JP2020030517A - Accounting processor, accounting method, accounting program - Google Patents

Abstract

To solve a problem that it is necessary to register in advance abstract terms and the like in a conventional accounting processor, an accounting method, and an accounting program.SOLUTION: An accounting processor having an abstract determination support function for determining corresponding abstract information from an entered account title, includes a storage unit 30 configured to store a keyword dictionary for registering, as keywords, one or more abstract terms constituting the abstract information, and abstract terms associated with the entered account title, and abstract patterns in which the account title and the abstract information are associated, and a control unit 10 configured to acquire a corresponding abstract pattern with an account title input for debit and an account title input for credit as keys. The accounting processor displays abstract terms broken down for respective keywords by referring to the keyword dictionary from the matched abstract pattern as abstract term candidates in descending order of usage frequency. Therefore, the abstract information can be created even if the abstract information is not registered in advance.SELECTED DRAWING: Figure 9

Description

  The present invention relates to creating summary information from account items, and the like.

  In a conventional accounting processor, there is a type in which past journals are registered in a dictionary as standard journals and used as a journal dictionary for standard transactions that occur every month, and journals can be easily created simply by inputting an account item. (For example, see Patent Document 1). In addition, there is a method in which an account is input simply by selecting a description character string by using a description dictionary in which a description character string (phrase) and a related account are registered, and a journal is automatically created easily ( For example, see Patent Document 2).

JP-A-06-052196 JP 2003-331209 A

However, in Patent Document 1, when a conventional journal dictionary is used, the journal dictionary can be used as it is for standard transactions in which account items and summary information are the same except for the amount of electricity bills generated monthly, etc. If they were different, there was a problem that they had to enter them again. There is also a problem that frequently occurring journals and summary information of journals frequently used by a person in charge need to be registered in a journal dictionary in advance.
In Patent Document 2, a journal can be easily created by selecting summary information and a partner subject after selecting a subject, but there is a problem that the summary information needs to be registered in a summary dictionary in advance. . Also, the transaction contents are registered in the summary dictionary as summary information, but the registered transaction contents are standard transaction contents, and the transaction contents (eg, eating and drinking etc.) are the same and account items (eg, entertainment expenses and meetings). Cost, etc.), there is a problem that the transaction status is unclear and the transaction contents are not sufficiently checked.

The first invention refers to an input means for accepting an input of an account, and an abstract description pattern table for registering an abstract pattern, which is a combination of one or more abstract words constituting the abstract information, in association with the input account. Extracting means for extracting a summary pattern matching the account input to the debit and the account input to the credit as a key; a means for creating a summary pattern list from the extracted summary pattern; and the summary pattern list. Means for registering the priority information of the summary pattern, first means for displaying the summary pattern obtained from the summary pattern list as summary text candidates in descending order of priority, and the displayed summary text candidate A second means for confirming the summary sentence candidate selected from the above as the summary sentence. It is a device.
The second invention is a means for receiving an input of an account,
An account pattern entered as a debit and an account entered in a credit by referring to an account abstract pattern table in which the entered account is registered by associating an entered pattern with an entered pattern, which is a combination of one or more abstract words constituting the entered information. Means for extracting a matching abstract pattern using the as a key,
Means for creating a summary pattern list from the extracted summary pattern,
Means having a function of registering the priority pattern list of the summary pattern list,
Refer to the keyword dictionary registered as a keyword in which the category indicating the transaction content is associated with the input account related to the description associated with the account, and decompose for each keyword from the description pattern list, and the description of each description pattern and the number of description phrases Means for obtaining
First means for displaying the acquired summary phrase as a summary phrase candidate in order of priority,
A second means for determining the summary word candidate selected from the displayed summary word candidates as a summary word,
An accounting processing device comprising: means for repeating the processing including the first means and the second means by the number of the key words of the key pattern having the highest priority based on the priority information of the key pattern. It is.
A third invention is an accounting processor according to the first invention or the second invention,
The extraction means refers to the subject summary pattern table and extracts a matching summary pattern using at least one of a taxation classification code, a tax rate code, and a department name associated with the summary pattern as a key. It is an accounting processor.
A fourth invention is the accounting processing device according to the first invention to the third invention, wherein the input means further receives an input of the amount of money, and the extracting means refers to the subject summary pattern table to obtain the summary. An accounting processing apparatus characterized by extracting a summary pattern that matches with an amount associated with the pattern as a key.
A fifth invention is the accounting processing device according to the first invention to the third invention, wherein the input means further accepts the input of the amount of money, and sets the account subject to the ratio of the amount of money as the target account. Stipulates a ratio that is a ratio of the input amount and the total amount of the target account, and the extracting means refers to the subject summary pattern table and further matches the summary pattern with the ratio associated with the summary pattern as a key. Is extracted.
A sixth invention is the accounting processing device according to the first invention to the third invention, further comprising means for registering journal data including at least an account item and an amount in a journal data DB, and the input means further comprises: An input of the amount is received, and an amount is generated based on a random number according to a predetermined probability distribution calculated based on the amount of all journal data included in the journal data DB, and the extracting unit refers to the subject summary pattern table. And extracting a matching summary pattern by further using the calculated amount associated with the summary pattern as a key.
The seventh invention refers to the subject summary pattern table including evaluation information for each transaction configuration parameter associated with an account for a plurality of transactions belonging to an arbitrary transaction category, and evaluates each summary pattern for each transaction configuration parameter. Means for extracting transaction configuration information indicating the affiliation of each of the summary patterns by classifying (clustering) each of the summary patterns having similar information structures into a predetermined word group having the same transaction configuration; and Based on the configuration information, by selecting the summary pattern from each transaction configuration, a means for acquiring the summary pattern that is an optimal combination of the account item, tax classification code and tax rate code for the transaction, Accounting device.
According to an eighth aspect of the present invention, a means for accepting an input of an account, a transaction summary and a transaction summary classified by transaction category and an account summary table registered in association with the entered account are input to the debit. Means for obtaining a debit account type corresponding to the debit account using the account as a key, and a credit account corresponding to the credit account using the account entered as a key with reference to the item description table. Means for acquiring a type, means for comparing a debit summary type and the credit summary type, means for extracting a summary type matching the debit summary type and the credit summary type, and decomposing the transaction content and transaction status for each keyword The abstract type extracted as described above with reference to the abstract type table for registering the abstract type and the abstract type, which is a combination of the abstract items summarized for each category, and registering the abstract type A means for acquiring the number of description items and the description item configuration as a key, and a plurality of transactions belonging to any transaction category of the keyword dictionary to be registered as a keyword in which a category indicating the transaction content is associated with a description phrase related to the input account With reference to the evaluation information for each transaction configuration parameter associated with the account item for, the keywords having a similar configuration of the evaluation information for each transaction configuration parameter of each keyword are classified into predetermined word groups having the same transaction configuration ( Means for extracting transaction configuration information indicating the affiliation of each of the keywords by performing clustering, and selecting keywords from each transaction configuration based on the transaction configuration information, thereby providing an optimal item for each item of the summary item configuration. Means for acquiring a keyword as a keyword, and giving priority to the acquired keyword as a keyword candidate First means for displaying in the descending order of the ranks, second means for determining a summary word candidate selected from the displayed summary word candidates as a summary word, and processing including the first means and the second means. Means for repeating the same number of times as the number of the summary items.
A ninth invention is the accounting processing device according to the first invention to the eighth invention, wherein a means for converting primitive vouchers indicating transaction contents into image data, and a means for extracting text information from the image data Referring to the keyword dictionary, decomposing text information as an input keyword for each keyword, associating the determined summary phrase with the input keyword, and automatically creating summary information from the determined summary phrase, An accounting processing device comprising: means for associating the summary information with the image data.
A tenth invention is the accounting device according to the first invention to the ninth invention, wherein the account item, the tax classification code, the tax rate are obtained from summary information created from the account item and the confirmed summary phrase. An accounting processing apparatus comprising: means for creating journal data including a code and the summary information; and means for registering the journal data in a journal data DB.
An eleventh invention is the accounting processing device according to the tenth invention, wherein the journal data including the account item and the summary information is created, and the journal data is registered in a journal data DB. First means for adding 1 to the number of times of selection of the corresponding summary phrase or automatically registering the corresponding summary phrase as a new keyword, depending on the presence or absence of the summary phrase used in the summary information in the keyword dictionary; and Means for feeding back to the keyword dictionary by means of (1).
A twelfth invention is the accounting device according to any of the tenth inventions, wherein the journal data including the account item and the summary information is created, and the journal data is registered in a journal data DB. At this time, depending on whether or not the summary information is registered in the subject summary pattern table, 1 is added to the number of times of selection of the summary pattern that matches the corresponding summary information or the corresponding summary information is automatically registered as a new summary pattern. And a means for feeding back to the subject summary pattern table by the first means.
A thirteenth invention is the accounting processing device according to any of the tenth inventions, wherein the means for receiving an input of a company that performs accounting processing and a company DB in which company information to be accounted for are registered. Means for obtaining the company code of the company entered as a key, means for obtaining matching journal data from the journal data DB using the obtained company code as a key, and description of the journal data obtained with reference to the keyword dictionary. An accounting processing apparatus comprising: means for extracting a summary phrase included in information; and means for creating a keyword dictionary for each company based on the extracted summary phrase.
A fourteenth invention is the accounting device according to any of the tenth inventions, wherein the means for receiving an input of a company that performs the accounting process and a company DB in which information of the company to be accounted for are registered. Means for acquiring the company code of the entered company, means for acquiring matching journal data from the journal data DB using the acquired company code as a key, and journal data acquired with reference to the subject summary pattern table. And a means for creating a summary pattern table for each company based on the extracted summary patterns.
A fifteenth invention is the accounting processing device according to any of the tenth inventions, wherein the means for acquiring a target date, which is the date of occurrence of the transaction to be accounted, includes: Means for determining a reference period for limiting the date of occurrence of the past transaction to be referenced, based on the reference setting in which the occurrence time is set and the target date and time, and from the journal data to the reference period. The accounting processing apparatus according to claim 1, further comprising: means for extracting corresponding journal data; and means for creating a keyword dictionary for each company based on the extracted journal data.
A sixteenth invention is the accounting processing device according to any of the tenth inventions, wherein the means for acquiring a target date that is the date of occurrence of the transaction to be accounted for, includes: Means for determining a reference period for limiting the date of occurrence of the past transaction to be referenced, based on the reference setting in which the occurrence time is set and the target date and time, and from the journal data to the reference period. An accounting processor comprising: means for extracting applicable journal data; and means for creating a summary pattern table for each company based on the extracted journal data.
A seventeenth invention is a program for causing a computer to function as the accounting device according to any one of the first to fourteenth inventions.

According to the present invention, it is not necessary for a person in charge to pre-register journals and summary information frequently used in a dictionary in advance, and by inputting an account item, an optimal summary word candidate or summary text (combination of summary words) can be obtained. Is displayed and selected, the journal can be efficiently created.
Further, by adding a department name, an amount, a tax classification code and a tax rate code (consumption tax reduction tax rate or standard tax rate) to the account item, it is possible to extract more accurate summary word candidates and summary text candidates.

