KR20150097838A - Pattern generating system for account recommendation statement data generation and providing method thereof - Google Patents

Abstract

The present invention relates to a system for an account recommendation and a statement data generation using a pattern database and a providing method thereof and, more particularly, to a system for an account recommendation and a statement data generation capable of generating statement data and recommending an account corresponding to the corresponding documentary evidence by automatically processing the transaction documentary evidence like cash receipts and tax invoices. According to one aspect of the present invention, provided is the system for the account recommendation and the statement data generation using the pattern database which includes a business registration number pattern DB which stores a business registration number pattern, a word pattern DB which stores a word pattern, an extraction module, a business registration number pattern search module, a word pattern search module, a control module, and a statement data generating module which generates the statement data.

Description

[0001] The present invention relates to an account recommendation and a document creation system using a pattern database,

The present invention relates to an account recommendation and slip creation system using a pattern database, and more particularly, to a system and method for providing an account recommendation and a slip creation system using pattern databases, and more particularly, And an account recommendation and slip creation system for generating slip data.

Companies will deal with a lot of data needed for management and management of the company, such as finance, production, and inventory. Therefore, along with the recent advances in computer technology, there is an increasing tendency to introduce ERP (Enterprise Resource Planning) solution software, which is a computer system for business management and management.

The ERP solution system is a computer system for business management and management. It can be an integrated system that integrates the management resources of various management systems that are operated independently across all divisions of the company, such as personnel, finance, and production. In addition, the ERP solution monitors the flow and usage of various resources in the enterprise, collects and interprets data related to accounting, sales, and inventory management to efficiently manage management resources, As shown in FIG.

In the past, even in the case of a typical ERP solution, it provides the function of generating slip data by processing various transaction documents such as receipts and tax invoices. However, the functions provided by the conventional ERP solution include a method of providing search results to users by simply searching past accounting data or document data, a method of generating a slip by selecting the right one among the search results, When a transaction occurred and the same transaction occurred after the user set up the journal entry in advance for the frequently occurring transaction, a simple method of generating the slip data according to the set contents was main.

In the conventional document processing method, only the contents that exactly match the past data are indicated, or only a uniform process for a limited type of transaction is possible. However, the types of transactions that companies handle are very diverse and complex, and traditional document processing methods have limitations in dealing with all the evidence for such complex and diverse forms of transactions.

According to an aspect of the present invention, there is provided a system and method for processing various types of transaction data using various pattern databases generated based on past accounting transactions, To provide a system that can do this.

According to an aspect of the present invention, there is provided an account recommendation and slip creation system using a pattern database (DB), the system comprising: a business number included in past account processing details of each customer who subscribes to the pattern generation system; A business number pattern DB for storing the business number pattern of each of the customer companies including the recommendation degree of the recommendation account subject to each business number, a word included in the past accounting treatment history of each customer who joined the pattern generation system, At least one of a search target business number or a search target word from a predetermined transaction data, a word pattern DB for storing a word pattern of each of the customer companies including a recommended account subject corresponding to each word and a recommended account subject corresponding to each of the words, An extraction module for extracting the search target business number, A business card number pattern search module for searching the business card number pattern database for a predetermined course, a word pattern search module for searching the word pattern DB for a second recommended account subject corresponding to the extracted search target word, A control module for determining one of the second recommendation account classes as the account subject corresponding to the transaction data, and a slip data generation module for generating slip data including an account subject corresponding to the transaction data, An account recommendation and slip creation system using a pattern database is provided.

In one embodiment, the account recommendation and slip creation system using the pattern database may include: a business number included in the past accounting processing history of each of the customer companies subscribed to the pattern generation system, a recommended taxation type for each business number, A taxation type pattern DB storing a taxation type pattern of each of the customer companies including a recommendation level of a recommendation taxation type and a taxation type pattern search module searching for the recommendation taxation type corresponding to the search target business number from the taxation type pattern DB The control module may determine one of the recommended taxation types corresponding to the searched business entity number as the taxation type corresponding to the transaction data having the highest recommendation degree.

In one embodiment, the account recommendation and slip creation system using the pattern database may further include: a business number included in the past accounting processing details of each of the customer companies subscribed to the pattern generation system, a recommendation disagreement by each business number, An unproved pattern DB for storing a non-contingent pattern of each of the customer companies including a recommendation degree of a non-recommended non-contingent, a non-contingent pattern search module for searching a non-contingent pattern DB corresponding to the search target business number from the non- The control module may determine one of the recommendation disagreements corresponding to the searched business entity number as the disadvantage corresponding to the transaction data.

In one embodiment, the account recommendation and document creation system using the pattern database may include a recommendation cost security account and a recommendation cost security account corresponding to each account item related to the cost or expense of each of the customer companies subscribed to the pattern generation system, Cost cost group pattern DB for storing the cost cost group pattern of the customer including the degree of recommendation of the customer, a cost expense group pattern DB for storing the cost cost group pattern of the customer, And a cost cost group pattern retrieval module for retrieving a recommended cost cost account corresponding to an account subject to the account category, wherein the control module calculates a recommendation cost of the recommended cost expense account corresponding to the account subject corresponding to the retrieved transaction data The largest one can be determined as a cost expense account corresponding to the transaction data.

In one embodiment, the account recommendation and slip creation system using the pattern database may include a plurality of debit account subjects of each of the customer companies subscribed to the pattern generation system, a recommendation credit account subject to each debit account subject, A settlement account pattern DB for storing the settlement account pattern of the customer including recommendation credits of the recommended credit account subject for the course, a recommended credit account subject corresponding to the account subject corresponding to the transaction data in the settlement account pattern DB Wherein the control module further includes a settlement account pattern matching module for selecting one of the recommendation credit account classes corresponding to the account category corresponding to the retrieved transaction data, .

In one embodiment, the account recommendation and slip creation system using the pattern database includes a recommendation account for each account number, recommendation accounts for each account number, and recommendation accounts for each account number A public service number pattern DB for storing a business number pattern and a word included in the past accounting treatment history, a recommended account subject corresponding to each of the above-mentioned words, and a common word pattern including a recommendation level of a recommended account subject corresponding to each of the above- The business number pattern search module may further include a common word pattern database for storing a common business word number corresponding to the search target business number if the transaction data is the data of a new customer , The first recommended account subject corresponding to the search target business number is registered in the public service number pattern And if the transaction data is the data of the new customer, the word pattern search module searches the database for a word corresponding to the search target word, The second recommended account subject can be searched from the common word pattern DB.

In an exemplary embodiment, the account recommendation and slip creation system using the pattern database may include: a bankbook transaction related word included in past account transaction details of each customer who joined the pattern generation system, a recommendation corresponding to each bankbook transaction related word, A passbook transaction related word pattern DB storing the passbook transaction related word pattern of each of the customer companies including the recommendation degree of the recommended account subject corresponding to each account subject and the passbook transaction related word, Related banknote transaction related word pattern including a related word, a recommended account subject corresponding to each of the public account transaction related words, and a recommendation account of a recommended account subject corresponding to each of the public account transaction related words Pattern DB, and if the transaction data is data related to a bank account transaction, Searches for a recommended account subject in the bankbook transaction related word pattern database, and if it is not possible to retrieve a recommended account subject corresponding to the search target word from the bankbook transaction related word pattern DB, or if the transaction data is data of a new customer, And a banknote transaction related word pattern retrieval module for retrieving a recommended account subject corresponding to the target word from the public service number pattern database, wherein the control module determines whether the recommended recommendation account corresponding to the searched target word The largest one can be determined as an account subject corresponding to the transaction data.

In one embodiment, the account recommendation and slip creation system using the pattern database may include scrapping at least one of electronic tax invoice data, electronic statement data, credit card transaction history data, cash receipt data, and bank account transaction data from a predetermined website And at least one of a scrapping module for generating the transaction data or an image recognition module for recognizing at least one of a tax bill, a credit card transaction history, a cash receipt, and a passbook to generate the transaction data.

