KR101972895B1 - Apparatus and method for providing transaction book service - Google Patents

Abstract

Provides a device and a method for providing a transaction ledger service that automatically classifies the contents of a transaction and presents the accuracy of the contents of the classified item, but recommends a specific number of items when revising the contents of the item. The proposed apparatus includes a scraping unit for collecting at least one transaction information of a user, a transaction book interface based on transaction information, automatically classifying the contents of each transaction information, displaying the accuracy of content classification of items, A transaction ledger interface generating unit for presenting the contents of a recommendation item for the selected transaction information, and an output unit for sending the transaction ledger interface to the user terminal.

Description

[0001] APPARATUS AND METHOD FOR PROVIDING TRANSACTION BOOK SERVICE [0002]

BACKGROUND OF THE INVENTION 1. Field of the Invention The present invention relates to an apparatus and method for providing a transaction ledger service, and more particularly, to an apparatus and method for providing a service that can automatically generate a ledger.

The National Tax Service adopts a voluntary declaration and payment system that allows taxpayers to calculate, report and pay tax base by themselves. Accordingly, corporations and individual entrepreneurs prepare accounting books and the tax amount is calculated based on them.

In the end, the preparation of accounting books should precede the tax work, but it is necessary to assist the experts in arranging the receipt and withdrawal slips and receipts that occur from time to time and writing the financial statements such as wage management .

Also, it takes a lot of time to write an accounting book by hand, and there is a problem that an error occurs in writing an item in the writing process.

In recent years, an automatic book service (for example, an automatic book service such as Easy Shop service) has been launched and used so that a user (that is, an individual business person or a corporation) can automatically invoke a transaction history without generating a receipt, have.

In this conventional automatic book service (for example, Easy Book Automatic Book Service), for example, when a user selects a bank, a credit card, an electronic (tax) bill or a cash receipt by setting a period, And collects the transaction details of the selected item and displays it on the user's terminal through a graphical user interface (see FIG. 1). For example, the above-described graphic user interface may be provided with a date, a business partner, an item, an item (content), a supply price, a sales tax, a duty free supply price, a total, and the like.

Accordingly, the user reports a graphical user interface (see FIG. 1) displayed on the screen, selects the contents of a desired item (for example, a cost item or a cost item) after clicking on the item column for each transaction. At this time, when the user clicks on one of the items (1 in FIG. 1), the item selection window (see FIG. 2) containing all items (about 160 items) that can be selected is displayed in a pop-up form. The user moves the scroll bar (2 in FIG. 2) of the pop-up-type item selection window 3 to select contents suitable for the transaction.

However, in the conventional automatic book service, the item selection window 3 containing a large number of item contents is displayed in a pop-up form, and a user has to select the appropriate item contents by moving the scroll bar 2 It is troublesome.

In addition, since the user directly selects among a large number of items, it takes a long time to select the content of an unfamiliar transaction, and it is highly likely that a wrong choice is made.

Prior Art 1: Korean Patent Laid-Open No. 10-2015-0067821 (System and Method of Automatic Book Creation and On-line Tax Accounting Service and Electronic Tax Reporting for Electronic Tax Reporting) Prior Art 2: Korean Patent Laid-Open No. 10-2013-0142741 (Tax Administration Automation Device) Prior Art 3: Korean Patent Laid-Open No. 10-2015-0013922 (Method of management of management ledger accounting) Prior Art 4: Korean Patent No. 10-1679051 (Tax Simplification System and Its Tax Management Method)

DISCLOSURE OF THE INVENTION The present invention has been proposed in order to solve the above-mentioned problems of the related art, and it is an object of the present invention to provide an apparatus and a method for automatically classifying and providing contents of an item for each transaction, And an apparatus and method for providing a transaction ledger service recommending the contents of an item.

According to an aspect of the present invention, there is provided an apparatus for providing a transaction ledger service, the apparatus comprising: a scraping unit for collecting at least one transaction information of a user; A transaction book that generates an account book interface based on the transaction information and displays the accuracy of the content of each transaction information item and presents the content of the recommendation item for the transaction information selected by the user based on the displayed accuracy; An interface generation unit; And an output unit for sending the transaction ledger interface to the user terminal.

