156 registers the journal data displayed on the registration screen in the accounting system.
  • the registration unit 156 may accept the correction of the journal data displayed on the registration screen from the user.
  • the registration unit 156 registers the journal data shown on the registration screen in the accounting system 3 and stores the journal data in the journal database in response to the pressing of the registration button on the registration screen.
  • the learning unit 157 corresponds to the apportionment rate output by the journal data creation unit 155, and at least a part of the journal data registered in the accounting system 3 by the registration unit 156 and at least one of the past text information corresponding to the journal data.
  • the account item determination model, the apportionment judgment model, and the apportionment rate determination model are learned from the teacher data including the department.
  • the learning unit 157 learns the account item determination model, the apportionment determination model, and the apportionment rate determination model using the newly stored information as teacher data in response to the information stored in the journal entry database by the registration unit 156. conduct. By doing so, in the data processing device 1, the more the journal data is registered in the accounting system 3, the more the model can be learned. Therefore, the account output from the model is apportioned or not. It is possible to improve the accuracy of the determination result and the proportional division rate.
  • FIG. 6 is a flowchart showing an example of the processing flow in the data processing apparatus 1.
  • the data acquisition unit 151 acquires the invoice data generated by the reading device 2 reading the invoice (S1).
  • the extraction unit 152 extracts text information from the invoice data acquired by the data acquisition unit 151 (S2).
  • the account item determination unit 153 selects a product name or service name that has never been selected from a plurality of products or services included in the text information extracted by the extraction unit 152 (S3). Further, the account item determination unit 153 specifies the transaction amount corresponding to the selected product name or service name from the plurality of transaction amounts included in the text information extracted by the extraction unit 152 (S4).
  • the account determination unit 153 inputs the date information of the invoice, the selected product name or service name, and the specified transaction amount into the account determination model, and the account output from the account determination model.
  • the account item is determined by acquiring (S5).
  • the apportionment rate determination unit 154 determines the apportionment rate corresponding to the date information of the invoice, the selected product name or service name, and the specified transaction amount (S6). Specifically, the apportionment rate determination unit 154 inputs the date information of the invoice, the selected product name or service name, and the specified transaction amount into the apportionment determination model, and the determination result output from the apportionment determination model. Determines whether or not to perform proportional division.
  • the apportionment rate determination unit 154 determines that the apportionment is to be performed, the date information of the invoice, the selected product name or service name, and the specified transaction amount are input to the apportionment rate determination model and output from the apportionment rate determination model. By acquiring the apportionment rate for each of the plurality of departments, the apportionment rate for each of the plurality of departments is determined.
  • control unit 15 determines whether or not all of the plurality of products or services included in the text information extracted by the extraction unit 152 have been selected (S7).
  • the process is transferred to S8, and when it is determined that all the plurality of products or services have not been selected, the control unit 15 transfers the process to S3.
  • the journal data creation unit 155 includes the date information extracted by the extraction unit 152 and the account items determined by the account item determination unit 153, corresponding to each of the one or more products or services extracted by the extraction unit 152. , Creates journal data including the apportionment rate determined by the apportionment rate determination unit 154 and the department name of the apportionment destination, and outputs a registration screen for accepting registration of the journal data to the accounting system to the display unit 13 (S8). ..
  • the registration unit 156 appropriately accepts corrections of the journal data displayed on the registration screen from the user, and then registers the journal data displayed on the registration screen in the accounting system (S9).
  • the learning unit 157 determines the account item based on the teacher data including at least a part of the journal data registered in the accounting system 3 by the registration unit 156 and at least a part of the past text information corresponding to the journal data. Further learning of the model, the apportionment determination model, and the apportionment rate determination model is performed (S10).
  • the data processing device 1 has created at least a part of the past text information extracted from the invoice data of the invoice as a voucher acquired in the past and the past text information corresponding to the past text information. Based on the journal data for which the apportionment rate of the amount to each of one or more departments is specified, the apportionment of the amount corresponding to at least a part of the text information extracted by the extraction unit 152 to each of one or more departments. Determine the rate and output the determined apportionment rate. By doing so, the data processing device 1 can create journal data corresponding to the apportionment to a plurality of departments for the new invoice data.
  • the apportionment rate determination unit 154 determines the apportionment rate for each of one or more departments using the apportionment determination model and the apportionment rate determination model, but the present invention is not limited to this.
  • the apportionment rate determination unit 154 uses an apportionment rate determination model that outputs the apportionment rate to one or more departments in response to the input of the text information extracted by the extraction unit 152, and apportionments to each of the one or more departments. The rate may be determined.
  • all or a part of the device can be functionally or physically distributed / integrated in any unit.
  • new embodiments resulting from any combination of the plurality of embodiments are also included in the embodiments of the present invention. The effect of the new embodiment produced by the combination has the effect of the original embodiment together.