According to another aspect of the present invention, there is provided a method of providing an account recommendation and a slip creation system using a pattern database, the method comprising the steps of: Storing a business number pattern of each of the customer companies including recommendation levels of recommended account subjects for each business number in a business number pattern database; Storing, in a word pattern DB, a word pattern of each of the customer companies including a recommended account subject corresponding to each of the words and a recommended account subject corresponding to each of the words, Extracting at least one of the words, the extracted search target business number Searching for a corresponding first recommended account subject in the business entity number pattern DB, searching a second recommendation account subject corresponding to the extracted search target word in the word pattern DB, Determining one of the second recommendation account courses having the largest recommendation degree as an account subject corresponding to the transaction data, and generating slip data including an account subject corresponding to the transaction data; A method of providing an account recommendation and document creation system is provided.

In one embodiment, a method of providing an account recommendation and a document creation system using the pattern database may include: identifying a business number included in the past accounting processing history of each of the customer companies subscribed to the pattern generation system, a recommended taxation type for each business number, Storing the taxation type pattern of each of the customer companies including the recommendation level of the recommended taxation type per business number in the taxation pattern DB, searching the taxation pattern DB corresponding to the search target business number, And determining one of the recommended taxation types corresponding to the searched business number as the taxation type corresponding to the transaction data.

In one embodiment, a method for providing an account recommendation and a slip creation system using the pattern database may include: identifying a provider number included in the past accounting processing history of each of the customer companies subscribed to the pattern generation system, Storing in the nonproblematic pattern database each of the nonproblematic patterns of the customers including the recommendation degree of the nonprovisional cause by the business number, searching the nonprofit pattern DB corresponding to the search target business number from the nonprofit pattern DB And determining that one of the recommendation disagreements corresponding to the searched business entity number is the unproblematic corresponding to the transaction data.

In one embodiment, a method for providing an account recommendation and a document creation system using the pattern database may include: a recommendation cost security account corresponding to each account item associated with a cost or an expense of each of the customer companies subscribed to the pattern generation system; Saving the cost cost group pattern of the customer including the recommendation degree of the expense account in the cost expense group pattern DB, if the account subject corresponding to the transaction data is related to cost or expense, Searching for a recommended cost expense account corresponding to the account subject corresponding to the transaction data, and a recommendation cost expense account corresponding to the account subject corresponding to the retrieved transaction data, And a step of determining the cost account.

In one embodiment, the method for providing an account recommendation and a slip creation system using the pattern database includes a plurality of debit account subjects of each of the customers who have joined the pattern generation system, a recommendation credit account subject to each debit account subject, Storing a billing account pattern of the customer including a recommendation credit account subject for a debit account subject in a settlement account pattern DB, a recommendation counterpart corresponding to an account subject corresponding to the transaction data in the settlement account pattern DB, The step of retrieving the account subject and the step of determining one of the recommendation credit account subjects corresponding to the account subject corresponding to the retrieved transaction data as the credit account subject corresponding to the transaction data, have.

In one embodiment, the method for providing account recommendation and slip creation system using the pattern database includes recommendation scores of the account numbers included in the past account processing history, the recommended account accounts for each account number, and the recommended accounts for each account number Storing a common business operator number pattern in a common business operator number pattern DB, a word included in the past account processing history, a recommended account item corresponding to each of the words, and a recommended recommendation account corresponding to each of the words Storing the common word pattern in the common word pattern DB; if the requested account subject corresponding to the search target business number is not retrieved from the business number pattern database or the transaction data is data of a new customer, Retrieving the first recommended account subject corresponding to the common service number pattern DB from the public service number pattern DB; The second recommendation account corresponding to the search target word may be stored in the common word pattern database if it is not possible to retrieve the recommended account subject corresponding to the search target word from the first word pattern database or if the transaction data is data of a new customer, And a search step of searching for a search query.

In one embodiment, a method for providing an account recommendation and a slip creation system using the pattern database may include: matching a passbook transaction related word included in the past accounting processing history of each customer who joined the pattern generation system, Storing a word transaction related word pattern of each of the customer companies in a passbook transaction related word pattern DB including a recommendation account subject corresponding to each of the recommended account subjects corresponding to the account transaction related words and a recommendation account corresponding to each of the recommended account subjects corresponding to the passbook transaction related words, Related public banking transaction related words, a recommended account item corresponding to each of the public banking transaction related words, and a recommendation account corresponding to each of the public banking transaction related words, Storing in a related word pattern DB, when the transaction data is data relating to a bank account transaction, Searching for a recommended account subject corresponding to a search target word from the passbook transaction related word pattern DB, searching for a recommended account subject corresponding to the search target word from the bankbook transaction related word pattern DB, Searching for a recommended account subject corresponding to the search target word in the common service provider number pattern DB, and a step of selecting one of the recommended account subjects corresponding to the searched search target word, And a step of determining an account subject to be made.

In one embodiment, the method for providing account recommendation and slip creation system using the pattern database may include providing at least one of electronic tax invoice data, electronic statement data, credit card transaction history data, cash receipt data, and bank account transaction data from a predetermined website Generating at least one of a tax bill, a credit card transaction history, a cash receipt, and a bankbook, and generating the transaction data by scraping the transaction data.

According to another aspect of the present invention, there is provided a computer-readable recording medium on which a program for performing the above-described method is recorded.

According to another aspect of the present invention, there is provided an account recommendation and slip creation system using a pattern database, the system including a processor and a memory in which a program is stored, wherein the program, when executed by the processor, An account recommendation and slip creation system using a pattern database for performing a method is provided.

According to an embodiment of the present invention, it is possible to provide a system capable of processing documentary evidence for various types of transactions and automatically generating document data using various pattern databases generated based on historical accounting processing details have.

BRIEF DESCRIPTION OF THE DRAWINGS A brief description of each drawing is provided to more fully understand the drawings recited in the description of the invention.
1 is a diagram showing a schematic configuration of an automatic document processing system according to an embodiment of the present invention.
FIG. 2 is a schematic diagram of a pattern generation system for generating a slip and an account recommendation system according to an embodiment of the present invention, and a pattern DB generated by the pattern generation system.
FIG. 3 is a schematic block diagram of an account recommendation and slip creation system according to an embodiment of the present invention. Referring to FIG.
4A to 4D are diagrams for explaining a method of generating slip data according to an embodiment of the present invention.

BRIEF DESCRIPTION OF THE DRAWINGS The present invention is capable of various modifications and various embodiments, and specific embodiments are illustrated in the drawings and described in detail in the detailed description. It is to be understood, however, that the invention is not to be limited to the specific embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS Hereinafter, the present invention will be described in detail with reference to the accompanying drawings.

The terms first, second, etc. may be used to describe various components, but the components should not be limited by the terms. The terms are used only for the purpose of distinguishing one component from another.

The terminology used in this application is used only to describe a specific embodiment and is not intended to limit the invention. The singular expressions include plural expressions unless the context clearly dictates otherwise.

In this specification, the terms "comprises" or "having" and the like refer to the presence of stated features, integers, steps, operations, elements, components, or combinations thereof, But do not preclude the presence or addition of features, numbers, steps, operations, components, parts, or combinations thereof.

Also, in this specification, when any one element 'transmits' data to another element, the element may transmit the data directly to the other element, or may be transmitted through at least one other element And may transmit the data to the other component. Conversely, when one element 'directly transmits' data to another element, it means that the data is transmitted to the other element without passing through another element in the element.

Hereinafter, the present invention will be described in detail with reference to the embodiments of the present invention with reference to the accompanying drawings. Like reference symbols in the drawings denote like elements.

1 is a diagram showing a schematic configuration of an automatic document processing system according to an embodiment of the present invention. The automated journal processing system shown in FIG. 1 generates various journalism patterns based on past accounting processing details, and automatically generates a journal by processing transaction evidence data generated by various transactions based on the generated journal entry pattern System.

The automated document processing system may include a pattern generation system 100, a pattern DB 200, and an account recommendation and document generation system 300.

The pattern generation system 100 may be a system for generating various patterns from a past accounting processing history stored in a predetermined accounting processing DB 10. [

The accounting processing history DB 10 may store accounting data of a past period (for example, five years). The accounting transaction history DB 10 can be generated by classifying and extracting certain types of data necessary for implementing the technical idea of the present invention among historical data processed or generated in various accounting programs.

The past accounting treatment history data stored in the above-mentioned accounting process data includes the date of creation of the document, the transaction classification, the purchase revenue classification, the credit classification, the account subject name, the business number of the business, the business name, the name of the business, Business type, representative name of the business, type of tax, disqualification, date of transaction, and so on.