A method of providing a transaction ledger service according to a preferred embodiment of the present invention is a method of providing a transaction ledger service in a transaction ledger service providing apparatus, comprising: a first step of collecting at least one transaction information of a user; A transaction history interface for generating transaction information based on the transaction information, displaying the accuracy of the content of each transaction information item, and presenting the content of the recommendation item for the transaction information selected by the user based on the displayed accuracy, step; And a third step of sending the transaction book interface to the user terminal.

Meanwhile, the service providing method may be implemented as a computer-readable recording medium storing a program to be executed by a computer, and may be provided as a program itself.

According to the present invention having such a configuration, the contents of the item (that is, the item information) are automatically classified and written for each transaction information, thereby solving the conventional problem that the user has directly written.

In addition, by displaying the accuracy of the item content classification according to the transaction information in color, the user can check only the item contents of a number of suspicious transaction information (that is, transaction information in which the accuracy of item information classification is low) among a plurality of transaction information It is possible to minimize the error rate of entry of the item contents.

Item recommendation

1 and 2 are diagrams employed to explain the problem in the conventional automatic book service.
3 is a system configuration diagram to which a transaction service providing apparatus according to an embodiment of the present invention is applied.
4 is an internal configuration diagram of the transaction ledger service providing server shown in FIG.
5 is an internal configuration diagram of the transaction ledger interface generation unit shown in FIG.
6 and 7 are flowcharts illustrating a method of providing a transaction ledger service according to an embodiment of the present invention.
8 is a diagram illustrating an example of a transaction ledger interface transmitted to the user terminal shown in FIG.
FIG. 9 and FIG. 10 are flowcharts for more specifically illustrating the item classification process for each transaction information shown in FIG.

While the invention is susceptible to various modifications and alternative forms, specific embodiments thereof are shown by way of example in the drawings and will herein be described in detail.

It should be understood, however, that the invention is not intended to be limited to the particular embodiments, but includes all modifications, equivalents, and alternatives falling within the spirit and scope of the invention.

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 the present application, the terms "comprises" or "having" and the like are used to specify that there is a feature, a number, a step, an operation, an element, a component or a combination thereof described in the specification, But do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in commonly used dictionaries should be interpreted as having a meaning consistent with the meaning in the context of the relevant art and are to be interpreted in an ideal or overly formal sense unless explicitly defined in the present application Do not.

Hereinafter, preferred embodiments of the present invention will be described in detail with reference to the accompanying drawings. In order to facilitate the understanding of the present invention, the same reference numerals are used for the same constituent elements in the drawings and redundant explanations for the same constituent elements are omitted.

3 is a system configuration diagram to which a transaction service providing apparatus according to an embodiment of the present invention is applied.

The system shown in FIG. 3 includes a user terminal 10, a network 20, a transaction information source 30, a database 40, and a transaction ledger service providing server 60.

The user terminal 10 is a terminal of an individual business corporation or corporation capable of transmitting tax data for voluntary tax payment to the Internal Revenue Service. Here, the user may mean an individual business operator or a corporation.

Users should present their books in the form of doubles according to the corporate accounting standards. In the case of small businesses, however, they should submit a simple book in consideration of captain ability and cost burden. do.

The user terminal 10 may be provided with a transaction book automatic generation service from the transaction ledger service providing server 60. [ In other words, when the user terminal 10 accesses the transaction book providing server 60 through the network 20 and requests the transaction book automatic generation service, the corresponding service can be provided. Here, the transaction book automatic generation service request can be started by selecting "Import Transaction Details" on the screen. If you do not have the "Import transaction history" menu, you will be able to select the menu corresponding to the transaction book automatic generation service request.

The user (provider) must first go through the registration process in order to receive the transaction book automatic generation service from the transaction ledger service providing server 60. In this case, the business operator should input the mutual name, business type, business address, tax office of workplace, business address code, and the like. You will also need to register business accounts, purchase cards, purchases, and accounts.

A business account is a business account that is reported to the tax office of the business site or an account that is actually used for business purposes. The account information of the business account can be provided as transaction data by inputting the financial institution of the business account, the bank account number, have.