In addition, by adding the tax classification code and tax rate code to the description combination, the tax classification code is referred from the description structure used, and if the tax classification code is taxable, the tax rate code automatically determines whether the tax rate code is reduced or standard tax rate As a result, it is possible to easily create a journal in consideration of the consumption tax.
By selecting the extracted abstract sentence candidate or abstract phrase candidate, the consumption tax (10%, 8%, etc.) is set based on the taxation classification and tax rate code corresponding to the selected abstract sentence candidate or abstract phrase candidate. This eliminates the need to enter a consumption tax.
By simply specifying the account item, tax classification, and consumption tax rate (10% or 8%, etc.), clustering is used to extract summary word candidates or summary text candidates corresponding to the reduced tax rate or the standard tax rate. Can also.

  According to Patent Document 1, it is necessary to register frequently-occurring journal entries and summary information of journals frequently used by a person in charge in a journal dictionary in advance. Since the person in charge does not need to register, there is no need to bother to edit and manage the dictionary and the table, so that the burden on the person in charge can be reduced.

Further, in Patent Document 2, when the transaction contents (eg, eating and drinking etc.) are the same and the account items (eg, entertainment expenses, meeting expenses, etc.) are different, the transaction status is unknown and the transaction contents are not sufficiently checked. On the other hand, according to the present invention, it is possible to create the most appropriate summary information for each account by describing not only the transaction content but also the transaction status.

Further, summary information can be created based on a combination of summary items from a dictionary in which general transaction terms are collected for each account item (Example 1). In Example 1 described above, all combinations of the account items and the prepared summary must be registered. On the other hand, by associating the combination of the summary items with a summary pattern classified into a certain pattern to one account, It is only necessary to register the minimum required combination among the combinations with the created summary. In addition, transaction information such as minimum transaction items and transaction status necessary for specifying an account is summarized into a summary type, so that appropriate summary information is created when an account is selected.

In addition, by setting multiple combinations of accounts and related descriptions, the related debit summary types of the debit account and the related credit summary types of the credit account are compared, and by using the same summary type, The accuracy of the summary information to be created can be improved. Also, some terms (November and 50,000 yen) are excluded from summaries (November rent and monthly fee of 50,000 yen) used in routine processing depending on the items of the summary type (date and amount, etc.). Accordingly, the number of abstracts to be registered can be reduced, and the registration of abstracts can be made more efficient.

  Further, by inputting an account item and converting the summary information into a template, the input efficiency can be improved (Example 2). In Example 2, the order of the summary items is fixed in advance, and it is necessary to register each item in a dictionary or the like in advance. On the other hand, by setting the summary type related to the account item for each account item, The order and contents of the summary items can be freely set for each account item.

In addition, in terms of estimating the key words from the "loan subject", more accurate estimation is possible by taking into account parameters such as "department" and "amount" in addition to "loan subject". .
For example, even for the same loan subject, the contents of the summary to be input differ between a case where the amount is high and a case where the amount is low, so that a more accurate guess can be made.

  In addition, although the list is displayed as "summary words" as the guessed result, as a modified example, the guessed result is displayed as "summary sentence" such as "Trailer replacement payment settlement Taro Yamada". The description entry can be completed by the selection process. Therefore, the input operation can be further simplified.

  In addition, there is no problem if the summary of the journal is not described. However, the taxable business operator of the consumption tax needs to keep “books and invoices”. This “book” corresponds to the summary of the journal, and it is necessary to describe the summary that satisfies the requirements. Therefore, the input operation can be further simplified by grouping the abstract terms by the consumption tax description requirements and automatically generating a summary satisfying the consumption tax description requirements from the contents of the transaction.

  In addition, transaction configuration parameters such as elements (“category indicating transaction content, etc.”, “items indicating transaction status”, “loan”, “tax classification code”, and “tax rate code”) set in advance to the extracted word (keyword) ) Is clustered (= classified words) based on the evaluation value (key) of, and the most appropriate words are extracted from each element to form a complete summary that meets the legally required requirements. it can. The “word group” is a collection of several words, that is, “keywords” or “keywords” (keywords) or “keywords” that form key information (including natural texts) based on a predetermined key. ).

  In addition, by preparing a set (subject abstract pattern table) of a combination of the amount of the previous journal and the abstract (including all of the abstract phrase, the abstract sentence, and the abstract information), the data set of the abstract + the amount (the subject abstract) By referring to the “pattern table” and comparing the “amount” of the journal data with the “amount set by the user”, which is the “amount” of the subject summary pattern table, a high-precision narrowing down can be performed.

In addition, by preparing a set of the combination of the amount of the previous journal and the description (subject summary pattern table), refer to the data set of the description + amount (subject summary pattern table),
By comparing the “amount” of the journal data and the “ratio” of the subject summary pattern table with the ratio of the sales amount set by the user and determining the magnitude, it is possible to perform highly precise narrowing. As for the ratio of sales, after calculating the total amount of sales, the ratio of sales (the ratio between the amount of journals and the total amount of sales) is calculated for each journal data.

FIG. 1 is a diagram illustrating an overall configuration of an accounting system 100 according to an embodiment. FIG. 2 is a diagram illustrating functional blocks of the accounting apparatus 1 according to the embodiment. It is a figure showing the example of the company DB used for the processing by the accounting processor concerning this embodiment. It is a figure showing an example of journalizing data DB used for processing by the accounting processing device concerning this embodiment. It is a figure showing the example of the subject summary table used by the processing by the accounting processor concerning this embodiment. It is a figure showing the example of the summary type table used by the processing in the accounting processor concerning this embodiment. It is a figure showing the example of the subject summary pattern table used in the processing by the accounting processor concerning this embodiment. FIG. 5 is a diagram illustrating an example of a keyword dictionary used in processing in the accounting processing device according to the present embodiment. 5 is a flowchart illustrating processing (Example 1) in the accounting processing device according to the present embodiment. 9 is a flowchart illustrating processing (Example 2) in the accounting processing device according to the present embodiment. 9 is a flowchart illustrating processing (Example 3) in the accounting processing device according to the present embodiment.

  Hereinafter, embodiments for carrying out the present invention will be described with reference to the drawings. Note that components denoted by the same reference numerals in the embodiments perform the same operation, and thus the description thereof may not be repeated.

<Overall Configuration of Accounting Processing System 100>
FIG. 1 is a diagram illustrating an overall configuration of an accounting processing system 100 according to the present embodiment.
FIG. 2 is a diagram illustrating functional blocks of the accounting apparatus 1 according to the present embodiment.

  In the accounting processing system 100 shown in FIG. 1, a server 1a for mainly storing and calculating accounting data and a terminal 1b for performing data input and instructions for processing are connected via a network, and cooperate with the accounting processing. Is performed. In addition, a system in which the accounting processing device 1 of the accounting office requested by the advisor performs accounting processing by executing various business application programs (hereinafter, application programs are also referred to as “programs”). It is.

The accounting processing system 100 includes, for example, a server 1a and a plurality of terminals 1b. The server 1a performs a process based on the operation data received from the terminal 1b. The plurality of terminals 1b are, for example, business processing personnel (hereinafter referred to as “persons in charge” or accounting staff who work at accounting firms such as tax accountants and certified public accountants, teachers and veteran staffs). It is a terminal operated by an advisor (a company that has entered into an advisory contract with an accounting firm). Although described in the accounting office, a department that performs accounting and accounting in a company may be used.

In FIG. 1, the accounting processing system 100 is described as including the server 1a and the terminal 1b, but this is an example. For example, a system in which servers and terminals in an accounting office are connected via a network, an accounting system between an accounting office and an advisor, an accounting system between head office and sales offices, an accounting system between head office branches, and an accounting system between head offices and branches. It may be a processing system.

  The accounting processing device 1 is, for example, a device provided in an accounting office and performs various accounting processes, and corresponds to one device (single device) such as the server 1a and the terminal 1b. The accounting processing device 1 performs a plurality of business processes corresponding to various accounting processes. Further, the transaction apparatus 1 may be configured by, for example, one stand-alone (single unit) computer (PC). Further, the transaction apparatus 1 may be a workstation (WS) configured by a plurality of PCs. As described above, the device configuration may be processed as a single device, or may be realized as a configuration of a system in which the server device 1a and the terminal 1b are connected via a network.

  Further, the accounting processing device 1 may be located in an advisor company, not in an accounting office, in a company that provides services such as business consignment, or may be a cloud service. For example, the terminal 1b does not necessarily need to be provided in the accounting office, and includes a terminal of a staff who goes out or works at home, and a terminal of a staff of a subcontractor. Further, the transaction apparatus 1 may be a mobile terminal such as a mobile phone or a tablet, a digital camera or a scanner.

  Further, the accounting processing device 1 may be constituted by only a server device or a plurality of server devices. In addition to a server device of an accounting office, accounting files of (an employee of) a plurality of companies (employees). (IDC (Internet Data Center) server device that provides a service for keeping and managing the data).

Further, the transaction apparatus 1 may be a virtual machine or a cloud whose entity is virtualized.
Furthermore, when the headquarters of the company performs financial management for each department or each branch (employee), the accounting processing device 1 may be a server device in the company.
The accounting processing device 1 may be a device that exclusively performs the processing of the present invention, or a device that performs accounting processing has the function of the accounting processing device 1 as one of various functions. Is also good.

  Further, the accounting processing device 1 may be used, for example, as a device that is provided at an advisor and reads a voucher (primitive voucher) such as a receipt or a receipt of the advisor and generates a voucher image. The voucher (primitive voucher) has been delivered to the accounting firm by mail from an advisor or by a person in charge of the advisor. In the case where the accounting processing is performed between the head office and the branch, the accounting processing apparatus 1 may be located both in the head office, in the head office accounting department and in the branch office, in the sales office of each base, and in the branch office.

The embodiments described above can be realized by computer hardware and a computer program executed thereon. In the above-described program, in the transmission of transmitting information and the reception of receiving information, processing performed by hardware, for example, processing performed by a modem or an interface card in transmission (processing performed only by hardware) ) Is not included.

The computer that executes the program may be a single computer or a plurality of computers. That is, centralized processing or distributed processing may be performed.
Further, in each of the above embodiments, it goes without saying that two or more communication means (terminal information transmitting unit, terminal information receiving unit, etc.) existing in one device may be physically realized by one medium. . The accounting processing device 1 may be processed as a single unit, or the server device 1a using the accounting processing device 1 and the terminal 1b using the accounting processing device 1 may be realized as an accounting processing system 100 connected via a network. Good.

Further, in each of the above embodiments, each process (each function) may be realized by central processing by a single device (system), or may be realized by distributed processing by a plurality of devices. May be done.
The present invention is not limited to the above embodiments, and various modifications are possible, and it goes without saying that they are also included in the scope of the present invention. This is merely an example, and the technical scope of the present invention is not limited to this.

FIG. 2 is a block diagram of the accounting processing device 1 according to the present embodiment.
<Accounting device 1>
The accounting processing device 1 includes a storage unit 30 and a control unit 10.
As shown in FIG. 2, the transaction apparatus 1 includes a control unit 10, a storage unit 30, an input unit 45, a display unit 46, and a communication unit 49. According to the configuration of the transaction processing device 1 of FIG. 1, the server device 1a corresponds to the control unit 10, the storage unit 30, and the communication unit 49, and the terminal 1b includes the input unit 45 and the display unit 46. Equivalent to.

The control unit 10 executes programs in a plurality of business processes corresponding to various types of accounting processes, and performs data-related processes such as data updates and management.
The control unit 10 can be generally realized by an MPU, a memory, or the like. The processing procedure of the control unit 10 is usually realized by software, and the software is recorded on a recording medium such as a ROM. However, it may be realized by hardware (dedicated circuit).