The creation date of the document may be the date on which the document corresponding to the accounting history data was created. Transactions can be classified as e-tax invoice purchase / sales, tax invoice purchase / sales, credit card purchase / sales, cash receipt purchase / sales, bank book receipt / deposit. The purchase sales breakdown may be a breakdown of whether the accounting history data is purchases or sales. The types of taxation can be taxation, exemption, permanent, etc., and can be subdivided into a card or cash. The credit struc- ture classification may be a breakdown of the accounting treatment data for debit or spoof. Account subject names can be, for example, assets, liabilities, capital, revenues, costs, and so on. The brief may be an item that the user has written about the transaction. The transaction date can refer to the supply period of goods or services.

The pattern generation system 100 may analyze the past accounting process data configured as described above and generate pattern data having a predetermined format to configure the pattern DB 200.

The account recommendation and document creation system 300 collects transaction proofs such as electronic tax invoice, electronic bill, credit card receipt, cash receipt and bankbook from the website 20, After the image is photographed, the image is analyzed and an account corresponding to the corresponding document is recommended using the pattern DB 200, and a slip is generated.

In one embodiment, the automated document processing system may be operatively associated with a given ERP solution system (not shown). According to an embodiment, the pattern generation system 100 may be included in the ERP solution system. In this case, the pattern generation system 100 may be in the form of hardware or software, or a combination thereof, included in the ERP solution system. On the other hand, the ERP solution system to which the technical idea of the present invention is applied is a computer system for business management and management, and it manages various management systems that are operated independently in all sectors of the company such as personnel, finance, It can be an integrated system that integrates resources. In addition, the ERP solution monitors the flow and usage of various resources in the enterprise, collects and interprets data related to accounting, sales, and inventory management to efficiently manage management resources, As shown in FIG.

2 illustrates a schematic configuration of a pattern generation system for generating a slip and an account recommendation (hereinafter referred to as a 'pattern generation system') and a pattern DB generated by the pattern generation system according to an embodiment of the present invention FIG.

Referring to FIG. 2, the pattern generating system 100 includes a data refining module 120, a recommendation degree calculating module 130, a business entity number pattern generating module 101, a word pattern generating module 102, Module 103, a nonprofit pattern generation module 104, a common service provider number pattern generation module 105, a common word pattern generation module 106, a cost cost group pattern generation module 107, a billing account pattern generation module 108 A business word pattern generation module 110, a bankbook transaction related word pattern generation module 111, a common bankbook transaction related word pattern generation module 112, a machine learning pattern generation module 113 ). According to an embodiment of the present invention, some of the above-described components may not necessarily correspond to components necessary for implementing the present invention, and the pattern generation system 100 may further include, It goes without saying that more components may be included. For example, the pattern generation system 100 may include other components included in the pattern generation system 100 (e.g., a data refining module 120, a recommendation degree calculation module 130, a business entity number pattern generation module 101, A word pattern generation module 102, a taxation type pattern generation module 103, a nonprofit pattern generation module 104, a common business entity number pattern generation module 105, a common word pattern generation module 106, A business word pattern generation module 110, a passbook transaction-related word pattern generation module 111, a common bank transaction-related word pattern generation module 107, a payment account pattern generation module 108, (Not shown) that can control the functions and / or resources of the machine learning pattern generation module 112, the machine learning pattern generation module 113, and the like.

The business entity number pattern generation module 101 may generate a business entity number pattern and store the business entity number pattern in the business entity number pattern DB 201. The word pattern generation module 102 generates a word pattern to generate a word pattern DB 202, And the taxation type pattern generation module 103 may generate the taxation type pattern and store the taxation type pattern in the taxation type pattern DB 203. The nonproportionation pattern generation module 104 generates a nonprofit pattern, The public company number pattern generation module 105 can generate the public company number pattern and store it in the public company number pattern DB 205. The common word pattern generation module 106 can store the common company number pattern in the public company number pattern DB 205, Pattern can be generated and stored in the common word pattern DB 206. [ Meanwhile, the cost cost group pattern generation module 107 may generate the cost cost group pattern and store the cost cost group pattern in the cost cost group pattern 207. The billing account pattern generation module 108 generates a billing account pattern, (208). The business type business entity pattern generation module 109 generates business type business entity patterns and stores them in the business type business entity pattern database 209. The business type word pattern generation module 110 generates business type word patterns and stores them in the business type word pattern DB 210 Can be stored. The bankbook transaction related word pattern generation module 111 may generate the bankbook transaction related word pattern and store it in the bankbook transaction related word pattern DB 211 and the common bankbook transaction related word pattern generation module 112 may generate the common bankbook transaction related word pattern Pattern can be generated and stored in the common banknote transaction related word pattern DB 212. The machine learning pattern generation module 113 can generate a machine learning pattern and store it in the machine learning pattern DB 213. [

In this specification, a DB (DataBase) may be implemented by at least one table, and may further include a separate DBMS (Database Management System) for searching, storing, and managing information stored in the DB It is possible. In addition, it can be implemented in various ways such as a linked-list, a tree, and a relational DB, and includes all data storage media and data structures capable of storing information to be stored in each pattern DB Can be used as a meaning.

The pattern generation system 100 may include hardware resources and / or software necessary for implementing the technical idea of the present invention, and it is understood that the pattern generation system 100 necessarily means one physical component or one device no. That is, the pattern generation system 100 may mean a logical combination of hardware and / or software provided to implement the technical idea of the present invention. If necessary, the pattern generation system 100 may be installed in a separate apparatus, The present invention may be embodied as a set of logical structures for realizing the technical idea of the present invention. In addition, the pattern generation system 100 may mean a set of structures separately implemented for each function or role for implementing the technical idea of the present invention. For example, the data editing module 120, the recommendation degree calculation module 130, the business entity number pattern generation module 101, the word pattern generation module 102, the taxation type pattern generation module 103, Module 104, a public company number pattern generation module 105, a common word pattern generation module 106, a cost cost group pattern generation module 107, a billing account pattern generation module 108, a business entity pattern generation module 109 ), The business type word pattern generation module 110, the bankbook transaction related word pattern generation module 111, the common account transaction related word pattern generation module 112, and the machine learning pattern generation module 113 are located in different physical devices Or may be located in the same physical device. According to an embodiment of the present invention, the data editing module 120, the recommendation degree calculation module 130, the business entity number pattern generation module 101, the word pattern generation module 102, the taxation type pattern generation module 103, A common company name pattern generation module 105, a common word pattern generation module 106, a cost cost group pattern generation module 107, a billing account pattern generation module 108, Module 109, a business type word pattern generation module 110, a bankbook transaction related word pattern generation module 111, a common bankbook transaction related word pattern generation module 112, and a machine learning pattern generation module 113, The detailed configurations to be configured may also be located in different physical devices, and detailed configurations located in different physical devices may be combined with each other to realize functions performed by the respective modules.

In this specification, a module may mean a functional and structural combination of hardware for carrying out the technical idea of the present invention and software for driving the hardware. For example, the module may mean a logical unit of a predetermined code and a hardware resource for executing the predetermined code, and it does not necessarily mean a physically connected code or a kind of hardware. It can easily be deduced to a technician.

The data refining module 120 can generate the refinement data by applying a predetermined replacement rule to the past accounting processing history data stored in the predetermined accounting processing DB 10.

(For example, a long number or a special character) is included in at least a part of the past accounting processing history data (for example, a business name, a product name, a brief, a representative, etc.) The data refinement module 120 can remove unnecessary information and perform operations to leave only meaningful keywords.

Table 1 below shows an example of the substitution rule.

Substitution target Substitution result Phone number Area code + 3 digits + 4 digits Phone number Mobile phone identification number 3 digits + 4 digits + 4 digits Cell Phone Number Special Characters ~! @ # $% ^ & * ();: '- = _ + etc. (remove) account (Stock), stocks, stocks (stocks, stocks, stocks, etc.) (remove) Quantity history [0-9] + [month] [day] [minute] [tea] etc. (remove) [0-9] + [Kg] [kg] [L] [Tone] [Name] [In] [Two] [Circle] [Volume] [Tea] etc. (remove) Long number Any number greater than 15 digits (remove)

For example, according to the above replacement rule, the data refining module 120 can replace Samsung Corporation with Samsung Corporation and 35Kg with copper.

The substitution rules shown in Table 1 are merely examples. For example, the substitution rule for eliminating '(foundation)' to indicate a cut, the rule for replacing 'November salary' or 'salary 3' with 'salary' As shown in FIG.