The purchase card is a credit card in the name of the employer used to purchase goods or services, and if the card company of the purchase card, the card number, and the payment account of the card are inputted, the card usage details and the charge amount can be provided as transaction data have.

Purchase and sales The customer can input the mutual, business type, business number (resident registration number), cost item, etc., and the transaction information can be processed in more detail about the purchase / sales history through the input of the customer.

In particular, the user terminal 10 can select an item of specific transaction information from a transaction book interface (corresponding to a GUI-type user interface) in which the contents of items are automatically classified and written for each transaction information and the accuracy of classification of item contents is displayed have. Here, selecting an item of specific transaction information means that there is an intention to modify the contents of the item of the transaction information.

Then, the user terminal 10 can send a signal to the transaction book service providing server 60, which selects a recommendation item content from among the item contents of the recommended number (for example, 5 or less) recommended for the selected transaction information have.

For example, the user terminal 10 may be implemented as a portable terminal or a computer.

Here, the portable terminal is a wireless communication device that is guaranteed to be portable and mobility, and can be used as a personal communication system (PCS), a global system for mobile communications (GSM), a personal digital cellular (PDC), a personal handyphone system (PHS) Handheld devices such as a handheld device, an assistant, an IMT (International Mobile Telecommunication) -2000, a Code Division Multiple Access (CDMA) -2000, a W-CDMA ) Based wireless communication devices.

The computer may include a desktop, a notebook, a laptop, and the like on which a WEB Browser is mounted. The user terminal 10 may be a smart device such as a smart phone, a smart note, a tablet PC, a smart camera, a smart TV, a wearable computer, or the like.

The network 20 may be implemented as a wired network such as a local area network (LAN), a wide area network (WAN), or a value added network (VAN). The network 20 may be implemented in any type of wireless network such as a mobile radio communication network, a satellite communication network, a Bluetooth, a Wireless Broadband Internet (Wibro), a High Speed Downlink Packet Access (HSDPA) have. On the other hand, the network 20 may be implemented as a network by a combination of wired and wireless.

The transaction information source 30 may provide transaction data including at least one purchase or sales transaction method.

The transaction information source 30 may include a bank, a credit card company, a cash receipt issuer, an electronic tax bill issuer, a securities company, an insurance company, and the like.

The transaction data provided from the transaction information source 30 includes bank account deposit and withdrawal information of a bank account, credit card purchase slip, cash receipt issuance information, electronic tax invoice issuance information, securities account deposit and withdrawal information, insurance account deposit and withdrawal information, and the like .

It is preferable that the transaction data of the transaction information source 30 is provided to the transaction ledger service providing server 60 after the authentication step has been performed in advance for information security. In other words, when accessing a server of the transaction information source 30 to collect transaction information, the transaction ledger service providing server 60 receives only transaction data of a provider that has been previously authenticated for information security. For example, when a business operator inputs predetermined authentication information to the transaction information source 30, the transaction information source 30 may provide the transaction data to the transaction book service server 60 in response to the authentication information have. Here, responding to the authentication information may mean a case where the authentication information input by the business entity matches the authentication information of the business entity held by the transaction information source 30. As a result, the transaction ledger service providing server 60 can acquire (acquire) transaction data by accessing the transaction information source 30 after the user inputs the authentication information and the agreement is confirmed.

The database 40 stores various types of information about the user (individual business person or corporation) who has joined the membership. Here, the various types of information may be, for example, a mutual name, a business type, a business address, a tax office, a business address code, a business account, a purchase card, On the other hand, examples of the various kinds of information described above can be added or subtracted as necessary.

In addition, the database 40 may store user-specific transaction information and a user-specific transaction book (for example, a bookkeeper, a simple book, or a journal) automatically generated by the transaction book service providing server 60.

The transaction ledger service providing server 60 collects one or more pieces of transaction information of the corresponding user from the transaction information source 30 when receiving the transaction ledger automatic generation service request from the user terminal 10. If the user sets the collection period, the transaction ledger service providing server 60 may collect only the transaction information within the collection period.