The control unit 10 is a CPU (central processing unit) that controls the entire transaction apparatus 1. The control unit 10 executes various functions in cooperation with the above-described hardware by appropriately reading and executing an OS (operating system) or an application program stored in the storage unit 30.
Further, the control unit 10 includes a management unit (not shown) for performing data management such as data update, and a processing unit (not shown) for performing data processing such as data comparison.

The storage unit 30 can be generally realized by an MPU, a memory, or the like. The processing procedure of the storage unit 30 is generally realized by software, and the software is recorded on a recording medium such as a ROM. However, it may be realized by hardware (dedicated circuit).
The storage unit 30 is a storage area such as a hard disk or a semiconductor memory device for storing programs, data, and the like necessary for the control unit 10 to execute various processes.
The storage unit 30 includes a program storage unit (not shown), a business partner DB (not shown), a company DB 31, a journal data DB 32, a subject summary table 33, a summary type table 34, and a subject summary pattern table. 35 and a keyword dictionary 36.

  The program storage unit is a storage area for storing various programs. The program storage unit stores an application program for executing various functions such as performing an accounting process. The business partner DB is a database that stores information on business partners of the company in the company DB. The business partner DB is associated with a business partner ID which is identification information for identifying a business partner, a business type, a company ID indicating a business partner of any company, a business partner name, an address, a store name, a telephone number, a company logo, It stores data on business partners such as business clerks. The data of these business partners is used as counterparts for sales, purchases, accounts receivable, accounts payable, and the like.

  Although the various functions of the control unit 10 described above are executed by one program as the application program, the various functions of the control unit 10 may be executed as a plurality of programs subdivided for each function.

  The company DB 31 shown in FIG. 3 stores company information to be subjected to accounting processing using a company code as a key. The company DB 31 stores a company code, an organization code, a department code, a company name, an organization name, a department name, a type, a year, an address, an organization head, a division, a registration place, and a person in charge. Are stored in association with each other. In addition to the case where the accounting office uses the accounting processing apparatus 1 for a plurality of advisors, the company may also use a branch office (not shown), a head office branch office (not shown), a head office and a sales office at each base. It also corresponds to the case where it is used between devices (not shown).

In the company DB 31 shown in FIG. 3, the company code is identification information for identifying a consultant, the organization store code is the head office or branch office of the company, and the department code is identification information for identifying the department to which the company belongs. The type of business is the type of business of the company, such as manufacturing or retail. The company name is the name of the company (eg, ABC Industries, etc.), the organization name is the name of the company's base such as the head office, branch office, sales office, etc. (eg, ○ Island branch office, etc.), and the department name is the accounting department And the name of the department such as sales. The type is a type of business such as accounting, taxation, and accounting. The address is the address of the organization of the company. The head of the organization is the name of the head of the organization of the company such as a representative at the headquarters (for example, Oyama x male for ABC Industry). The category is a category such as a corporation or an individual. The registration location is a storage location of business data such as journal data for each company. The person in charge is a person in charge of operations such as accounting.

The company DB 31 may store, for example, a representative name, a company logo, a DB registration date, a business form, a commissioned business, and the like, in addition to the items described in FIG. The representative name may be used, for example, for linking the parent-child relationship of the company. The DB registration date corresponds to an advisory contract date or a branch establishment date. The business form is a corporate business, a private business, a mere individual, or the like. The responsibilities include accounting (monthly audits, settlement of accounts, etc.) and tax (corporate tax returns, blue returns, etc.).

The journal data DB 32 is a database that stores journal data using a journal ID for identifying the journal data as a key.
The journal data DB 32 stores journal data and a slip ID for identifying a slip image received by the slip image receiving unit 11 in association with a journal ID for identifying the journal data. The journal data stored in the journal data DB 32 can be updated by being input and edited using an editing screen.

  The journal data DB 32 shown in FIG. 4 includes a journal ID, a company code, an organization code, a department code, a date, a debit item (debit account item), a credit item (credit account item), and a tax classification code. , The tax rate code, the transaction category, the amount, the consumption tax amount, the summary, the slip ID, the slip classification, and the slip contents are stored in association with each other. Here, the date is the date when the journal data was generated, and is the same as the date included in the slip image. In the case of the consumption tax, it is the date of the tax purchase or the summary period. The tax classification code indicates whether the consumption tax is taxable, tax-exempt, tax-exempt, or exempt. The code related to taxation may be specified in accordance with the transaction content of the consumption tax.

The tax rate code indicates the tax rate of the consumption tax. Even though the consumption tax is the same account, the tax rate (standard tax rate or reduced tax rate) differs depending on the transaction content. The reduced tax rate is applied to periodicals and food products, but it is determined separately from the standard tax rate for eat-in and the reduced tax rate for takeout, so it is automatically determined whether the reduced tax rate or the standard tax rate based on the tax rate code. Calculate the consumption tax for each journal. For example, a consumption tax is calculated with a tax rate of "8" for a reduced tax rate of 8% and "10" for a standard tax rate of 10%. .

Further, the amount is the amount of consideration paid in the transaction, and is a debit amount or a credit amount of a single journal. This is because in the case of a single journal, the debit amount and the credit amount are the same. Also, items may be stored separately for the debit amount and the credit amount so that a composite journal having different debit amounts and credit amounts can be created. For example, if the transaction category is tax-included, the amount includes the consumption tax amount, so the amount (value “1,080”) of the journal data (when the value of the journal ID is “J001”) is the value of the transaction amount (value “1,000”) includes the consumption tax amount (the value of which is “80”). If the transaction category is tax-excluded, the amount does not include the consumption tax, so the amount (the value “1,000”) of the journal data (when the journal ID value is “J003”) is only the transaction amount. Does not include the consumption tax amount (the value “80”).

The consumption tax amount is the amount of the consumption tax, and the tax rate (8%, 10%, etc.) set based on the tax classification code (value of "taxation") and the tax rate code (value of "standard tax rate" or "reduced tax rate") ), Calculate the consumption tax, and set the amount to the consumption tax amount in consideration of the tax-included and tax-excluded settings of the transaction category (whether or not to add the consumption tax amount to the amount). When the value of the tax classification code is “not taxable”, the value of the tax rate code is “none”, and the value of the consumption tax amount is “0”.

The summary is a transaction content such as the name and name of the counterparty of the transaction, the content of the provision of the asset or the service, and the like, and is a supplementary content to the account. Originally, there is no need to describe the summary of the journal, but the taxable business operator of the consumption tax needs to describe the requirements for describing the consumption tax in the summary of the journal. Therefore, by summarizing the description phrase (keyword) according to consumption tax description requirements (predetermined words in consumption tax journals), and automatically generating a summary that satisfies the consumption tax description requirement from the content of the transaction, The burden of input can be reduced, and an appropriate summary can be easily generated. The predetermined word group may be a transaction configuration parameter other than the requirement for describing the consumption tax.

The slip classification is a classification of a slip (primitive voucher) in which the slip image is a receipt, a receipt, or the like. The slip content is the content of text information acquired from the slip image in a character recognition process using OCR or the like. Although the details will be described later, this text information is used to automatically create summary information.

The subject summary table 33 shown in FIG. 5 is a diagram showing associations between account subjects, their lending (debit, credit), and summary types. Account items, credits (debits, credits), and summary types are stored in association with each other.
The summary type is obtained by classifying transaction contents and transaction status for each transaction category. Further, it is a subject summary table to be registered in association with the summary type and the input account. In addition to the items described in FIG. 5, for example, an item for performing weighting based on a priority such as the number of times of use may be stored. By performing weighting, summary types related to commonly used accounts may be displayed in descending order of priority, and the person in charge may select the summary type, or by learning the summary type that is frequently used and providing feedback. An optimal summary type table can be created for each company or each year and month.

In addition, the summary type is a combination of the account, its loan and the transaction category related to the account, and in the case of cash debit, the cash account such as sales, accounts receivable, goods purchase, other deposits and deposits is debited. Transaction categories to be journaled are stored. Similarly, in the case of a cash credit, a transaction category in which a cash account such as food and drink, transportation, purchase of goods, utilities, taxes, purchases, accounts payable, unpaid, other payments, and deposits is credited is stored. ing. There are both cash debits and credits for deposits, but in the case of cash debits, deposits are withdrawn from deposits, and in the case of cash credits, deposits are deposits to deposits. By using the summary type, it is possible to narrow down the transaction category related to the account using the account as a key.

The summary type table 34 illustrated in FIG. 6 is a diagram illustrating a summary item configuration in which combinations of transaction contents and transaction status are summarized for each transaction category. The summary item is obtained by decomposing the transaction contents and the transaction status for each keyword and compiling them for each category. Further, it is a summary type table for registering a summary item configuration, which is a combination of summary items, with a summary type. The summary type table 34 stores the summary type, the number of items in the summary item configuration, and the content of each item in the summary item configuration in association with each other. In addition to the items described in FIG. 6, for example, an item for performing weighting based on the priority such as the number of times of use may be stored.

Of the summary types related to account items that are often used by performing weighting, if the summary type is different even if the same summary type (eg, traffic) (“traffic”-“traffic / fare / content / payment”) Destination / Visit / Reason for Visit ”or“ Transport ”-“ Transport / Accommodation / Contents / Payee / Accommodation / Reason for Visit / Taxation Class Code / Tax Rate Code / Amount ”etc.) It is also possible to allow the user to select, or by learning the summary type that is frequently used and performing feedback, it is possible to create an optimal summary type table related to the account item for each company or each year and month. A summary type table for each company that reflects the latest trends by optimizing each year and month may be created.

In FIG. 6, the same name (eg, traffic) is used in the summary type even if the description item configuration is different, but different names (eg, traffic 1, traffic 2) are used when the description item configuration is different. You may. When different names (eg, traffic 1, traffic 2, etc.) are used in the summary type table, the summary types in the subject summary table 33 are also stored with different names (eg, traffic 1, traffic 2, etc.).

The subject summary pattern table 35 shown in FIG. 7 is a diagram showing associations between summary patterns in which combinations of summary terms are standardized and combinations of account subjects. The summary pattern is a combination of one or more summary words constituting the summary information. Also, it is a subject summary pattern table for registering the summary pattern and the input account subject in association with each other. The subject summary pattern table 35 includes a debit subject, a credit subject, a department name, an amount, a ratio, an object, a tax classification code, a tax rate code, a standard deviation, a criterion, a description pattern, and the number of registrations. , Evaluation information, and transaction configuration information are stored in association with each other.

By combining account names (debit and credit items) with department names, amounts (combinations of amounts and criteria), ratios (combinations of ratios and targets and criteria), tax classification codes, tax rate codes, and standard deviations Further, by narrowing down the summary patterns, it is possible to display a highly accurate combination of summary words and phrases as candidates. All items may be used for filtering, or some items such as “Account (Debit and Credit)”, “Department Name and Amount”, and “Account and Department Name” Amounts "," accounts and amounts "," accounts and objects and ratios "," accounts and tax classification codes and tax rate codes "," accounts and standard deviation ", and the like may be used.

The debit item (debit account item) and the credit item (credit account item) are the debit item (debit account item) and the credit item (credit account item) of the journal data DB shown in FIG. The department name is the department name in the company DB shown in FIG. 3, and the department may be different even with the same summary. Since the contents of the summary to be entered may differ between the same account item when the amount is high and when the amount is low, the amount of each journal and the amount set in FIG. In such a case, the summarizing pattern can be narrowed down by making a comparison based on a large amount of money and a small amount of money when the criterion is small.