In particular, as shown in the quantity part of the above table, when the data to be replaced includes the replacement subject character string corresponding to the replacement subject regular expression in the past accounting processing history data, the data refining module 120 updates the replacement subject regular expression The substitution result corresponding to the expression can be replaced with the replacement string represented by the regular expression.

The recommendation degree calculating module 130 calculates the frequency of each individual data item included in the refinement data, and based on the calculated frequency of each unit period and the predetermined weight of the unit period, Can be calculated.

In one embodiment, the individual data item may be each field constituting the accounting transaction history DB 10, but may be a more detailed item. In the latter case, the individual data items may be account subjects by business number, account subjects by word, taxation type by business number, unfair reasons by business number, cost cost account by account subject, credit account subject by debit account subject, and the like.

The unit period may be a period having a constant period such as a month or a year.

For example, if the unit period is a month, the recommendation degree calculating module 130 calculates the recommendation degree of each individual data item by using the recommendation degree = Σ (the frequency of each individual data item month) ㅧ (the weight of the corresponding month) Can be calculated.

On the other hand, since a recent transaction reflects a relatively accurate situation, the weight of the unit period may be set to a higher value as the unit period is more recent. That is, the weight of the unit period may be set to the highest value in the case of the month closest to the present, and may be set to a gradually lower value as the distance from the present is farther away.

On the other hand, the business number pattern generation module 101 analyzes the past accounting processing details based on the business number, and analyzes which account category the specific business number is processed. That is, the business entity number pattern generation module 101 can generate a business entity number pattern for each customer who is subscribed to the pattern generation system. That is, the business entity number pattern generation module 101 generates, for each of the customers who have subscribed to the pattern generation system, the business entity number, the business entity number, and the business entity number included in the past accounting processing based on the refinement data corresponding to the customer, It is possible to generate the business number pattern of the customer including the recommendation account class by the business number and the recommendation degree of the recommended account class by each business number.

Meanwhile, in one embodiment, the business entity number pattern generation module 101 may analyze the past financial transaction details according to the business entity number, the purchase / sales classification, the business entity number, and the transaction category. For example, when a merchandise sales number is generated for a merchant A, it can be corresponded to a foreign trade receipt. If a merchandise merchandise number is generated for a merchant A, it can be matched to the accounts payable.

The business entity number pattern generation module 101 may generate a business entity number pattern for each customer who subscribes to the automatic document processing system or the pattern generation system 100 according to an embodiment of the present invention.

According to the embodiment, the business number pattern may further include various information besides the business number and the account subject information corresponding to the business number.

On the other hand, even if the accounts are the same, there may be cases in which different accounts are accounted for according to the contents of the transactions. Therefore, there may be a case where a plurality of account subjects corresponding to one business number are included. In this case, it is needless to say that the recommendation degree for each account subject corresponding to one business number may be different from each other.

Table 2 below shows an example of a column constituting a business number pattern.

Column name Column Description Pattern Deal Classification Electronic Tax Invoice Purchase / Sales, Tax Invoice Purchase / Sales, Credit Card Purchase / Sales, Cash Receipt Purchase / Sales, Passbook Deposit / Deposit Purchase Sales Category Purchase, sales division Car stool division Debit, Credit Category Business Partner Number Business number of customer -Key value Account code The code of the account used for the transaction Price Transaction amount Count The number of account codes used based on the business number Recommendations Recommendations for each account code used based on the business number Last transaction date Date last traded Generation time The time the pattern was created

On the other hand, there may be cases where a transaction without a business number occurs. To this end, the word pattern generation module 102 extracts words from fields such as a business name, brief, product name, and representative name that can serve as a basis for a transaction pattern, and determines which account subject is processed Can be analyzed. That is, the word pattern generation module 102 generates, for each of the customer companies subscribed to the pattern generation system, the tabular data corresponding to the customer in the tabular data (preferably, the name of the supplier included in the tabular data, , Product name, representative name), and generates the word pattern of the customer including the extracted word and the recommended account subject corresponding to each of the words.

For example, the word pattern generation module 102 may analyze the past accounting processing history to correspond to a communication fee account in case of a transaction including words such as a telephone charge, a mobile phone charge, an international call charge, and an Internet charge, For transactions involving words such as salary, bonus or bonus, it can correspond to the personnel account subject.

The word pattern generation module 102 may generate a word pattern differently for each customer who subscribes to the automatic document processing system or pattern generation system 100 according to an embodiment of the present invention.

According to an embodiment, the business number pattern may further include various information besides the word and the account subject information corresponding to the word.

On the other hand, even if the words are the same, there may be cases in which different accounts are accounted according to transaction contents, so there may be a case where a plurality of account subjects corresponding to one word are included. In this case, it is needless to say that the recommendation degree for each account subject corresponding to one word can be different from each other.

Table 3 below shows an example of a column constituting a word pattern.

Column name Column Description Pattern Deal Classification Electronic Tax Invoice Purchase / Sales, Tax Invoice Purchase / Sales, Credit Card Purchase / Sales, Cash Receipt Purchase / Sales, Passbook Deposit / Deposit Purchase Sales Category Purchase, sales division Car stool division Debit, Credit Category word Word-Key value Account code The code of the account used for the transaction Price Transaction amount Count The number of account codes used based on that word Recommendations Recommendations for each account code used based on that word Last transaction date Date last traded Generation time The time the pattern was created

The taxation type pattern generation module 103 can generate a taxation type pattern by analyzing the taxation type according to the business number of the business partner in the case of a tax bill, a credit card, or a cash receipt purchase. That is, the taxation type pattern generation module 103 generates, for each of the customer companies subscribed to the pattern generation system, the business entity number, the business entity number, and the business entity number included in the past accounting processing based on the refinement data corresponding to the customer, The taxation type pattern of the customer including the recommended taxation type for each business number and the recommendation type of the recommended taxation type for each business number can be generated.

The taxation type may include at least one of card tax, card exemption, card tax, cash tax, cash tax, cash exemption, or cash.

Meanwhile, in one embodiment, the taxation type pattern generation module 103 may analyze past accounting processing details by business number, purchase / sales classification, business number, and transaction category.

The taxation type pattern generation module 103 may generate taxation type patterns differently for each company subscribing to the automatic document processing system or pattern generation system 100 according to an embodiment of the present invention.

According to an embodiment, the taxation type pattern may further include various information besides the taxation type corresponding to the business number and the corresponding business number.

On the other hand, even if the accounts are the same, accounting may be carried out on different accounts depending on the contents of the transactions. Therefore, there may be a case where a plurality of taxation types corresponding to one business number are involved. In this case, it is needless to say that the recommendation degree for each taxation type corresponding to one business number may be different from each other.

Table 4 below shows an example of the columns that make up the taxation type pattern.

Column name Column Description Pattern Deal Classification Electronic Tax Invoice Purchase / Sales, Tax Invoice Purchase / Sales, Credit Card Purchase / Sales, Cash Receipt Purchase / Sales, Passbook Deposit / Deposit Purchase Sales Category Purchase, sales division Car stool division Debit, Credit Category Business Partner Number Business number of customer -Key value Taxation type Taxation type such as taxation, duty free, permanent Count The number of account codes used based on the business number Recommendations Recommendations for each account code used based on the business number Last transaction date Date last traded Generation time The time the pattern was created

On the other hand, when a VAT declaration is made, a reason for not deducting the purchase tax amount is referred to as a construction contract, and the nonprofit pattern generation module 104 may generate a pattern for the unproblematic. That is, for each of the customer companies subscribed to the pattern generation system, based on the refinement data corresponding to the customer in the refinement data, the company number included in the past accounting process, the non-recommendation for each business number, It is possible to generate the non-proscribed pattern of the customer including the recommendation degree of the non-recommended recommendation by number.

For example, the unfairness pattern generation module 104 may correspond to the non-compliance of 'equipment (tangible asset purchase)' in the case of the purchase tax for expenditure not directly related to the business, The amount of the purchase tax on expenditure can be countered by the non-discretion of 'entertainment expenses'. In this manner, the unproved pattern generation module 104 can generate a non-proactive pattern by analyzing the accounts used for the reason for non-deduction and the recommendation degree thereof.