Also, the transaction ledger service providing server 60 generates a transaction ledger interface (i.e., GUI type user interface) in which the contents of the items according to the transaction information are automatically classified based on the collected transaction information of the corresponding user, 10). At this time, the deal book interface will display a differential color according to the accuracy of automatic classification of item contents (item information) for each transaction information.

Upon receipt of the confirmation signal confirming the transaction ledger interface, the transaction ledger service providing server 60 displays a transaction ledger (for example, one of a double ledger, a simple ledger, and a journal) based on transaction information shown in the transaction ledger interface Can be automatically generated.

In particular, when receiving the item selection signal of the specific transaction information from the user terminal 10, the transaction ledger service providing server 60 transmits the contents of a specific number (for example, up to 5 items) to the item of the specific transaction information Recommended. Here, the recommended item contents may be referred to as a recommendation item content or a recommended item content list. Limiting the suggested content to about five is meant to allow you to see all the recommendations at once. If too many items are suggested, it can be troublesome to use a scroll bar or the like. Therefore, it is preferable to limit the content of the recommendation item to about five.

When receiving the recommendation item content selection signal from the user terminal 10, the transaction book service server 60 can modify the contents of the current item of the specific transaction information to the contents of the selected recommendation item.

Also, the transaction ledger service providing server 60 transmits the updated transaction ledger interface (i.e., GUI type user interface) to the user terminal 10.

3, the database 40 and the transaction ledger service providing server 60 are separately configured. However, the database 40 may be included in the transaction ledger service providing server 60. FIG.

4 is an internal configuration diagram of the transaction ledger service providing server 60 shown in FIG.

The transaction ledger service providing server 60 may include a scraping unit 62, a transaction ledger interface generating unit 64, and an output unit 66. The transaction ledger service providing server 60 may be the transaction ledger service providing apparatus described in the claims of the present invention.

The scraping unit 62 may collect one or more transaction information (transaction data) of the user from the transaction information source 30.

Since the transaction information source 30 may include agencies including various transaction methods, the scraping unit 62 may perform authentication approval for the transaction information source 30 in advance, So that the source 30 can collect transaction information. For example, the scraping unit 62 may extract transaction information from the transaction information source 30 using Web scraping and / or screen scraping techniques. Since the scrapping technique is a well known technique, further description of the scrapping technique is omitted.

The scraping unit 62 provides the collected one or more pieces of transaction information of the user to the transaction ledger interface generating unit 64. Here, the transaction information may include a name of a supplier, a transaction cost, a transaction date and the like.

The transaction ledger interface generating unit 64 generates a transaction ledger interface (for example, GUI type user interface) for the user based on the received one or more pieces of transaction information.

At this time, the transaction ledger interface generation unit 64 automatically classifies the contents of each item of transaction information, and determines the accuracy of the item content classification. The transaction ledger interface generating unit 64 may generate a book-shaped user interface (that is, corresponding to the transaction ledger interface) in which the accuracy of the content classification of items is displayed for each transaction information. Here, the transaction ledger interface generation unit 64 may display the accuracy by color. That is, the color of each transaction information may be changed according to the accuracy of classification of the contents of each transaction information item. Of course, the transaction information with the same content classification accuracy for the items will be displayed in the same color.

In the past, there is a problem that the user has to select the appropriate item contents by moving the scroll bar for each transaction among numerous item contents, and the user selects one of a large number of item contents, so that it takes time to select an unfamiliar item In addition to lengthening, there was a high probability of wrong choice. However, in the present invention, the problem of the conventional art can be solved by automatically classifying and specifying the contents of each item of transaction information.

In particular, when receiving the item selection signal of the specific transaction information, the transaction ledger interface generating unit 64 can recommend the contents of a specific number (for example, five or less) of items of the specific transaction information. At this time, the content of the recommendation item can be generated according to the accuracy of the item content classification method or the item content classification of the specific transaction information.

When receiving the recommendation item content selection signal, the transaction ledger interface generation unit 64 can modify the current item content of the specific transaction information to the contents of the selected recommendation item.

In addition, the transaction ledger interface generator 64 may transmit the updated transaction ledger interface (i.e., GUI-like user interface) to the user terminal 10.