Landscapes

  • Business, Economics & Management (AREA)
  • Engineering & Computer Science (AREA)
  • Accounting & Taxation (AREA)
  • Development Economics (AREA)
  • Economics (AREA)
  • Finance (AREA)
  • Marketing (AREA)
  • Strategic Management (AREA)
  • Technology Law (AREA)
  • Physics & Mathematics (AREA)
  • General Business, Economics & Management (AREA)
  • General Physics & Mathematics (AREA)
  • Theoretical Computer Science (AREA)
  • Financial Or Insurance-Related Operations Such As Payment And Settlement (AREA)
  • Management, Administration, Business Operations System, And Electronic Commerce (AREA)

Abstract

L'invention concerne un dispositif de traitement de données (1) qui comprend : une unité d'acquisition de données (151) qui acquiert des données de coupon ; une unité d'extraction (152) qui extrait des informations texte à partir des données de coupon ; une unité de détermination de proportion (154) qui détermine la proportion de la somme d'argent correspondant à au moins une partie des informations texte extraites par l'unité d'extraction (152) à chacun d'un ou de plusieurs départements, sur la base d'au moins une partie des informations texte antérieures extraites des données de coupon sur des coupons émis dans le passé, et des données de journal qui ont été créées dans le passé en réponse aux informations texte antérieures et qui spécifie la proportion de la somme d'argent à chacun du ou des départements ; et une unité de création de données de journal (155) qui délivre la proportion déterminée.
PCT/JP2020/034103 2020-09-09 2020-09-09 Dispositif de traitement de données, procédé de traitement de données et programme WO2022054165A1 (fr)

Priority Applications (3)

Application Number Priority Date Filing Date Title
JP2020547247A JP6810306B1 (ja) 2020-09-09 2020-09-09 データ処理装置、データ処理方法及びプログラム
PCT/JP2020/034103 WO2022054165A1 (fr) 2020-09-09 2020-09-09 Dispositif de traitement de données, procédé de traitement de données et programme
JP2020205042A JP2022045868A (ja) 2020-09-09 2020-12-10 データ処理装置、データ処理方法及びプログラム

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/JP2020/034103 WO2022054165A1 (fr) 2020-09-09 2020-09-09 Dispositif de traitement de données, procédé de traitement de données et programme

Publications (1)

Publication Number Publication Date
WO2022054165A1 true WO2022054165A1 (fr) 2022-03-17

Family

ID=73992972

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/JP2020/034103 WO2022054165A1 (fr) 2020-09-09 2020-09-09 Dispositif de traitement de données, procédé de traitement de données et programme

Country Status (2)

Country Link
JP (2) JP6810306B1 (fr)
WO (1) WO2022054165A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP7233794B1 (ja) * 2022-10-21 2023-03-07 ファーストアカウンティング株式会社 情報処理装置、情報処理方法及びプログラム

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006195570A (ja) * 2005-01-11 2006-07-27 Hitachi Information Systems Ltd 会計伝票の按分処理システム、同按分処理方法、同按分プログラム
JP2016181254A (ja) * 2015-03-23 2016-10-13 株式会社オービック 自動仕訳処理装置、自動仕訳処理方法、および自動仕訳処理プログラム
WO2018179411A1 (fr) * 2017-03-31 2018-10-04 ファーストアカウンティング株式会社 Système et procédé de comptabilité
JP2019174949A (ja) * 2018-03-27 2019-10-10 株式会社オービック 共通費管理装置、共通費管理方法、及び共通費管理プログラム
JP2020057186A (ja) * 2018-10-02 2020-04-09 フードゲート株式会社 会計ソフトウェア及びシステム
JP6712738B1 (ja) * 2019-10-31 2020-06-24 株式会社日本デジタル研究所 証憑判定装置、会計処理装置、証憑判定プログラム、証憑判定システム及び証憑判定方法
JP6732325B1 (ja) * 2020-04-21 2020-07-29 ファーストアカウンティング株式会社 会計処理システム、会計処理方法、会計処理プログラム