On the other hand, in the case of a customer having a business purpose such as manufacturing or construction, since the detailed cost account such as the manufacturing cost, the contract cost, and the sales management cost is used, in order to improve the accuracy of account recommendation and avoid confusion, The generation module 107 can analyze various cost security accounts that are mixed and classified into manufacturing costs, contract costs, and SG & A expenses. That is, the cost expense group pattern generation module calculates, for each of the customer companies subscribed to the pattern generation system 100, the account data related to the cost or expense based on the refinement data corresponding to the customer in the refinement data The cost cost group pattern of the customer including the recommendation cost of the recommendation cost account and the recommendation degree of each recommendation cost expense account can be generated. The recommended cost expense account may include at least one of manufacturing, contracting, and sales management.

For example, the cost cost group pattern generation module 107 generates the cost cost group pattern generation module 107, such as manufacture (recommendation level 10), contract level (recommendation level 10), and sales management (recommend level level 80) You can generate a costing pattern.

Meanwhile, in one embodiment, the cost expense group pattern generation module 107 may analyze the past accounting treatment according to account subjects and transaction categories related to account costs and purchase / sales division or cost expense related to cost expense.

Also, according to an embodiment, the cost guard group pattern may further include various information besides the recommended cost security account corresponding to each account subject to cost or expense.

On the other hand, a billing account may show a certain pattern. For example, most stock purchases for business purposes are accounted for as accounts payable, and credit card purchases are transferred to a bank account (ordinary deposit). Accordingly, the billing account pattern generation module 108 can form a pattern by analyzing which accounts are accounted by which account items for each customer. That is, the billing account pattern generation module 108 generates, for each of the customer subscribing to the pattern generation system, a plurality of debit account items, payment of each debit account item based on the tabular data corresponding to the customer, You can create a billing account pattern that includes a recommendation credit account subject to account and a recommendation rating for each credit account subject.

For example, if the debit is an inventory asset, the billing account pattern generation module 108 may form a pattern by making a corresponding settlement account correspond to 'debit account', and in the case of vehicle maintenance expenses, A pattern can be formed corresponding to the billing account.

The billing account pattern generation module 108 may generate taxation type patterns differently for each company subscribing to the automatic bill processing system or the pattern generation system 100 according to an embodiment of the present invention.

On the other hand, even if the accounts are the same, there may be cases where the accounts are accounted for by different billing accounts depending on the contents of the transactions. Therefore, there may be a case in which there are plural depts corresponding to one debit account subject. In this case, it is needless to say that the degree of recommendation for each of the debit account subjects corresponding to one debit account subject may be different from each other.

The business type company pattern generation module 109 can classify the business entity number pattern generated by the business entity pattern generation module 101 according to the business type and generate a detailed pattern, The word processor 110 may analyze the word patterns generated by the word pattern generation module 102 according to the type of industry and generate a detailed pattern.

On the other hand, in the case of a bankbook transaction, a business number can not be described because of its nature, and therefore it is necessary to generate a pattern using only the words described in the brief or the like.

Therefore, the passbook transaction-related word pattern generation module 111 extracts bankbook transaction-related words from the bankbook transaction-related refinement data corresponding to the client company among the refinement data for each of the customer companies subscribing to the pattern generation system, It is possible to generate the bank account transaction related word pattern including the recommendation account corresponding to the passbook transaction related words, the recommended account subject corresponding to each bankbook transaction related word, and the recommended account subject corresponding to each bankbook transaction related word .

However, since there may be a case where a plurality of accounts are mixed in an account which can clarify account processing based on a specific passbook-related word and one account-related word, it is possible to distinguish the words, Words that can be processed by multiple accounts can be separated into non-deterministic patterns. That is, when the passbook transaction-related word pattern generation module 111 maps a specific passbook-related word and two or more account subjects, the pattern for the specific passbook-related word may be an undetermined pattern, The pattern for the specific passbook-related word may be a definite pattern. For example, if the word 'phone charge' is mapped to a 'communication fee' account, this pattern can be a definite pattern, and the word 'meals' is mapped to a 'benefit' account and a 'entertainment fee' account. This pattern may be an undetermined pattern.

The passbook transaction related word pattern generation module 111 may generate taxation type patterns differently for each company subscribing to the automatic document processing system or pattern generation system 100 according to an embodiment of the present invention.

On the other hand, the public account transaction-related word pattern generation module 112 analyzes the briefs and the like in the account transactions for all the customer companies, and extracts the words, and then analyzes the account subject processed for each word. In particular, the common account transaction related word pattern generation module 112 can generate patterns by selecting words having high accuracy (recommendation degree) from the generalized accounts applicable to all companies. That is, the common bank transaction related word pattern generation module 112 extracts common bank transaction related words from the refinement data related to bank account transactions among the refinement data, and extracts the common bank transaction related words, the common bank transaction related words A common account transaction related word pattern including the recommendation account corresponding to each of the public account transaction related words and the recommendation account corresponding to each of the public account transaction related words can be generated.

Meanwhile, the machine learning module 113 may extract a word from the purified data, and perform a machine learning on the extracted word to generate a machine learning pattern.

The machine learning module 113 can generate a formal pattern by performing machine learning with various words included in the name, brief, name, and representative name included in the past accounting processing history as key values.

In one embodiment, the machine learning module 113 may generate the machine learning pattern by applying a machine learning method such as SVM (Support Vector Machine) or ME (Maximum Entropy).

In particular, machine learning patterns generate machine learning patterns that are verified for accuracy and reliability, so they can be applied to any customer and can be used for new customers.

Meanwhile, the common service provider number pattern generation module 105 may generate a common service provider number pattern by analyzing the service provider numbers of all customer service providers. The generated common service provider number pattern may include existing account transaction details such as new customer service providers It can be utilized by customers who do not. That is, the common service provider number pattern generation module 105 includes reference numbers of the business number included in the past accounting process, recommended account classes for each business number, and recommendation accounts for each business number based on the refinement data A common carrier number pattern can be generated.

Meanwhile, the common word pattern generation module 106 extracts words by analyzing various words included in the name, brief, name, and representative name included in the past accounting processing details for all the customer companies, You can analyze the account subjects that are handled differently. That is, the common word pattern generation module 106 extracts a word from the purified data, and includes the extracted word, a recommended account subject corresponding to each of the words, and a recommendation degree of a recommended account subject corresponding to each of the words A common word pattern can be generated.

Also, the common word pattern generation module 106 may map frequently used special words and account subjects. For example, a vehicle manufacturer (e.g., Hyundai, Kia, etc.), the name and brand of a transportation company can be mapped to a 'buy vehicle' account item as a key value.

Various patterns stored in the pattern DB 200 can be generated by the method described above.

Therefore, the business number pattern DB 201 stores the business number included in the past accounting processing details of each customer who joined the pattern generation system, the recommended account item for each business number, and the recommendation degree of the recommended account item for each business number And the word pattern DB 202 may store a word included in the past accounting processing history of each customer who subscribed to the pattern generation system, a recommendation account corresponding to each of the words And a recommendation account corresponding to each of the words may be stored.

The taxation type pattern DB 203 includes a recommendation level of the reference number of the recommended taxation type for each business number and the reference number of taxation type for each business number and the business number included in the past accounting processing details of each customer who joined the pattern generation system The taxation type pattern of each of the customer companies.

The nonprofit pattern DB 204 includes a recommendation of the business number included in the past accounting processing history of each of the customers who subscribed to the pattern generation system, the non-recommendation by each business number, and the recommendation of non-recommendation by each business number Unacceptable patterns of each of the customer companies.

The common business entity number pattern DB 205 may store a common business entity number pattern including a business entity number included in the past accounting transaction details, a recommended account item for each business number, and a recommendation degree of a recommended account item for each business number.

The common word pattern DB 206 may store a word included in the past accounting processing history, a recommended account subject corresponding to each of the words, and a common word pattern including a recommendation degree of a recommended account subject corresponding to each of the words .

The cost cost group pattern DB 207 stores a cost cost account corresponding to each account item associated with the cost or expense of each of the customer companies subscribed to the pattern generation system, The cost group pattern of the cost can be stored.

The settlement account pattern DB 208 includes a plurality of debit account subjects of each customer who joined the pattern generation system, a recommendation credit account subject to each debit account subject and a recommendation credit account subject to each debit account subject The billing account pattern of the client company including the billing account pattern can be stored.