The output unit 66 can output a book form user interface (i.e., a transaction book interface) from the transaction ledger interface generation unit 64. [ That is, the output unit 66 sends the user interface in the form of a book to the user terminal 10 via the network 20.

5 is an internal configuration diagram of the transaction ledger interface generation unit 64 shown in FIG.

The transaction ledger interface generation unit 64 may include an item classification unit 67, an accuracy determination unit 68, and a user interface generation unit 69.

The item classifying unit 67 can automatically classify the contents of the items of the collected transaction information of the corresponding user. The classifying unit 67 can sequentially sort and classify the following classification methods.

First, if the user (member) has the contents of the item (for example, the cost item or the expense item) previously selected for the transaction information, the contents of the item for the transaction information are classified into the contents of the item previously selected. Such a classification is referred to as a first classification method.

If there is no content of the previously selected item, it is first determined whether there is a member who has traded with the trading partner of the transaction information, and if there is a member of the same type of trader among the traded members, Here, since the membership information is stored in the database 40 in advance, it can be determined based on this information.

If there is a member in the same category as the user, the contents of the items selected by the members of the same type of industry for the transaction information are classified into the items of the corresponding transaction information. Such a classification is referred to as a second classification method.

On the contrary, if there is no member in the same business as the user, the contents of the item selected by the members of the business type other than the user most frequently selected for the transaction information are classified into the contents of the item of the transaction information. Such a classification is referred to as a third classification method.

However, in the case where there is no member who has traded with the trading partner of the transaction information described above, it is important to know the business type of the trading partner in order to classify the contents of the transaction information.

If the business type of the trading information is known, the contents of the predetermined item are classified into the contents of the item of the corresponding transaction information by referring to the business type of the user and the business type of the corresponding business. Such a classification may be referred to as a fourth classification method. The business type of the customer of the transaction information may be known through collected transaction information (i.e., scraping data) or DB (not shown) of the member company (merchant). The content of the predetermined item can be found through the first category classification table for each business type in which the content of the category for each category is created in the form of a look-up table. Although not illustrated, the contents of the item (for example, a cost item or an expense item) which is considered to be most suitable may be designated in consideration of the relationship between the business type of the business type and the business type of the user in the first business type item classification table. For example, if there are three suppliers (A, B, and C), the first category of item classification will have three item contents for the user's industry. That is, when the business type of the user and the business type of the business partner A correspond, the item content of " a " is associated. When the business type of the user and the business type of the business partner B correspond to each other, If the business type of the business type and the business type of the business type C are corresponded to each other, the item "C" will be associated. The category classification table for each business category is prepared in advance and stored in the category classifying section 54a, and any person skilled in the art will understand the above description.

On the other hand, if the business type of the customer of the transaction information can not be known, it is determined whether or not the business type is included in the business name of the customer. For example, in the case where the business partner's name is "@@ gas station", "%% restaurant", "&& mart", etc., the gas station, restaurant,

In the case of extracting a keyword that is classified as a business type within the mutual business partner, the contents of the predetermined item are classified into the contents of the item of the corresponding transaction information based on the business type of the user and the business type of the corresponding business partner based on keyword extraction. Such a classification is referred to as a fifth classification method. The content of the predetermined item may be the same as that described in the fourth classification method.

On the other hand, when the keywords that are classified as the business type are not extracted within the mutual business partners, that is, when there is no business keyword in the mutual business partners, a similar business type is estimated for the business partner through text comparison. For example, if the business partner's name is "Kagurepo Klee", the business type of hairdressing salon can be estimated as similar business type for the corresponding business. Meanwhile, in order to estimate the similar business type through the text comparison, the item classifying unit 54a may analyze the mutual customers and perform machine type automatic machine learning through text comparison. Then, the item classifying unit 54a will have the result of automatic type-machine learning of the industry type, and will utilize it.

If the similar business type is estimated for the corresponding business, the content of the predetermined business is classified into the content of the corresponding transaction information based on the business type of the user and the similar business type estimated for the business. Such a classification is referred to as a sixth classification method. The content of the predetermined item may be the same as that described in the fourth classification method.