The ratio can be narrowed down by calculating the ratio of the amount of each journal to the amount of the reference target, and comparing the calculated ratio of the amount with the ratio set in FIG. 7 based on the determination criterion. . The tax classification code and the tax rate code are the tax classification code and the tax rate code of the journal data DB shown in FIG. The standard deviation is obtained by obtaining a normal distribution (average value and standard deviation) with respect to the amounts of all journals, and comparing the calculated standard deviation with the standard deviation set in FIG. it can. The number of registrations is the number of times the summary information created by selecting the summary phrase by the person in charge is registered in the subject pattern table.

The evaluation information is a predetermined element for classifying a plurality of accounts for a plurality of transactions belonging to an arbitrary transaction category used in clustering (classifying a group of words) to be described later. This is an evaluation value for each transaction configuration parameter such as a tax rate code. The transaction configuration information indicates the affiliation (predetermined word group) of each abstract phrase or each abstract pattern used in clustering, which will be described later, and a transaction configuration parameter (clustering parameter) for configuring each cluster (predetermined word group). Key).

In addition to the items described in FIG. 7, for example, an item for performing weighting based on the priority such as the number of times of use may be stored (an example of a modified summary pattern). In the case of adding the number of times of use, a combination of the frequently used portions of the abstract pattern (eg, book fee-magazine A-convenience store E-1) is used in abstract pattern 1 (eg, book fee-magazine A). By setting the combination of the following summary words as summary pattern 2 (eg, convenience store E-1), the weight of summary pattern 1 is weighted by the number of registrations, and the weight of summary pattern 2 is weighted by the number of times of use. Note that a summary pattern with a large number of registrations may be displayed as a summary sentence candidate indicating the transaction content used in the summary information.

If the abstract pattern 1 (example: book price-magazine A) is the same, but the abstract pattern 2 (example: D bookstore-1 book) is different, the case of FIG. 7 is the abstract pattern (example: "book price-magazine A-convenience store"). E-1 book "," book-magazine A-D bookstore-1 book ", etc.), but in the case of the modified summary pattern example, search is for summary pattern 1 (eg: book-magazine A-magazine A). Then, by searching for the summary pattern 2 (eg, “Convenience store E-1 book”, “D bookstore-1 book”, etc.), it is possible to find a combination of account items that are used more frequently than in the case of FIG. Since the retrieval time of the abstract pattern can be reduced by narrowing the abstract patterns, the display time of the abstract word candidates displayed in the descending order of the priority order from the abstract pattern which is the combination of the abstract pattern 1 and the abstract pattern 2 can be shortened. Is selected By learning the combination of the abstract pattern 1 and the abstract pattern 2 and providing feedback, it is possible to create an optimal subject abstract pattern table for each company or each year and month. Further, by narrowing down by department name, amount, ratio, tax classification code, tax rate code, standard deviation or a combination thereof, it is possible to perform highly precise narrowing.
By optimizing each year and month, a subject summary pattern table for each company that reflects the latest trends may be created.

Specifically, a key word included in the summary information of the matching journal data from the journal data DB is extracted from the subject summary pattern table using the company code selected from the company DB as a key, and the subject summary pattern table for each company is extracted. create. Further, based on a reference setting (not shown) in which the occurrence time of the past transaction to be referred to is set, a target date which is the date of occurrence of the transaction to be accounted is obtained, and the target date and the reference are obtained. Based on the setting, determine a reference period for limiting the date of occurrence of past transactions to be referred to, and use the reference period as a key to include in the summary information of matching journal data from the journal data DB. The extracted summary phrase is extracted from the subject summary pattern table, and a subject summary pattern table for each month is created.

The keyword dictionary 36 shown in FIG. 8 is decomposed from the summary information of the journal data registered in the past for each of the summary phrases, and the keyword and the account, which are the character strings (phrases) of the summary associated with the categories such as business partners and personal names. It is a figure which shows the association of. In addition, the keyword dictionary is registered as a keyword in which a category indicating the transaction content is associated with a summary phrase associated with the input account item. The keyword dictionary 36 stores a keyword, an account item, a loan, a category, an item, a process, a particle, a tax classification code, a tax rate code, an occurrence count, and a selection count in association with each other.

The account item is the name of a classification item necessary to represent the nominal amount of the display amount used in journal entries in double-entry bookkeeping, financial statements, and the like. It is also used as a key for clustering.

Lending refers to debits and credits, and is used in combination with accounts. It is also used as a key for clustering.

The category indicates a transaction classification or a classification based on the transaction contents and transaction status of the business partner, person name, payment, product, and the like. In addition, by associating keywords with transaction categories, if there is no connection with an account (eg, travel expenses and salary allowance) but they are in the same category (eg, person name), and there is no summary phrase candidate (eg, Employees who have not paid for transportation expenses in the past because they have paid salary, such as employees who have not paid for transportation expenses in the past are displayed as summary phrase candidates, etc. (Can be extracted as a candidate) can be used as a summary word candidate with priority. It is also used as a key for clustering.

The items indicate transaction configuration, types, attributes, and the like based on transaction contents and transaction status, such as cash, sales, purchases, traffic, payees, destinations, and visit reasons. The item is associated with the content of each item of the summary item configuration of the summary type table and a keyword, and a keyword corresponding to the item of the summary item configuration can be used as a summary word candidate. It is also used as a key for clustering.

The process is to perform a specific process associated with the keyword to add a date or amount to the summary word candidate (for example, the date is November 24, the amount is 50,000 yen, and the keyword is “rent”). Is a date, the summary word candidate is "November Rent", and if the processing is a monetary amount, the summary word candidate is "Rent 50,000 yen". You do not need to register (example: “November rent”, “December rent”, “October rent 50,000 yen” are different keywords, so usually all will be registered. However, if you register for "monthly rent," you only need to register "monthly rent" and "rent 50,000 yen," and if you register for "rent," you only need to register one.)

Particles can be used to form natural summary information by performing sentence shaping processing using particles when generating summary information.

The tax classification code and the tax rate code are the tax classification code and the tax rate code of the journal data DB shown in FIG. It is also used as a key for clustering.

In addition to the items described in FIG. 8, for example, a flag indicating whether or not a particle is used may be stored. The number of appearances is the number of times the keyword has been displayed as a summary word candidate. The number of selections is the number of times the keyword has been selected from the summary word candidates. By performing weighting using the number of appearances and the number of selections, frequently used account items and related summary types are displayed in descending order of priority, and the person in charge may select them. By learning many abstract types and providing feedback, it is possible to create an optimal keyword dictionary for each company or each year and month. By optimizing each year and month, a keyword dictionary for each company reflecting the latest trends may be created.

Specifically, using the company code selected from the company DB as a key, abstract words included in the summary information of the matching journal data are extracted from the keyword dictionary from the journal data DB, and a keyword dictionary for each company is created. Further, based on a reference setting (not shown) in which the occurrence time of the past transaction to be referred to is set, a target date which is the date of occurrence of the transaction to be accounted is obtained, and the target date and the reference are obtained. Based on the setting, determine a reference period for limiting the date of occurrence of past transactions to be referred to, and use the reference period as a key to include in the summary information of matching journal data from the journal data DB. The key words to be extracted are extracted from the keyword dictionary, and a keyword dictionary for each year and month is created.

The input unit 45 in FIG. 2 is an input device such as a keyboard and a mouse. The input unit 45 may be a touch panel or a pen input. Further, the input unit 45 may be an input device such as a microphone for voice input, a camera or a scanner for image input.
The display unit 46 is a display device including an LCD (Liquid Crystal Display) or the like.
The communication unit 49 is, for example, a slip image reading device such as a scanner or an interface for performing communication with an external device via a communication network.
Note that the computer in the present invention refers to an information processing device including a control unit, a storage device, and the like, and the accounting processing device 1 is an information processing device including the control unit 10, the storage unit 30, and the like. Included in the concept of computer.

<Processing of accounting processor 1>
Next, a process performed by the accounting apparatus 1 will be described.
FIG. 9 is a flowchart illustrating processing in the accounting processing device 1 according to the present embodiment.
The processing of the first embodiment will be described with reference to a flowchart. In addition, as for other described examples such as the second and third embodiments and the modified examples of the respective embodiments, only the differences from the first embodiment are described, and the description of the common portions is omitted.

  A person in charge (eg, a staff of an accounting firm, an employee of the accounting department, etc.) starts an accounting application, selects a company (eg, ABC Industries) that performs accounting, and selects a fiscal year (eg, 2017) and The date to be processed (for example, November 2017) is set. The company information including the settlement year of the selected company is acquired from the company DB, and the input screen of the accounting data of the selected accounting year is displayed (step S (hereinafter simply referred to as “S”) 101).

  For a single transaction, look at the receipt or receipt for the transaction that corresponds to the date (eg, November 20), debit account (eg, expense), credit account (eg, cash), amount (eg, : 8,000 yen). The receipt and the receipt may be digitized in advance, and may be input while displaying an image and referring to the image (S102).

  A description pattern (eg, “taxi”) that matches the debit item (eg, debit item−interest expense) and the credit item (eg, credit item−cash), which is the account item input with reference to the item description pattern table, as a key Fees-Reimbursement-○ Taro, Taxi fare-Higashi □ Business entertainment-× Saburo Shima, "Condolence expenses-To Higashi □ Corporation-○ Tataro", "Green mourning expenses-△ To the tree company-- Tataro "). If a matching summary pattern is not found in the subject summary pattern table and a matching summary pattern is not found, the journal data DB is referenced to narrow down by account (eg, debit subject-compensation expense, credit subject-cash). A summary pattern is created with reference to the keyword dictionary described later from the summary information thus obtained.

In addition, when the department name is different for the same summary content, a more precise summary pattern can be obtained by further narrowing down by the department name. For example, when narrowing down by account items (eg, debit item-compensation cost, credit item-cash), summary pattern 3 ("taxi payment-payment settlement", department name-business) and summary pattern 4 ("taxi payment-payment") The settlement pattern 4 can be extracted by further narrowing down the department name to “general affairs”.

In addition, when the amount is high and when the amount is low, the content of the summary to be input may be different even for the same account item, and there is a judgment based on the amount and a judgment based on the amount ratio. As a judgment based on the amount, for example, when narrowing down by an account item (eg, debit item-interest expense, credit item-cash), the amount set by the user or the like is "5,000 (yen)" and the judgment criterion is "large". By comparing the results and narrowing down the conditions based on the comparison results (greater than 5,000 yen), the summary patterns registered in the subject summary pattern table, “Food and Beverage Fees-Entertainment for Customers-Higashi □ Trading-× Island In addition to "Saburo", similar abstract patterns such as "Food and drink costs-Entertainment for customers-East Shoji" and "Food and drink costs-Entertainment for customers-East Shoji-Otataro" etc. can be extracted. .

Next, as a judgment based on the amount ratio, for example, when the target is sales, the ratio between the amount of each journal and the total amount of sales is calculated based on the total amount of sales, and the account item (eg, debit item-interest expense, credit When narrowing down by (subject-cash), further compare with the ratio "0.3" set by the user etc. with the judgment criterion "large" and narrow down (greater than 0.3) based on the comparison result In addition to the summary patterns registered in the subject summary pattern table, “Food and Beverage Fees-Hospitality to Customers-Higashi □ Shoji-× Saburo Shima,” the similar summary pattern “Food and Drink Costs-Hospitality to Customers-Higashi □ “Trading” and “Food and Beverage-Entertainment for Customers-Higashi □ Trading-O Taro” can also be extracted. Although the target is sales in the embodiment, another account such as selling expenses and general administrative expenses may be designated.