The business type company pattern DB 209 may store the business type business pattern described above, and the business type word pattern DB 210 may store the business type word pattern described above.

The bankbook transaction-related word pattern DB 211 includes a bankbook transaction related word included in the past account transaction details of each customer who joined the pattern generation system, a recommended account item corresponding to each bankbook transaction related word, Related word pattern database 212 including a recommendation level of a recommendation account corresponding to each word, and the common banknote transaction related word pattern DB 212 may store a common banknote transaction related word pattern A related account term, a related account term, a related account term, a recommended account account corresponding to the common account transaction related word, and a recommendation account account corresponding to the common account transaction related word.

The machine learning pattern DB 213 may store a machine learning pattern as described above.

The pattern DB 200 may be used in the account recommendation and document creation system 300 in the future. That is, the account recommendation and document creation system 300 can process various transaction proof data using the pattern DB 200 and generate corresponding document data. Hereinafter, the account recommendation and document creation system 300 300 will be described in more detail with reference to FIG.

3 is a diagram illustrating a schematic configuration of an account recommendation and slip creation system 300 according to an embodiment of the present invention.

3, the account recommendation and slip creation system 300 includes a scraping module 320, an image recognition module 330, an extraction module 340, a control module 350, a slip data generation module 360, A commercial pattern pattern search module 301, a word pattern search module 302, a taxation pattern search module 303, an unprotected pattern search module 304, a common business entity number pattern search module 305, A cost category pattern search module 307, a settlement account pattern search module 308, a business entity pattern search module 309, an industry word pattern search module 310, a passbook transaction related word pattern search module 311 A common bank transaction related word pattern search module 312, and a machine learning pattern search module 313. According to an embodiment of the present invention, some of the above-described components may not necessarily correspond to components necessary for implementing the present invention, and the pattern generation system 100 may further include, It goes without saying that more components may be included.

The account recommendation and document creation system 300 may include hardware resources and / or software required to implement the technical idea of the present invention, and may be a physical component or a device It does not mean anything. That is, the account recommendation and document creation system 300 may mean a logical combination of hardware and / or software provided to implement the technical idea of the present invention. If necessary, The present invention may be embodied as a set of logical structures for realizing the technical idea of the present invention. In addition, the account recommendation and document creation system 300 may mean a set of configurations separately implemented for each function or role for implementing the technical idea of the present invention. For example, the scraping module 320, the image recognition module 330, the extraction module 340, the control module 350, the slip data generation module 360, the business number pattern search module 301, Module 302, a taxation type pattern search module 303, a nonprofit pattern search module 304, a common company number pattern search module 305, a common word pattern search module 306, a cost cost group pattern search module 307 A business type word pattern search module 310, a bankbook transaction related word pattern search module 311, a public account transaction related word pattern search module 312 ), The machine learning pattern search module 313 may be located in different physical devices, or may be located in the same physical device. According to the embodiment, the scraping module 320, the image recognition module 330, the extraction module 340, the control module 350, the slip data generation module 360, the business number pattern search module 301, A word pattern search module 302, a taxation type pattern search module 303, an unprotected pattern search module 304, a common company number pattern search module 305, a common word pattern search module 306, Module 307, a settlement account pattern search module 308, a business entity pattern search module 309, an industry word pattern search module 310, a passbook transaction related word pattern search module 311, a common bank transaction related word pattern search The detailed configurations of each module such as the module 312 and the machine learning pattern search module 313 are also located in different physical devices and detailed configurations located in different physical devices are organically coupled to each other, May be realized.

The control module 350 may be configured to provide the account recommendation and other features included in the document creation system 300 (e.g., scraping module 320, image recognition module 330, extraction module 340, A commercial number pattern search module 301, a word pattern search module 302, a taxation type pattern search module 303, an unproven pattern search module 304, a common company number pattern search module 305, A pattern search module 308, a business type pattern search module 309, a business word pattern search module 310, a pass word transaction pattern search module 307, Module 311, the public banking transaction related word pattern retrieving module 312, the machine learning pattern retrieving module 313, and the like) and / or resources.

The scraping module 320 may generate transaction data by scraping at least one of electronic tax calculation data, electronic billing data, credit card transaction history data, cash receipt data, and bank account transaction data from a predetermined web site.

Meanwhile, the scraping module 320 may collect transactions evidence such as electronic tax invoices, electronic invoices, credit card receipts, cash receipts, and bankbooks from a predetermined web site 20. The web site 20 may include an e-vertical site of the National Tax Service, a cash receipt site, various credit finance association sites, various card company sites, various bank sites, and the like. For example, the scraping module 320 may collect purchase / sales data of electronic tax invoices and electronic invoices through the e-vertical site, and may purchase cash receipts / sales, credit card purchases / sales data And collect credit card sales data from the Kookmin Financial Association website, collect credit card purchasing data through each credit card company site, and collect bankbook deposit and withdrawal data from each bank site.

The image recognition module 330 can generate the transaction data by recognizing at least one of a tax bill, a credit card transaction history, a cash receipt, and a passbook. That is, the image recognition module 330 scans / photographs the paper evidence 30 such as a tax bill, a credit card transaction history, a cash receipt, a passbook, etc. and analyzes the image, Lt; / RTI >

The generated transaction data may include a business number, a product name, a brief, a business name, a transaction date, an amount, and the like. If the transaction data is passbook-related transaction data, the passbook brief, the passbook vendor, , Amount, and the like.

The scraping module 320 and / or the image recognition module 330 may automatically acquire and / or perform image recognition by a predetermined scheduler module (not shown). The scheduler module may automatically drive the scraping module 320 and / or the image recognition module 330 periodically (e.g., every day).

The extraction module 340 may extract at least one of a search target business number or a search target word from the transaction data.

The account recommendation and slip creation system 300 can search the pattern DB 200 for various data necessary for slip creation including the recommended account slip based on the retrieval object business number or the retrieval object word.

The business entity number pattern search module 301 can search the business entity number pattern DB 201 for a recommended account subject corresponding to the extracted business entity number.

Also, the word pattern search module 302 may search the word pattern DB 202 for a recommended account subject corresponding to the extracted search target word.

Meanwhile, the recommended account subject retrieved by the business number pattern search module 301 may be the same as the recommended account subject retrieved by the word pattern retrieval module 302, but they may be different from each other. In addition, the recommended account subject searched by the business number pattern search module 301 and / or the recommended account subject searched by the word pattern search module 302 may be two or more.

As described above, when there are a plurality of recommended account subjects retrieved by the business number pattern search module 301 and / or the business number pattern search module 301, one of them can be selected by the recommendation degree of each retrieved recommended account subject have. That is, the control module 350 selects one of the recommended account items retrieved by the business number pattern search module 301 and / or the business number pattern search module 301, Subject can decide.

On the other hand, if the transaction data is data of a new customer or the business number pattern search module 301 can not retrieve a recommended account item corresponding to the search target business number from the business number pattern database 201 for other reasons . In this case, the business number pattern search module 301 can search the public service number pattern DB 305 for a recommended account item corresponding to the search target business number. Similarly, if the word pattern search module 302 fails to retrieve a recommended account subject corresponding to the search target word from the word pattern DB 202, or if the transaction data is data of a new customer, Can be searched in the common word pattern DB 306. [0064]

Meanwhile, the taxation type pattern search module 303 can search the taxation type pattern DB 203 for a recommendation taxation type corresponding to the search target business number. If two or more recommended taxation types are searched, the control module 350 can determine one of the recommended taxation types corresponding to the searched business entity number as the taxation type corresponding to the transaction data having the highest recommendation degree.

The unprovoked pattern search module 304 can search the unproved pattern DB 204 for a non-recommendable cause corresponding to the search target business number. If two or more unfair causes are searched, the control module 350 may determine one of the recommended non-compliances corresponding to the searched service provider number as the unproblematic corresponding to the transaction data.

If the account category corresponding to the transaction data is related to the cost or expense, the cost cost group pattern search module 307 searches the cost category group DB 207 for a recommendation cost corresponding to the account subject corresponding to the transaction data You can search for expense accounts. In addition, the control module 350 may determine one of the recommended cost expense accounts corresponding to the account subject corresponding to the retrieved transaction data as the cost expense account corresponding to the transaction data.