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2006195570A (ja) * 2005-01-11 2006-07-27 Hitachi Information Systems Ltd 会計伝票の按分処理システム、同按分処理方法、同按分プログラム
JP2016181254A (ja) * 2015-03-23 2016-10-13 株式会社オービック 自動仕訳処理装置、自動仕訳処理方法、および自動仕訳処理プログラム
WO2018179411A1 (fr) * 2017-03-31 2018-10-04 ファーストアカウンティング株式会社 Système et procédé de comptabilité
JP2019174949A (ja) * 2018-03-27 2019-10-10 株式会社オービック 共通費管理装置、共通費管理方法、及び共通費管理プログラム
JP2020057186A (ja) * 2018-10-02 2020-04-09 フードゲート株式会社 会計ソフトウェア及びシステム
JP6712738B1 (ja) * 2019-10-31 2020-06-24 株式会社日本デジタル研究所 証憑判定装置、会計処理装置、証憑判定プログラム、証憑判定システム及び証憑判定方法
JP6732325B1 (ja) * 2020-04-21 2020-07-29 ファーストアカウンティング株式会社 会計処理システム、会計処理方法、会計処理プログラム

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP7233794B1 (ja) * 2022-10-21 2023-03-07 ファーストアカウンティング株式会社 情報処理装置、情報処理方法及びプログラム
WO2024084692A1 (fr) * 2022-10-21 2024-04-25 ファーストアカウンティング株式会社 Dispositif de traitement d'informations, procédé de traitement d'informations et programme

Also Published As

Publication number Publication date
JP2022045868A (ja) 2022-03-22
JP6810306B1 (ja) 2021-01-06
JPWO2022054165A1 (fr) 2022-03-17

Similar Documents

Publication Publication Date Title
US7416131B2 (en) Electronic transaction processing server with automated transaction evaluation
JP5204208B2 (ja) レシートデータ照合支援装置およびレシートデータ照合支援プログラム
JP6635563B1 (ja) 仕訳要素解析装置、会計処理システム、仕訳要素解析方法、仕訳要素解析プログラム
JPWO2019008766A1 (ja) 証憑処理システムおよび証憑処理プログラム
WO2020179055A1 (fr) Dispositif d'analyse de bon, système de comptabilité, procédé d'analyse de bon et programme d'analyse de bon
CN116051092A (zh) 一种跨系统自动对账方法及装置
WO2022054165A1 (fr) Dispositif de traitement de données, procédé de traitement de données et programme
JP6464440B1 (ja) 会計処理装置、会計処理システム、会計処理方法及びプログラム
JP6732325B1 (ja) 会計処理システム、会計処理方法、会計処理プログラム
CN109544134B (zh) 便捷支付服务方法和系统
JP6810303B1 (ja) データ処理装置、データ処理方法及びデータ処理プログラム
JP6848134B1 (ja) データ処理装置、データ処理方法及びプログラム
WO2002054307A1 (fr) Systeme de gestion de boutique electronique
JP6944603B1 (ja) データ処理装置、データ処理方法及びプログラム
JP2001236354A (ja) 自動仕訳処理機能を有する会計システム
JP6844076B1 (ja) データ処理装置、データ処理方法及びプログラム
WO2022049689A1 (fr) Dispositif de traitement de données, procédé de traitement de données et programme
JP6967174B1 (ja) データ処理装置、データ処理方法及びプログラム
WO2022176100A1 (fr) Dispositif de traitement de données, procédé de traitement de données et programme
WO2020255361A1 (fr) Système de traitement de comptabilité, procédé de traitement de comptabilité et programme de traitement de comptabilité
JP7021819B1 (ja) データ処理装置、データ処理方法及びプログラム
JP7063963B2 (ja) 支払支援システム、支払支援方法及び支払支援プログラム
WO2018221146A1 (fr) Programme servant à deviner un titre de compte, dispositif servant à deviner un titre de compte et procédé servant à deviner un titre de compte
WO2020050391A1 (fr) Système et procédé d'affichage de journalisation
JP3066021U (ja) コンピュータによる事業業績の算出装置

Legal Events

Date Code Title Description
ENP Entry into the national phase

Ref document number: 2020547247

Country of ref document: JP

Kind code of ref document: A

121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20953231

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 20953231

Country of ref document: EP

Kind code of ref document: A1