Further, in the embodiment, the total amount of sales (total of annual amounts) is used, but may be the total of monthly amounts of sales, or the total of daily amounts, and is not limited to the total.
In addition, since the tax rate of the consumption tax is different even for the same account, for example, when narrowing down by the account (eg, debit item-interest expense, credit item-cash) and tax classification code "tax", the tax rate code By narrowing down by “reduced tax rate”, it is possible to extract a summary pattern such as “newspaper fee-Y newspaper-convenience store E-1”.

In addition, when narrowing down by an account item (eg, debit item-compensation cost, credit item-cash), a predetermined probability distribution is obtained from the average value and the standard deviation from the amounts of all the journal data registered in the journal data DB. Thus, when the predetermined probability distribution is a normal distribution (mean value and standard deviation), the specific data (one or more amounts of money) is changed from “mean value−1 × standard deviation” to “mean value + 1 × standard deviation”. Is about 68%, and the probability of being within the range of “mean−2 × standard deviation” to “mean + 2 × standard deviation” is about 95%, so that the standard deviation α ( For example, based on α = 2,600 yen, average value 13,450 yen, a plurality of specific data amounts (for example, random numbers) generated from random variables according to a predetermined probability distribution such as a normal distribution (for example, random numbers) 6,000 yen) and an account (eg, debit account-exchange) The value “5,000 yen” of the amount corresponding to “expense, credit item-cash” is compared, and the result is narrowed down based on the comparison result satisfying the judgment criterion value “large” (specific data larger than 5,000 yen is extracted). , A plurality of corresponding abstract patterns can be extracted, and a high-precision narrowing-down can be performed. In the present embodiment, the normal distribution has been described, but another probability distribution such as a binomial distribution may be used.

In addition, for words (keywords) and sentences (summary patterns) extracted from the summary information of journal data, elements (for example, “category” indicating “transaction events and transaction contents”) set in the extracted words (keywords) are used. , "Items" indicating "Business partners and transaction status", and "Lending and borrowing" of accounts, transaction configuration parameters such as "Taxation classification code" and "Tax rate code" as keys, and clustering (= classification of words) , And extract an optimal word from each element. Then, it is possible to narrow down the summary patterns that match based on the extracted words, and thus it is possible to form a summary without omission that satisfies the requirements required by law. If a matching summary pattern is found in the subject summary pattern table, the key of clustering is stored in “transaction configuration information” of the subject summary pattern table.

If a matching abstract pattern is not found in the subject abstract pattern table, it corresponds to the abstract phrase or abstract pattern (combination of abstract terms) included in the abstract information (transaction contents and transaction status) of each journal data from the journal data DB. The structure of the evaluation information for each transaction configuration parameter (loan, category, item, tax classification code, tax rate code, etc.) of the description phrase or description pattern included in the description information of each journal data The transaction composition information indicating the affiliation of each abstract phrase or each abstract pattern (such as lending, category, item, tax classification code, tax rate code, etc.) (Combination of configuration parameters), and the transaction configuration information is stored in a keyword dictionary or subject summary pattern template. And outputs it to the table.

Here, as an index indicating similarity, a method of calculating an average value between transaction contents as a representative value of evaluation information for each transaction configuration parameter, and using the closeness of the Euclidean distance between the representative values as an index of similarity Alternatively, a method may be considered in which a correlation coefficient calculated for the entire transaction content with respect to the evaluation information of each summary phrase or summary pattern is used as an index of similarity. In addition, a general method may be used as the clustering method. For example, agglomerative hierarchical clustering (group averaging method, centroid method, Ward method, etc.) and division optimization type clustering (k-means method, etc.) are considered. Can be

The number of clusters in clustering varies depending on the number of data in the case of unsupervised clustering. However, in the case of performing semi-supervised clustering, it may be set arbitrarily according to the number of types of transaction contents and transaction situations. Based on the transaction configuration information, by selecting a description phrase or a description pattern from each transaction configuration having a different tax classification code and tax rate code, a description phrase that is an optimal combination of an account, a tax classification code, and a tax rate code for the transaction. Or, select an abstract pattern. The selection of an abstract phrase or an abstract pattern may be selected one by one from each transaction configuration, or each transaction configuration and the transaction configuration feature are relatively close to each other from the keyword dictionary or the subject abstract pattern table, or By extracting the number of appearances, the number of selections, the number of registrations, and the name of the section, etc. of the abstract pattern, the abstract words or abstract patterns (abstract sentences) selected from each cluster according to the number of appearances, the number of selections, the number of registrations, the department name, etc. The number may be weighted.

Since there are a plurality of summary patterns that match using the debit subject and the credit subject as keys, a summary pattern list is created by combining a plurality of summary patterns. The summary pattern list is prioritized in the descending order of the number of registrations of the summary pattern, and the summary patterns are rearranged (eg, “taxi fare-reimbursement settlement-Otataro” (7 times of registration), “taxi fare-east □ Business entertainment-× Shima Saburo ”(5 registrations),“ Bus fee − △ to the tree company ”-○ Tataro-Business talks (4 times of registration),“ Congratulations-East □ To the trading company-○ Taro ”(3 registrations). From the rearranged summary pattern list, the summary pattern with the largest number of registrations (eg, summary pattern “taxi fare-reimbursement payment-○ Taro” (registration frequency: 7 times)) is acquired (S103).

The abstract pattern extracted here may be used as an abstract sentence candidate, or the process may proceed to S104 to extract an abstract phrase.

As a modified example of S103, referring to the summary pattern list including evaluation information for each transaction configuration parameter associated with an account for a plurality of transactions belonging to an arbitrary transaction category from the subject summary pattern table, and configuring the transaction configuration information of each summary pattern ( (Combination of transaction configuration parameters such as lending, category, item, taxation classification code, tax rate code, etc.) The transaction configuration information indicating the affiliation is obtained, and the transaction configuration information is output to the subject summary pattern table.

Based on the transaction configuration information, by selecting a description pattern from each transaction configuration having a different tax classification code and tax rate code, an optimal combination of the account item, tax classification code, and tax rate code for the transaction from the selected plurality of description patterns. Is extracted. The summary pattern may be selected one by one from each transaction configuration, or the number of registrations and department names of the transaction configuration or the summary pattern whose transaction configuration characteristics are relatively close to each transaction configuration may be extracted from the subject summary pattern table. Then, the number of summary patterns selected from each cluster may be weighted according to the number of registrations or the department name. The summary pattern list is created from a plurality of selected summary patterns.

The keyword dictionary is decomposed for each keyword by referring to the keyword dictionary to obtain a description word and a description word of each description pattern (for example, the number of description words is 3 from the description pattern "taxi fee-reimbursement settlement-Otataro") And the abstracts of "taxi fare," "pay-for-pay," and "* Taro"). Next, in the summary pattern list, the first summary word candidate from the summary pattern in the summary pattern list is displayed in descending order of the total number of usages of the summary word. More specifically, the first abstract phrase of each abstract pattern in the abstract pattern list is extracted, and the extracted abstract phrases are arranged in descending order of priority, so that abstract word candidates (eg, "taxi fee", "hand gift" , "Congratulations" etc.) (S104).

The display of summary word candidates is "unselected" (fixed), "a plurality of summary words narrowed down from the summary pattern list in descending order of priority" (eg, "taxi fare", "hand gifts", "congratulations" Expenses, etc.)) (variable), and “direct input” (fixed) described later.
Note that if the extracted abstract phrases overlap, an exclusion process is performed to exclude the second and subsequent abstract phrases of the overlapping abstract phrases (for example, in the case of the above four abstract patterns, the first abstract phrase is " Taxi fare, taxi fare, bus fare, souvenir fare, and congratulations fee will be collected, but due to the exclusion process, candidates will be taxi fare, bus fare, and souvenir fare , "Condolence expenses").

In addition, in the embodiment, the summary word candidates are displayed according to the priority according to the number of registrations, but the registration update date of the summary pattern matches the latest summary pattern, the total number of usage of the summary word, the number of usage of the summary word, and the keyword that matches the summary word. May be prioritized based on the number of occurrences or the number of selections, or the total number of usages of the abstract, the number of usages of the abstract, the number of registrations, the date of registration update, the number of appearances, the priority by weighting using the number of selections May be attached.

The summary word candidate displayed in S104 (eg, “taxi fare”) is selected and fixed as the summary word (S105). The keyword dictionary is updated by adding 1 to the number of appearances of the summary phrase displayed as the summary word candidate. Further, 1 is added to the number of times of selection of the selected summary word candidate, and the keyword dictionary is updated. In this embodiment, both the number of appearances and the number of selections are updated, but only the items used in the priority order may be updated. If the number of summary words acquired from the summary pattern acquired in S103 is 1 (S106: No), the process moves to S112.

If the number of summary words acquired from the summary pattern acquired in S103 is 2 or more (S106: Yes), the processing from S108 to S111 is repeated by the number of summary words (S107).
By displaying the candidate word phrases in order of the number of summary words, the summary words are narrowed down step by step, and the frequently used summary words and the summary words closely related to the previous summary word are appropriately displayed as the summary word candidates. Is done.
In addition, although the judgment condition in S106 is that the number of summary words is two or more, any condition may be used as long as it is possible to determine whether the summary pattern is singular or plural.

If there is only one summary phrase registered in the summary pattern, it is displayed as a summary word candidate as it is, and the selected summary word candidate is determined as a summary. If there is no option in the summary phrase candidate, you can enter the summary phrase directly, or you can decompose the summary information of journal data registered in the past for each summary phrase and associate it with categories such as business partners and personal names A category such as a business partner or a person's name may be selected from the dictionary to display summary word candidates. The keyword dictionary is updated by adding 1 to the number of appearances of the summary phrase displayed as the summary word candidate. Further, 1 is added to the number of times of selection of the selected summary word candidate, and the keyword dictionary is updated. In this embodiment, both the number of appearances and the number of selections are updated, but only the items used in the priority order may be updated.

That is, when journal data is registered in the journal data DB, 1 is added to the number of times of selecting the corresponding abstract phrase or the corresponding abstract phrase is added to a new keyword depending on the presence or absence of the abstract phrase used in the abstract information in the keyword dictionary. By automatically registering the keyword as a feedback, the keyword dictionary is fed back to the keyword dictionary, so that an optimal keyword frequently used by the keyword dictionary for learning can be registered efficiently. In addition, when registering journal data in the journal data DB, 1 is added to the number of times a summary pattern that matches the corresponding summary information is selected or the corresponding summary information is newly added, depending on whether or not the summary information is registered in the subject summary pattern table. By automatically registering a summary pattern as a simple summary and providing feedback to the subject summary pattern table, the subject summary pattern table can efficiently register an optimal summary pattern that is often used for learning.

In addition, a summary pattern including the selected summary word candidate (eg, “taxi fare”) from the summary pattern acquired in S103 (eg, “taxi fare-pay-as-you-go payment-田 Tataro”, “taxi fare-east □ Shoji entertainment” − × Saburo Shima ”) may be extracted (S108).

An abstract word next to the abstract word candidate selected from the extracted abstract pattern (the selected abstract word candidate is the first word, so the next abstract word is the second) is extracted, and the extracted abstract word is extracted as an abstract word candidate ( (Example: "Payment for payment", "Entertainment for commercial affairs", etc.) (S109).