The billing account pattern search module 308 may search the billing account pattern database 208 for a recommendation credit account account corresponding to the account account corresponding to the transaction data, A recommendation credit account corresponding to the account data corresponding to the transaction data may be determined as the credit account account corresponding to the transaction data.

Meanwhile, there may be a case where the transaction data is data related to a bank account transaction. In this case, the passbook transaction-related word pattern search module 311 can search the passbook transaction related word pattern DB 211 for a recommended account subject corresponding to the search target word. If the banknote transaction related word pattern retrieval module 311 does not retrieve the recommended account subject corresponding to the retrieval target word from the bankbook transaction related word pattern DB 211 or the transaction data is data of a new customer, It is possible to search for the recommended account subject corresponding to the search target word in the common business entity number pattern DB 312. The control module 350 may determine one of the recommended account classes corresponding to the searched search word as the account class corresponding to the transaction data.

The slip data generation module 360 may generate slip data including slip data related information retrieved in the manner described above (for example, an account subject corresponding to the transaction data).

4A to 4D are diagrams for explaining how the account recommendation and document creation system 300 generates the slip data.

FIG. 4A is a view showing an example of a card receipt, which is one of transaction proofs. 4A, the account recommendation and document creation system 300 can image the card receipt and generate transaction data. The generated transaction data includes a card type (Kookmin Bank), a transaction date 2012-05-15, an amount 4545, a sales tax 455, a merchant name (FOOD), a business number (101-81- 12345), and the like.

Meanwhile, the account recommendation and slip creation system 300 can extract a business number from the transaction data and search for an account subject in the business number pattern DB 201. The word 'food' included in the merchant name is extracted The account subject can be searched in the word pattern DB 202.

FIG. 4B is a diagram showing a result of searching in the business number pattern DB 201 and the word pattern DB 202. FIG. Referring to FIG. 4B, the account recommendation and slip creation system 300 may search for 'benefits' (account code 811) and 'entertainment expenses' (account code 813). Since the recommendation degree of the 'Welfare Benefits' account is the largest among these two accounts, the account recommendation and document creation system 300 recommends the 'Welfare Benefits' account as an account item for the transaction document as shown in FIG. 4A .

Meanwhile, the account recommendation and slip creation system 300 may search the settlement account pattern DB 208 for a credit account for 'Welfare Benefits', which is a recommended account item, and recommend the 'accounts payable' account as a credit account .

In addition, the account recommendation and document creation system 300 can further search the pattern DB 200 for other detailed items required to generate the slip data, and extract items to be included in the slip data from the transaction data It is possible.

After acquiring the detailed items necessary for the creation of the slip data, the account recommendation and slip creation system 300 can generate the slip data as shown in FIG. 4C or 4D.

Meanwhile, according to an embodiment, the account recommendation and document creation system 300 may include a processor and a memory for storing a program executed by the processor. The processor may include a single-core CPU or a multi-core CPU. The memory 11 may include a high speed random access memory and may include non-volatile memory such as one or more magnetic disk storage devices, flash memory devices, or other non-volatile solid state memory devices. Access to the memory by the processor and other components can be controlled by the memory controller. Here, when the program is executed by a processor, the program may cause the account recommendation and document creation system 300 according to the present embodiment to perform the method of providing the account recommendation and the document creation system described above.

Meanwhile, a method of providing an account recommendation and a document creation system according to an embodiment of the present invention may be implemented in the form of computer readable program instructions and stored in a computer readable recording medium. A computer-readable recording medium includes all kinds of recording apparatuses in which data that can be read by a computer system is stored.

The program instructions recorded on the recording medium may be those specially designed and constructed for the present invention or may be those known to those skilled in the software art.

Examples of the computer-readable recording medium include magnetic media such as a hard disk, a floppy disk and a magnetic tape, optical media such as CD-ROM and DVD, a floptical disk, And hardware devices that are specially configured to store and execute program instructions such as magneto-optical media and ROM, RAM, flash memory, and the like. The above-mentioned medium may also be a transmission medium such as a light or metal wire, wave guide, etc., including a carrier wave for transmitting a signal designating a program command, a data structure and the like. The computer readable recording medium may also be distributed over a networked computer system so that computer readable code can be stored and executed in a distributed manner.

Examples of program instructions include machine language code such as those produced by a compiler, as well as devices for processing information electronically using an interpreter or the like, for example, a high-level language code that can be executed by a computer.

The hardware devices described above may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

It will be understood by those skilled in the art that the foregoing description of the present invention is for illustrative purposes only and that those of ordinary skill in the art can readily understand that various changes and modifications may be made without departing from the spirit or essential characteristics of the present invention. will be.

It is therefore to be understood that the above-described embodiments are illustrative in all aspects and not restrictive. For example, each component described as a single entity may be distributed and implemented, and components described as being distributed may also be implemented in a combined form.

It is intended that the present invention covers the modifications and variations of this invention provided they come within the scope of the appended claims and their equivalents. .

Claims (18)