In addition, selection is made (eg, “payment settlement”) from the displayed summary word candidates (eg, “payment settlement”, “East Shoji entertainment”). The keyword dictionary is updated by adding 1 to the number of times of selection of the selected summary word candidate (S110). If there is no option in the summary word candidate, the summary word may be directly input, or a category such as a business partner or a person's name may be selected from the keyword dictionary to display the summary word candidate. The keyword dictionary is updated by adding 1 to the number of appearances of the summary phrase displayed as the summary word candidate.

The selected summary phrase (eg, “taxi fare”) is combined with the selected summary word candidate selection (eg, “payment settlement”), and determined as a summary word (S111). Although the processing of S111 is directly combined in the present embodiment, the processing may be performed after the sentence shaping process is performed by adding a particle to the confirmed summary word and then combined.

If the determined summary phrase (including the case where it is combined in S111) is registered as a summary pattern in the subject summary pattern table (S112: Yes), 1 is added to the number of times the summary pattern is selected (S113) and registered. If not (S112: No), it is registered as a new summary pattern in the subject summary pattern table (S114). The summary information is automatically generated from the determined summary word or description, and the tax classification code and the tax rate code corresponding to the determined summary word or description are automatically determined.

Thereafter, journal data is generated based on the input date, account item, amount, description information, tax classification code and tax rate code. Specifically, the amount of consumption tax is set to the consumption tax amount based on the consumption tax rate (10%, 8%, etc.) in consideration of the set contents of the journal data including tax and tax (tax classification code, tax rate code, etc.). The generated journal data is registered in the journal data DB.

Since the specific contents of the modified example include a plurality of summary patterns that match using the debit subject and the credit subject as keys, a summary pattern list is created by combining a plurality of summary patterns. Using the debit subject (eg, debit subject-compensation expense) as a key, a debit keyword (eg, taxi fare, reimbursement, Otaro, etc.), which is a keyword associated with the debit subject, is acquired from the keyword dictionary. In addition, using the credit item (eg, credit item-cash) as a key, a credit keyword (eg, taxi fee, advance payment, cash payment, etc.) which is a keyword associated with the credit item is acquired from the keyword dictionary.

Next, the acquired descriptive keywords and the debit keywords are used as keys, respectively, to obtain the matching description terms from the description pattern list for each description pattern. Number) ”) (Example:“ Taxis (7 times)-Advance payment (5 times)-○ Taro (4 times) ”,“ Taxis (7 times)-Higashi □ Shoji entertainment (3 Times)-× Saburo Shima (3 times), "Condolence expenses (5 times)-To East Shoji (5 times)-○ Taro (4 times)", "Bus fare (5 times)-△ Tree Shokai (3 times)-○ Taro (4 times)-Business talks (5 times) ").

The number of use of the description words for each of the description patterns obtained in S103 is totaled, and the total number of use of the description words for each description pattern (displayed as “summary pattern (total number of use of description words)”) is obtained (example: Taxi fare (7 times)-Advance payment (5 times)-○ Taro (4 times) (16 times), "Taxi fare (7 times)-Higashi □ Business entertainment (3 times)-× Shima Saburo (3 times) Times) (13 times), congratulations (5 times)-To East Shoji (5 times)-○ Taro (4 times) (11 times), "Bus fee (5 times)-△ tree company (3 times)-Business negotiations-○ Taro (4 times) "(12 times).

Decompose all the abstract patterns included in the abstract pattern list and obtain the number of abstract words and the abstract words (Example: From the abstract pattern "taxi fee-pay-on-delivery-○ Tataro", the abstract word number 3 and the "taxi fee", Obtain a summary phrase of "advance payment" and "○ Taro"). Next, sort the summary patterns in the summary pattern list in descending order of the total number of terms used (eg, "taxi fare (seven times)-reimbursement settlement (five times)-○ Taro (four times) summary words and phrases 3" ( 16 times), "Taxis (7 times)-East business entertainment (3 times)-× Shima Saburo (3 times) Key words and phrases 3 times" (13 times), "Bus fare (5 times)-△ Kishokai To (3 times)-○ Taro (4 times)-Business talks (5 times) Number of words and phrases: 4 (12 times), "Condolence expenses (5 times)-To East Shoji (5 times)-○ Taro (4 times) Number of abstract words 3 "(11 times).

From the rearranged abstract pattern list, an abstract pattern having the largest total number of abstract terms used (eg, an abstract pattern "taxi fare-reimbursement settlement-Otataro" (16 times)) is acquired (S103). The first summary word / phrase candidate is displayed from the summary patterns in the summary pattern list. Specifically, by extracting the first summary phrase of each summary pattern in the summary pattern list, the summary phrase is narrowed down step by step, and the extracted summary phrase is selected as a summary word candidate (eg, "taxi fee", "souvenir" Cost, etc.) and “congratulations” (S104).

From the abstract pattern acquired in S103 (eg, the abstract pattern "taxi fare-reimbursement-○ Tataro" (16 times, the number of abstract phrases is 3), the number of abstract phrases is 3, and the top of the first abstract phrase candidate is " The highest rank of the taxi fee and the second number of words and phrases is "payment settlement", and the highest number of the last word and phrase candidates is "○ Taro". Next, an abstract pattern list in which the abstract patterns are sorted in descending order of the total number of abstract terms used (example: taxi fee (number of abstract terms used: 7 times)-Payment settlement (number of abstract words used: 5 times)-○ Taro ( Number of abstract words used: 4) Number of abstract words: 3 (total number of abstract words used: 16), Taxi fare (7 times)-East business entertainment (3 times)-× Saburo Shima (3 times) Number 3 ”(13 times),“ Bus fare (5 times)-To Kyushokai (3 times)-○ Taro Taro (4 times)-Business talks (5 times) Key words 4 (12 times), “ Based on congratulations (5 times)-To East Shoji (5 times)-○ Taro (4 times, number of words and phrases 3) (11 times) from the pattern list, "taxi fare (7 times), taxi Fee (7 times), bus fee (5 times), condolence expenses (5 times) ", and the first summary word and phrase by exclusion processing The supplement is "taxi fare (7 times), bus fare (5 times), condolence expenses (5 times)".

In addition, the second summary word candidate from the pattern list is “advance payment (5 times), east □ business entertainment (3 times), Takagi Shokai (3 times), east □ business (5 times)” Becomes Also, “Taro Taro (4 times), Saburo Xshima (3 times), Taro Taro (4 times), and Taro Taro (4 times)” are obtained from the pattern list, and the third summary is obtained by the exclusion process. The phrase candidates are "○ Taro (four times), x Saburo Shima (three times)". In the present embodiment, the summary pattern is displayed in descending order of priority according to the total number of terms used, but may be changed to be displayed in descending order of priority according to the number of terms used at the time of displaying each candidate term candidate. .

The input term determined in S105 (for example, "taxi fare-reimbursement-X Saburo Shima") is determined as the input summary information. After creating the journal data, it is registered in the journal DB. At the time of registering the journal data, it is checked whether or not the summary information of the journal data is in the subject summary pattern table as a summary pattern. If there is no summary pattern that matches the summary information (S112: No), the summary information (for example, “taxi”) The payment is made in the subject summary pattern table as a new summary pattern (S114). If there is a summary pattern that matches the summary information (S112: Yes), 1 is added to the registered number of registered summary patterns, and the subject summary pattern table is updated (S113).

As another description example, the date (eg, November 20), debit account (eg, rent), credit account (eg, cash), and amount (eg, 5,000 yen) are described. In the case of the pattern "Monthly parking fee-2nd parking lot-Monthly", the value of the processing column of the keyword dictionary of "Monthly parking fee" is "Date" by referring to the keyword dictionary. The “November parking fee” combined with the acquired “November” and the extracted “Monthly parking fee” is displayed as a keyword candidate. Although “November parking fee” is displayed as a keyword candidate, “Month parking fee” is displayed as a keyword candidate, and “Monthly parking fee” is selected when “Monthly parking fee” is selected. May be created and substituted into the summary information.

In addition, "5,000 yen per month" combined with "5,000 yen" obtained from the date in S104 and S105 and extracted is displayed as a summary phrase candidate. Although "5,000 yen per month" is displayed as a summary word candidate, "monthly amount" is displayed as a summary word candidate, and when "monthly amount" is selected, "5,000 yen per month" is created and summary information is created. May be substituted. If a new word is added to the summary word if it is not in the summary word candidate, select the direct entry (not shown) at the bottom of the summary word candidate and add a new summary word (eg "company car"). To enter. When the input is determined, it is registered in the keyword dictionary.

When registering in the subject summary pattern table in S106, if the date or amount is included in the summary information, such as "November parking lot-second parking lot-5,000 yen per month-company car" For the date, remove the numeric part of the date, and for the amount of money, remove the number of the amount of money and units such as yen, and then add “Monthly parking fee-2nd parking lot-monthly amount-company car”. Is registered in the subject abstract pattern table as a simple abstract pattern.
In the present embodiment, the summary information is created from the summary pattern, but when creating the summary information, the subject summary table is referred to, the corresponding summary type is set, the summary pattern is summarized, and the summary information is created. You may make it create.

According to this embodiment, it is possible for the person in charge to easily create the summary information by simply selecting the summary phrase without registering the summary information in advance or manually inputting the summary information when inputting the journal data, This has the effect of reducing the trouble of inputting journal data. Further, information relating to a transaction required for selecting an account item can be created as summary information. Also, by repeating the selection, the accuracy of the summary word candidates is improved, and the summary word candidates can be displayed for each item as if they were linked as if they were not linked.

Furthermore, by registering the created summary information and selected summary phrases, and by feeding back the registered summary information to the subject summary pattern table and keyword dictionary, it is possible to repeat the learning of summary information and summary phrases to create summary information and summary phrase candidates. The accuracy of the display can be improved, and appropriate summary information can be created and appropriate summary phrase candidates can be displayed. "Narrowed down step by step"

The first embodiment creates the summary information using the subject summary pattern table in which the debit and credit account items are associated with the summary pattern, while the second embodiment describes the process of creating the summary information with the flowchart of FIG. I do.

The processing up to the display of the accounting data input screen is the same as that in S101, and thus the description is omitted. For a transaction, check the receipt and receipt for the transaction, and enter the date (eg, November 20), amount (eg, 8,000 yen), debit account (eg, travel expenses), credit An account item (eg, cash) is input (S201).

A debit summary type (eg, “traffic”), which is a corresponding summary type, is acquired by referring to the subject summary table for the input debit account (eg, travel expenses and transportation expenses) (S202).

  Refer to the subject summary table for the entered credit account (eg, cash), and enter the corresponding credit summary type (eg, “Eating and drinking”, “Transportation”, “Purchase of goods”, “Other payment” Etc.) (S203).

The control unit compares the debit summary type acquired in S202 (eg, “traffic”) with the credit summary type acquired in S203 (eg, “eating and drinking”, “traffic”, “purchase goods”, “other payment”, etc.). , The matching summary type (eg, “traffic”) is set as the debit summary type and the credit summary type. When there are a plurality of matching abstract types, they may be displayed as a list and selected, or a priority may be set for the abstract type and a higher priority type may be set (S204).

The summary item configuration of the summary type (eg, “traffic”) set in the debit summary type (or credit summary type) with reference to the summary type table (eg, “traffic” —the number of items 7 “traffic / fare / content / Payment destination / Visit destination / Reason for visit ") is acquired (S205).

Based on the summary item configuration acquired in S205, the keywords (keywords) associated with the accounts from the keyword dictionary for each item are displayed in the order of the highest priority as candidate keyword phrases (S207). The priority is set based on the number of appearances, the number of selections, and the like. The keyword dictionary is updated by adding one to the number of appearances of the keyword corresponding to the displayed summary word candidate.

As a modified example of S207, a keyword for each summary item configuration including evaluation information for each transaction configuration parameter associated with an account for a plurality of transactions belonging to an arbitrary transaction category is referred to from the keyword dictionary, and the transaction configuration parameter of each keyword is referred to. (Lending, category, item, tax classification code, tax rate code, etc.) The clustering is performed so that keywords having similar structures in the evaluation information have the same transaction structure, and the transaction structure information indicating the affiliation of each keyword is obtained. Then, the transaction configuration information is output to a keyword dictionary (not shown).

Based on the transaction configuration information, by selecting keywords from respective transaction configurations having different tax classification codes and tax rate codes, an optimal keyword that is an optimal combination of an account and a tax rate code for the transaction is selected from the selected keywords. It is extracted for each item of the summary item configuration as a summary word. The keyword may be selected one by one from each transaction configuration, or the transaction configuration or the transaction configuration feature whose transaction configuration feature is relatively close to each transaction configuration or the number of appearances or selections of the keyword may be extracted from the keyword dictionary to appear. The number of keywords selected from each cluster may be weighted according to the number of times or the number of times of selection.

If a matching keyword is not found in the keyword dictionary, the journal data DB refers to the account corresponding to the description phrase included in the summary information of each journal data, and enters the summary information (transaction content and transaction status) of each journal data. ) Is clustered so that the description terms that have a similar structure in the evaluation information for each of the transaction configuration parameters (lending, category, item, tax classification code, tax rate code, etc.) included in the description phrase are included in the same transaction configuration To obtain transaction composition information (combination of transaction composition parameters such as lending, category, item, taxation classification code, tax rate code, etc.) indicating the affiliation of each summary phrase, and output the transaction composition information (not shown) to a keyword dictionary I do.

Based on the transaction configuration information, by selecting a description phrase from each transaction configuration having a different tax classification code and tax rate code, a description phrase that is an optimal combination of an account, a tax classification code, and a tax rate code for the transaction is selected. . The selection of an abstract phrase may be selected one by one from each transaction configuration, or the number of appearances, the number of selections, the number of registrations, the number of occurrences of the transaction configuration or the abstract phrase whose transaction configuration characteristics are relatively close to each transaction configuration from the keyword dictionary, and the like. A section name or the like may be extracted, and the number of summary terms selected from each cluster may be weighted according to the number of appearances, the number of selections, the number of registrations, the name of the section, or the like.

A summary phrase is selected from the summary phrase candidates displayed in S205. The selected summary word candidate is determined as a summary word, and the keyword dictionary is updated by adding 1 to the number of times of selection of the keyword corresponding to the determined summary word.
(S208).

The processes of S207 and S208 are repeated for the number of items of the summary item configuration acquired in S205 (for example, the number of items is 7) (S206).

The summary word candidates selected for each item are combined in the order of the summary item configuration acquired in S205 to create summary information (S209). Specifically, if the number of items is two, the candidate word / phrase candidate selected for item 2 is substituted (confirmed) as a keyword / phrase (eg, taxi fare), and the keyword / phrase substituted for item 1 (eg, traffic) ( The description information (eg, taxi fare: 8,000 yen) is created by combining the description phrase assigned to item 2 (eg, fare) after the example (8,000 yen).
In the embodiment, the words are combined as they are. However, the words may be combined after adding a particle to the summary word candidate selected in each item.

  The summary information created in S209 is input, and the journal data is created and registered in the journal DB. The summary information input this time may be registered as a summary pattern.

S207 and S208 will be described using specific examples. In the case of date (example: November 20), amount (example: 8,000 yen), debit account (example: travel expenses and transportation expenses), the summary type is "traffic", and refer to the summary type table. In S207, the summary item configuration ("traffic"-"traffic / fare / content / payee / visitor / visit reason") is acquired.

For the item “traffic”, a keyword that matches the debit account “travel expenses” and the item “traffic” is searched from the keyword dictionary and acquired as a summary phrase candidate. Since the keyword obtained from the keyword dictionary has a value of “none” in the processing field of the keyword dictionary, the keywords associated with the account (eg, travel expenses and transportation expenses), such as “taxi charges” and “bus charges”, are possible keyword phrases. "Taxi fare" (seven times of selection), "bus fare" (five times of selection), etc. are displayed in descending order of the number of selections. If "taxi fare" is selected, the item "traffic" is displayed. Is replaced with the “taxi fare”, and the process proceeds to the next item “fare”.

The keyword dictionary is updated by adding 1 to the number of appearances of the key words displayed as key word candidates such as "taxi charges" and "bus charges". Further, 1 is added to the number of times of selection of the selected "taxi fee" (the number of times of selection is 7) (number of times of selection is 8), and the keyword dictionary is updated. In this embodiment, both the number of appearances and the number of selections are updated, but only the items used in the priority order may be updated.

Next, for the item “fares”, a keyword that matches the debit account “travel expenses” and the item “fares” is searched from the keyword dictionary, and acquired as a summary word candidate. For the keywords “Fare” and “Fare” obtained from the keyword dictionary, the value in the processing field of the keyword dictionary is “Amount”, so “Fare” and “Fare” etc. are displayed as summary word candidates, and “Fare” If selected, “Fare 8,000”, which is a combination of the summary word candidate “Fare” and the amount “8,000 yen”, is substituted for the item “Fare”, and the process proceeds to the next item “Contents”.

The keyword dictionary is updated by adding 1 to the number of appearances of the key word displayed as a key word candidate such as “fare” and “fee”. In addition, 1 is added to the number of times the selected "fare" is selected, and the keyword dictionary is updated. In this embodiment, both the number of appearances and the number of selections are updated, but only the items used in the priority order may be updated. If you do not want to enter a fare, prepare an input skip item such as "unselected" above the summary word candidate, and if you select an input skip item such as "unselected" as the summary phrase, enter the item "Fare" Is replaced with an empty character.

Next, for the item “contents”, a keyword matching the item “contents” and the item “contents” of the debit account “travel expenses” is searched from the keyword dictionary, and acquired as a summary phrase candidate. The keywords obtained from the keyword dictionary, such as “payment payment” and “entertainment”, have a value of “none” in the processing field of the keyword dictionary. Therefore, “payment payment”, “entertainment”, etc. are displayed as summary word candidates, When "select" is selected, a blank character is substituted for the item "content", and the process proceeds to the next item "payee". The keyword dictionary is updated by adding 1 to the number of appearances of the key word displayed as a key word candidate such as "payment settlement" and "entertainment".

Next, for the item “payee”, a keyword that matches the debit account “travel expenses” and the item “payee” is searched from the keyword dictionary and acquired as a summary phrase candidate. The keywords obtained from the keyword dictionary, such as “□ Kyoto taxi” and “Tokyo bus”, have a value of “None” in the processing field of the keyword dictionary. Is displayed, and when "□ Kyo Taxi" is selected, "□ Kyo Taxi" is substituted for the item "Payee", and the process proceeds to the next item "Visit". The keyword dictionary is updated by adding 1 to the number of appearances of the key word displayed as a key word candidate such as “□ Kyoto taxi” or “Tokyo bus”.

In addition, 1 is added to the selected number of times of the selected “□ Kyoto taxi”, and the keyword dictionary is updated. In this embodiment, both the number of appearances and the number of selections are updated, but only the items used in the priority order may be updated.

Next, for the item “visited”, a keyword matching the debit account “travel expenses” and the item “visited” is searched from the keyword dictionary and acquired as a summary phrase candidate. The keywords obtained from the keyword dictionary, such as “Tokyo Shoji” and “Toki Shokai”, have “None” in the processing field of the keyword dictionary. When “unselected” is selected, a blank character is substituted for the item “visited”, and the process proceeds to the next item “visit reason”. The keyword dictionary is updated by adding 1 to the number of appearances of the key word displayed as a key word candidate such as “To □ Shoji” or “@ki Shokai”.

Next, for the item “reason for visit”, a keyword that matches the debit account “travel expenses” and the item “reason for visit” is retrieved from the keyword dictionary and acquired as a summary phrase candidate. The keywords obtained from the keyword dictionary, such as "around customer" and "negotiation", have a value of "none" in the processing field of the keyword dictionary. Therefore, "around customer" and "negotiation" are displayed as summary word candidates, When “advance” is selected, “customer” is assigned to the item “visit reason”, and since there is no next item, the process proceeds to S206.

The keyword dictionary is updated by adding 1 to the number of appearances of the key word displayed as a key word candidate such as “customer round” or “business negotiation”. In addition, 1 is added to the number of times of selection of the selected "around customer" (S208), and the keyword dictionary is updated. In this embodiment, both the number of appearances and the number of selections are updated, but only the items used in the priority order may be updated.

  In S206, "taxi fare 8,000 yen (blank character) □ Kyoto taxi customer rotation" is input as summary information (S209). If you are going to do text formatting, you will enter "8000 yen for the taxi fare (empty character).

According to this embodiment, it is possible for the person in charge to easily create the summary information by simply selecting the summary phrase without registering the summary information in advance or manually inputting the summary information when inputting the journal data, This has the effect of reducing the trouble of inputting journal data. Further, information relating to a transaction required for selecting an account item can be created as summary information.

Also, by repeating the selection, the accuracy of the summary word candidates is improved, and the summary word candidates can be displayed for each item as if they were linked as if they were not linked. Furthermore, by registering the created summary information and selected summary phrases, and by feeding back the registered summary information to the subject summary pattern table and keyword dictionary, it is possible to repeat the learning of summary information and summary phrases to create summary information and summary phrase candidates. The accuracy of the display can be improved, and appropriate summary information can be created and appropriate summary phrase candidates can be displayed.

In the first and second embodiments, summary information is created by selecting summary word candidates, whereas in the third embodiment, processing for automatically creating summary information will be described with reference to the flowchart of FIG.

The processing up to the display of the accounting data input screen is the same as that in S101, and thus the description is omitted. Receipts and receipts should be digitized in advance, input and displayed while displaying images, and the contents of the receipts and receipts (eg, convenience store E book fee magazine 300 yen per book) should be stored in OCR etc. in advance. The image is converted into text by the character recognition process and is associated with the image (S301).

While looking at the image of the receipt (eg, convenience store E, book fee, magazine, 300 yen per book), in the relevant transaction, date (eg, November 20), amount (eg, 300 yen), debit account (eg, newspaper) Book expenses) and credit account (eg, cash) are input (S302).

  Description patterns (eg, “Books-Magazine A-Convenience E”) and “Books” corresponding to account items (eg, debit items-newspaper book expenses, credit items-cash) entered with reference to the subject description pattern table. Magazine B-D bookstore "," newspaper fee-newspaper C-Otataro ", etc.) (S303).

  With reference to the item summary table, a debit summary type (eg, “purchase goods”), which is a summary type corresponding to the input debit account (eg, newspaper book expense), and a credit account (eg, cash) ) And the corresponding summary type (eg, “Eating and Drinking,” “Transportation,” “Purchase of Goods,” “Other Payment,” etc.) and the corresponding summary type (eg, “Purchase of Goods”) )) Is set as the debit summary type and the credit summary type. If there is more than one matching abstract type, it is displayed as a list and you can select it from the displayed list, or you can set the priority for the abstract type and automatically set the higher priority type among the matching abstract types (S304).

The abstract type is "article purchase", and the abstract item configuration ("article purchase"-"article purchase / book price / contents / article name / payee / quantity / amount") is acquired in S304 with reference to the abstract type table (step S304). S305).