As an account recommendation and slip creation system using a pattern database (DB)
Stores the business number pattern of each of the customer's companies including the business number included in the past accounting processing details of each customer who joined the pattern generation system, the recommended account subject for each business number, and the recommendation level of the recommended account subject for each business number DB number pattern DB;
A word pattern included in the past accounting processing history of each of the customer companies subscribed to the pattern generation system, a recommendation account subject corresponding to each of the words, and a recommendation account course corresponding to each of the words, Word pattern DB;
An extraction module for extracting at least one of a search target business number or a search target word from predetermined transaction data;
A business entity number pattern search module for searching the business entity number pattern DB for a first recommended account subject corresponding to the extracted business entity number;
A word pattern search module for searching, from the word pattern DB, a second recommended account subject corresponding to the extracted search target word;
A control module for determining one of the first recommendation account or the second recommendation account as the account subject corresponding to the transaction data;
And a slip data generating module for generating slip data including an account subject corresponding to the transaction data. The system of claim 1, wherein the account recommendation and document creation system using the pattern database comprises:
The taxation type pattern of each of the customer companies including the business number included in the past accounting processing details of each of the customer companies subscribed to the pattern generation system, the recommended taxation type for each business number and the recommended taxation type for each business number Storing taxation type pattern DB; And
Further comprising a taxation type pattern search module for searching, in the taxation type pattern DB, a recommendation taxation type corresponding to the search target business number,
The control module includes:
And a pattern database for determining one of the recommended taxation types corresponding to the searched business number as the taxation type corresponding to the transaction data.
The system of claim 1, wherein the account recommendation and document creation system using the pattern database comprises:
An unproblematic pattern of each of the customers including the business number included in the past accounting processing history of each customer who joined the pattern generation system, the recommendation disagreement by each business number, Unproblematic pattern DB to store;
And an unproved pattern search module for searching, from the unprofitable pattern DB, a recommendation nonprofit corresponding to the search target business number,
The control module includes:
And a pattern database for determining one of the recommendation nonconformities corresponding to the searched business entity number as the disadvantage corresponding to the transaction data.
The system of claim 1, wherein the account recommendation and document creation system using the pattern database comprises:
A cost estimate for storing the cost cost group pattern of the customer including the recommendation cost cost account corresponding to each of the account items related to the cost or expense of each of the customer companies subscribed to the pattern generation system and the recommendation degree of each recommendation cost expense account Group pattern DB;
And a cost expense group pattern retrieval module for retrieving a recommended cost expense account corresponding to the account subject corresponding to the transaction data from the cost expense group pattern DB when the account subject corresponding to the transaction data is related to the cost or expense However,
The control module includes:
And a pattern database for determining one of a recommended cost expense account corresponding to an account subject corresponding to the retrieved transaction data as a cost expense account corresponding to the transaction data.
The system of claim 1, wherein the account recommendation and document creation system using the pattern database comprises:
A plurality of debit account subjects of each of the customers who have joined the pattern generation system, a recommendation credit account subject to each debit account subject, and a recommendation credit account subject to each debit account subject, A billing account pattern DB for storing patterns;
And a settlement account pattern search module for searching the settlement account pattern DB for a recommendation account item corresponding to an account item corresponding to the transaction data,
The control module includes:
And a pattern database for determining one of the recommendation credit account items corresponding to the account item corresponding to the retrieved transaction data as a credit account item corresponding to the transaction data.
The system of claim 1, wherein the account recommendation and document creation system using the pattern database comprises:
A common service provider number pattern DB for storing a common service provider number pattern including a service provider number included in the past account processing details, a recommended account subject for each business number, and a recommendation level of a recommended account subject for each business number; And
A common word pattern DB for storing a common word pattern including a word included in the past accounting processing history, a recommended account subject corresponding to each of the words, and a recommendation level of a recommended account subject corresponding to each of the words,
The business entity number pattern search module,
If it is not possible to retrieve a recommended account subject corresponding to the search target business number from the business entity number pattern database or if the transaction data is data of a new customer, the first recommended account subject corresponding to the search target business number, The number pattern DB,
The word pattern search module includes:
If it is not possible to retrieve a recommended account subject corresponding to the search target word from the word pattern DB or if the transaction data is data of a new customer, the second recommended account subject corresponding to the search target word to the common word pattern DB System of Account Recommendation and Document Creation Using Pattern Database Retrieved from.
The system of claim 1, wherein the account recommendation and document creation system using the pattern database comprises:
A recommendation account corresponding to each bankbook transaction related word and a recommendation account correspondence item corresponding to each bankbook transaction word included in the past account processing history of each customer who joined the pattern generation system A banknote transaction related word pattern DB storing a banknote transaction related word pattern of each of the customer companies;
A public account transaction related word included in the past account processing history, a recommended account item corresponding to each of the public account transaction related words, and a recommendation account corresponding to each of the public account transaction related words A common banknote transaction related word pattern DB;
If the transaction data is data related to a bank account transaction, searching a recommended account subject corresponding to the search target word in a bank transaction-related word pattern DB,
If it is not possible to retrieve a recommended account subject corresponding to the search target word from the bankbook transaction related word pattern DB or if the transaction data is data of a new customer, a recommended account subject corresponding to the search target word is stored in the common provider number pattern DB And a banknote transaction related word pattern retrieval module for retrieving the banknote transaction related word pattern retrieval module,
The control module includes:
And a pattern database for determining one of the recommended account items corresponding to the searched search word as the account subject corresponding to the transaction data.
The system of claim 1, wherein the account recommendation and document creation system using the pattern database comprises:
A scraping module for scraping at least one of electronic tax calculation data, electronic billing data, credit card transaction history data, cash receipt data, and bankbook transaction data from a predetermined website to generate the transaction data; or
And an image recognition module for recognizing at least one of a tax bill, a credit card transaction history, a cash receipt, and an account, and generating the transaction data.
A method of providing an account recommendation and slip creation system using a pattern database,
The business number of each of the customer companies including the recommendation number of the recommendation account item by each business number and the business number included in the past accounting processing details of each customer who joined the pattern generation system, Storing in a number pattern DB;
Wherein each word pattern of each of the customer companies including a word included in the past accounting processing history of each customer who joined the pattern generation system, a recommended account subject corresponding to each of the words, and a recommended account subject corresponding to each of the words, Storing in a pattern DB;
Extracting at least one of a search target business number or a search target word from predetermined transaction data;
Retrieving a first recommended account subject corresponding to the extracted search target business number from the business ID number pattern DB;
Searching the word pattern database for a second recommended account subject corresponding to the extracted search target word;
Determining one of the first recommendation account or the second recommendation account as the account subject corresponding to the transaction data; And
And generating slip data including an account subject corresponding to the transaction data.
10. The method of claim 9, wherein the account recommendation and the slip creation system using the pattern database include:
The taxation type pattern of each of the customer companies including the business number included in the past accounting processing details of each of the customer companies subscribed to the pattern generation system, the recommended taxation type for each business number and the recommended taxation type for each business number Storing in the taxation type pattern DB;
Searching the taxation type pattern DB for a recommendation taxation type corresponding to the search target business number; And
Further comprising the step of determining, as the taxation type corresponding to the transaction data, one of the recommended taxation types corresponding to the searched business entity number, which is the highest of the recommended taxation types, as the taxation type corresponding to the transaction data.
10. The method of claim 9, wherein the account recommendation and the slip creation system using the pattern database include:
An unproblematic pattern of each of the customers including the business number included in the past accounting processing history of each customer who joined the pattern generation system, the recommendation disagreement by each business number, Storing them in a nonproblematic pattern DB;
Retrieving a recommendation nonprofit corresponding to the search target business number from the nonprofit pattern DB; And
Further comprising the step of determining that one of the recommendation nonconformities corresponding to the searched business number is the nonconformity corresponding to the transaction data.
10. The method of claim 9, wherein the account recommendation and the slip creation system using the pattern database include:
The cost cost group pattern of the customer's cost including the recommendation cost cost account and the recommendation cost of each recommendation cost expense account corresponding to each account item related to the cost or expense of each of the customer companies subscribed to the pattern generation system, DB;
Searching for a recommended cost expense account corresponding to an account subject to the transaction data in the cost expense group pattern DB if the account subject corresponding to the transaction data is associated with a cost or expense; And
Further comprising the step of: determining, as a cost expense account corresponding to the transaction data, one of the recommended cost expense accounts corresponding to the account subject corresponding to the retrieved transaction data, having the highest recommendation degree as the cost expense account, / RTI >
10. The method of claim 9, wherein the account recommendation and the slip creation system using the pattern database include:
A plurality of debit account subjects of each of the customers who have joined the pattern generation system, a recommendation credit account subject to each debit account subject, and a recommendation credit account subject to each debit account subject, Storing the pattern in the settlement account pattern DB;
Retrieving a recommendation credit account subject to an account subject corresponding to the transaction data in the settlement account pattern DB; And
Determining one of the recommendation credit account items corresponding to the account item corresponding to the retrieved transaction data as the credit account item corresponding to the transaction data, the account recommendation and the slip using the pattern database / RTI >
10. The method of claim 9, wherein the account recommendation and the slip creation system using the pattern database include:
Storing a common service provider number pattern in a common service provider number pattern DB including a service provider number included in the past account processing details, a recommended account item for each service number, and a recommendation level of a recommended account class for each service number;
Storing a common word pattern including a word included in the past accounting processing history, a recommended account subject corresponding to each of the words, and a recommendation level of a recommended account subject corresponding to each of the words to the common word pattern DB;
If it is not possible to retrieve a recommended account subject corresponding to the search target business number from the business entity number pattern database or if the transaction data is data of a new customer, the first recommended account subject corresponding to the search target business number, Searching in the number pattern DB; And
If it is not possible to retrieve a recommended account subject corresponding to the search target word from the word pattern DB or if the transaction data is data of a new customer, the second recommended account subject corresponding to the search target word to the common word pattern DB Wherein the system further comprises a step of retrieving the account recommendation and document creation system using the pattern database.
10. The method of claim 9, wherein the account recommendation and the slip creation system using the pattern database include:
A recommendation account corresponding to each bankbook transaction related word and a recommendation account correspondence item corresponding to each bankbook transaction word included in the past account processing history of each customer who joined the pattern generation system Storing a word transaction related word pattern of each customer company in a bank transaction related word pattern DB;
A public account transaction related word included in the past account processing history, a recommended account item corresponding to each of the public account transaction related words, and a recommendation account corresponding to each of the public account transaction related words Storing a word pattern in a common banknote transaction related word pattern DB;
Searching for a recommended account subject corresponding to the search target word in a passbook transaction related word pattern database if the transaction data is data related to a passbook transaction;
If it is not possible to retrieve a recommended account subject corresponding to the search target word from the bankbook transaction related word pattern DB or if the transaction data is data of a new customer, a recommended account subject corresponding to the search target word is stored in the common provider number pattern DB ; And
Further comprising the step of determining, as an account subject corresponding to the transaction data, one of the recommended account subjects corresponding to the searched word to be searched, the one having the highest recommendation degree as the account subject corresponding to the transaction data.
10. The method of claim 9, wherein the account recommendation and the slip creation system using the pattern database include:
Generating the transaction data by scraping at least one of electronic tax calculation data, electronic billing data, credit card transaction history data, cash receipt data, and bankbook transaction data from a predetermined web site; or
And generating the transaction data by recognizing at least one of a tax invoice, a credit card transaction history, a cash receipt, and a passbook.
A computer-readable recording medium having recorded thereon a program for performing the method according to any one of claims 9 to 16.
As an account recommendation and slip creation system using a pattern database,
A processor; And a memory in which the program is stored,
Wherein said program, when executed by said processor, causes said journal data analysis system to perform the method of any one of claims 9 to 16.

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