  The summary pattern acquired in S303 (eg, "book fee-magazine A-convenience store E-1 book", "book fee-magazine B-D bookstore-1 book", "newspaper fee-newspaper C-convenience store E-1 copy" , Etc.), and extract a summary pattern (eg, “book cost-magazine A-convenience store E-1 book”) that matches the receipt content (eg, convenience store E book price magazine 300 yen) acquired in S301 (S306). .

  The digest pattern extracted in S306 is decomposed to obtain a digest phrase (S307), and the digest item configuration acquired in S305 (“article purchase” − “article purchase / book price / contents / article name / payee / quantity / amount”) ) Is substituted for the summary word obtained while referring to the keyword dictionary, and summary information ("purchase / book price / contents (example: magazine A) / article name (example: month)" / payee (example: convenience store E) / Quantity (eg, one book) / money (eg, money) ”) is automatically created (S308).

Since the value in the processing column of the keyword dictionary for the product name “Month” is “Date”, “November” acquired from the input date (for example, November 20) and “Month” are combined to form “11”. Month "is substituted for the item name. In addition, since the item is an amount, a description phrase of “amount” is added. Since the value in the processing column of the keyword dictionary is “amount”, the value is combined with “300 yen” obtained from the input amount (eg, 300 yen). "Amount 300 yen" may be substituted for the amount item, or "300 yen" acquired from the input amount (eg, 300 yen) may be substituted for the amount item as it is.
Therefore, the summary information (“article purchase / book fee / contents (example: magazine A) / article name (example: November issue) / payee (example: convenience store E) / quantity (example: one book) / amount (example: An amount of 300 yen) is automatically created.

If there is a summary pattern that matches the summary information (S309: Yes), 1 is added to the number of registrations of the registered matching summary pattern (S310), the subject summary pattern table is updated, and no match is found. (S309: No) is added to the subject summary pattern table (S311).

According to this embodiment, the person in charge can automatically create the summary information without registering the summary information in advance or selecting the summary phrase when inputting the journal data, thereby reducing the trouble of inputting the journal data. effective. In addition, by registering the automatically created summary information and feeding back the registered summary information and selected summary words to the subject summary pattern table and keyword dictionary, the learning of the summary information is repeated, and the accuracy of the summary information creation increases, If text can be obtained from receipts and receipt images, appropriate summary information can be created automatically.

  Further, the processing in the present embodiment may be realized by software. Then, this software may be distributed by software download or the like. Further, the software may be recorded on a recording medium such as a CD-ROM and distributed. Note that this also applies to other embodiments in this specification. The software that implements the information processing apparatus according to the present embodiment is a program as described below. That is, this program may be a program that executes the first to third embodiments and the modifications of those embodiments.

As described above, the accounting apparatus, the accounting method, and the accounting program according to the present invention are capable of registering summary information in advance without a person in charge registering summary information or selecting a summary phrase when inputting journal data. It can be automatically created, has the effect of reducing the trouble of inputting journal data, and is useful as an accounting device, an accounting method, an accounting program and the like.

DESCRIPTION OF SYMBOLS 1 Account processing apparatus 1a Server apparatus 1b Terminal 10 Control part 30 Storage part 31 Company DB
32 journal data DB
33 subject summary table 34 summary category table 35 subject summary pattern table 36 keyword dictionary 45 input section 46 display section 49 communication section

Claims (17)

An input means for receiving input of an account,
An account pattern entered as a debit and an account entered in a credit by referring to an account abstract pattern table in which the entered account is registered by associating an entered pattern with an entered pattern, which is a combination of one or more abstract words constituting the entered information. Extracting means for extracting a matching abstract pattern using the as a key,
Means for creating a summary pattern list from the extracted summary pattern,
Means having a function of registering the priority pattern list of the summary pattern list,
A first means for displaying the summary pattern obtained from the summary pattern list as a summary sentence candidate in the order of priority,
A second means for determining a summary sentence candidate selected from the displayed summary sentence candidates as a summary sentence.
A means for receiving input of an account,
An account pattern entered as a debit and an account entered in a credit by referring to an account abstract pattern table in which the entered account is registered by associating an entered pattern with an entered pattern, which is a combination of one or more abstract words constituting the entered information. Means for extracting a matching abstract pattern using the as a key,
Means for creating a summary pattern list from the extracted summary pattern,
Means having a function of registering the priority pattern list of the summary pattern list,
Refer to the keyword dictionary registered as a keyword in which the category indicating the transaction content is associated with the input account related to the description associated with the account, and decompose for each keyword from the description pattern list, and the description of each description pattern and the number of description phrases Means for obtaining
First means for displaying the acquired summary phrase as a summary phrase candidate in order of priority,
A second means for determining the summary word candidate selected from the displayed summary word candidates as a summary word,
An accounting processing device comprising: means for repeating the processing including the first means and the second means by the number of the key words of the key pattern having the highest priority based on the priority information of the key pattern. .
An accounting device according to claim 1 or claim 2,
The extraction means refers to the subject summary pattern table and extracts a matching summary pattern using at least one of a taxation classification code, a tax rate code, and a department name associated with the summary pattern as a key. Accounting processor.
The accounting device according to claim 1, wherein:
The input means further receives the input of the amount,
The accounting processing device according to claim 1, wherein the extraction means refers to the subject summary pattern table and extracts a matching summary pattern by further using the amount associated with the summary pattern as a key.
The accounting device according to claim 1, wherein:
The input means further receives the input of the amount,
The account that is the basis for the amount ratio is defined as the target account,
Obtain a ratio that is a ratio of the input amount and the total amount of the target account,
The accounting processing apparatus according to claim 1, wherein the extraction unit refers to the subject summary pattern table and extracts a matching summary pattern using the ratio associated with the summary pattern as a key.
The accounting device according to claim 1, wherein:
Means for registering journal data including at least an account item and an amount in the journal data DB,
The input means further receives the input of the amount,
Generating an amount based on a random number according to a predetermined probability distribution calculated based on the amount of all journal data included in the journal data DB;
The accounting processing device according to claim 1, wherein said extracting means extracts a matching abstract pattern by referring to said subject abstract pattern table and further using said calculated amount associated with said abstract pattern as a key.
An accounting device according to claim 1 or claim 2,
Referring to the subject summary pattern table including the assessment information for each transaction configuration parameter associated with an account for a plurality of transactions belonging to an arbitrary transaction category, the configuration of the evaluation information for each transaction configuration parameter of each summary pattern is similar Means for extracting transaction configuration information indicating the affiliation of each of the summary patterns by classifying the summary patterns with each other in a predetermined word group having the same transaction configuration,
Means for selecting the summary pattern from each of the transaction configurations based on the transaction configuration information to obtain the summary pattern that is an optimal combination of an account item, a tax classification code, and a tax rate code for the transaction. Characteristic accounting processor.
A means for receiving input of an account,
Refer to the item description table to register the transaction type and transaction status in association with the description type classified by transaction category and the entered account, and refer to the account description table registered as a key, and use the account entered in the debit as a key and the corresponding debit account Means for obtaining the abstract type;
Means for obtaining a credit summary type corresponding to the credit account by using the account entered as a key with reference to the item summary table,
Means for comparing the debit summary type and the credit summary type;
Means for extracting a descriptive summary type and a corresponding summary type from the credit summary type,
Refers to the summary type table, which registers the summary type and summary type, which are combinations of summary items that are decomposed by transaction for each keyword and summarized for each category, and registers the summary type with the extracted summary type as a key. Means for obtaining the number and the description item configuration;
Register as a keyword that associates the category indicating the transaction content with the description associated with the input account.Refer to the evaluation information for each transaction configuration parameter associated with the account for multiple transactions belonging to any transaction category in the keyword dictionary. Then, by classifying keywords having similar configurations of evaluation information for each transaction configuration parameter of each keyword into a predetermined word group having the same transaction configuration, transaction configuration information indicating the affiliation of each of the keywords is extracted. Means,
Means for selecting a keyword from each transaction configuration based on the transaction configuration information, thereby acquiring an optimal keyword for each item of the summary item configuration as a summary phrase,
First means for displaying the acquired summary phrase as a summary phrase candidate in order of priority,
A second means for determining the summary word candidate selected from the displayed summary word candidates as a summary word,
An accounting processing apparatus comprising: means for repeating the processing including the first means and the second means by the number of the summary items.
The accounting processing device according to claim 1, wherein:
Means for converting the primitive voucher indicating the transaction content into image data,
Means for extracting text information from the image data,
Means for decomposing text information as an input keyword by referring to the keyword dictionary for each keyword, and associating the determined summary phrase with the input keyword;
Means for automatically creating summary information from the determined summary words and phrases,
An accounting processing device comprising: means for associating the summary information with the image data.
An accounting device according to any one of claims 1 to 9,
Means for creating journal data including the account, tax classification code, tax rate code and the summary information from the account information and summary information created from the determined summary phrase,
Means for registering the journal data in the journal data DB.
The accounting device according to claim 10,
Means for creating journal data including the account item and the summary information,
When registering the journal data in the journal data DB, 1 is added to the number of times of selection of the corresponding abstract phrase or the corresponding abstract phrase is set as a new keyword depending on the presence or absence of the abstract phrase used in the abstract information in the keyword dictionary. The first means to register automatically,
Means for feeding back to said keyword dictionary by said first means.
The accounting device according to claim 10, wherein:
Means for creating journal data including the account item and the summary information,
When registering the journal data in the journal data DB, depending on whether the summary information is registered in the subject summary pattern table, 1 is added to the number of times of selection of the summary pattern that matches the corresponding summary information or the corresponding summary information is newly added. A first means for automatically registering as an abstract pattern,
Means for feeding back to the subject summary pattern table by the first means.
The accounting device according to claim 10, wherein:
Means for accepting input from a company performing accounting,
Means for acquiring a company code of a company entered by referring to a company DB in which company information to be processed is registered;
Means for acquiring matching journal data from the journal data DB using the acquired company code as a key,
Means for extracting a description phrase included in the description information of the journal data obtained by referring to the keyword dictionary,
Means for creating a keyword dictionary for each company based on the extracted summary words and phrases.
The accounting device according to claim 10, wherein:
Means for accepting input from a company performing accounting,
Means for acquiring a company code of a company entered by referring to a company DB in which company information to be processed is registered;
Means for acquiring matching journal data from the journal data DB using the acquired company code as a key,
Means for extracting a summary pattern that matches the summary information of the journal data obtained by referring to the subject summary pattern table,
Means for creating a summary pattern table for each company based on the extracted summary pattern.
The accounting device according to claim 10, wherein:
Means for obtaining the target date, which is the date of occurrence of the transaction to be accounted for;
Means for determining a reference period for limiting the date of occurrence of the past transaction to be referred to, based on the reference setting in which the occurrence time of the past transaction to be referred to is set and the target date and time,
Means for extracting journal data corresponding to the reference period from the journal data,
Means for creating a keyword dictionary for each company based on the extracted journal data.
The accounting device according to claim 10, wherein:
Means for obtaining the target date, which is the date of occurrence of the transaction to be accounted for;
Means for determining a reference period for limiting the date of occurrence of the past transaction to be referred to, based on the reference setting in which the occurrence time of the past transaction to be referred to is set and the target date and time,
Means for extracting journal data corresponding to the reference period from the journal data,
Means for creating a summary pattern table for each company based on the extracted journal data.
A program for causing a computer to function as the accounting device according to any one of claims 1 to 16.