As described above, the item classification unit 67 sequentially performs the six classification schemes described above, and classifies the contents of each item of the transaction information according to which classification scheme among the six classification schemes And transmits the classification result to the accuracy determining unit 68. [

The accuracy determining unit 68 determines the accuracy of the content classification for each item of the transaction information from the item classifying unit 67. [ For example, when the classification result from the item classification unit 67 is the first classification method, the accuracy of the content classification of the item of the transaction information may be 90 to 99%. When the classification result from the item classification unit 67 is the second classification method, the accuracy of the content classification of the item of the transaction information may be 80 to 89%. When the classification result from the item classification unit 67 is the third classification method, the accuracy of the content classification of the item of the transaction information may be 70 to 79%. When the classification result from the item classification unit 67 is the fourth classification method, the accuracy of the content classification of the item of the transaction information may be 60 to 69%. In the case where the classification result from the item classification unit 67 is the fifth classification method, the accuracy of the content classification of the item of the transaction information may be 50 to 59%. In the case where the classification result from the item classification unit 67 is the sixth classification method, the accuracy of the content classification of the item of the transaction information may be 40 to 49%.

The accuracy determining unit 68 transmits the determined accuracy to the user interface generating unit 69.

The user interface generating unit 69 may generate a user interface corresponding to a transaction type book interface in the form of a bookmark showing the accuracy of item content classification for each transaction information. At this time, the content of the item automatically classified for each transaction information is written in the user interface, and the accuracy of the content classification for each item of the transaction information can be displayed in color. That is, the user interface generation unit 69 may assign different colors to the transaction information according to the accuracy of the content classification of the items of the transaction information. Of course, transaction information with the same classification accuracy will be displayed in the same color.

The user interface generation unit 69 can determine that the accuracy of the content classification of the item of the transaction information is 90 to 99% because the classification result is the first classification method, for example, the color of the " Can be displayed.

The user interface generating unit 69 can display the corresponding transaction information in the color of the " marginal marginal orange " if the classification result is the second classification method and the accuracy of the content classification of the item of the corresponding transaction information is 80 to 89% can do.

The user interface generation unit 69 can determine that the accuracy of the content classification of the item of the transaction information is 70 to 79% because the classification result is the third classification method, for example, by displaying the corresponding transaction information in the color of " can do.

The user interface generation unit 69 displays the corresponding transaction information in the color of the " marginal orange ", for example, when the classification result is the fourth classification method and the accuracy of the content classification of the item of the transaction information is 60 to 69% .

The user interface generation unit 69 displays the transaction information in the color of "performance yellow", for example, if the classification result is the fifth classification system and the accuracy of the content classification of the item of the transaction information is 50 to 59% .

The user interface generating unit 69 can display the corresponding transaction information in the color of " orange ", for example, if the classification result is the sixth classification method and the accuracy of the content classification of the item of the transaction information is 40 to 49% have.

On the other hand, the colors exemplified in the above may be colors other than yellowing / yellowing / yellowing / yellowing / yellowing / yellowing / yellowing / orange. For example, it is possible to give a different color depending on the accuracy. For example, there are various colors such as a colorless / yellowish orange / a yellowish / yellowish / orange / a yellowish / orange, a colorless / blue / green / yellow / orange / It only needs to be arrayed to be visible to the user.

In particular, the user interface generation unit 69 includes a recommendation unit 69a. The recommendation section 69a can recommend the contents of a specific number of items (for example, five or less). That is, when the user selects an item of specific transaction information in order to modify the contents of the item of the specific transaction information in the user interface, the recommendation unit 69a sets the item content classification method of the specific transaction information or the item Based on the accuracy of the content classification, it is possible to present the contents of the recommendation items limited to a predetermined number (for example, five).

Here, the item content recommendation method of the recommendation section 69a will be described in more detail as follows.

If there is a member who has traded with the trading partner of the specific transaction information to be modified, it is judged whether or not there is a member in the same kind of business among the trading members. Here, since the membership information is stored in the database 40 in advance, it can be determined based on this information.

If there is a member in the same category as the user, it can recommend about 5 items in the order of the items selected by members of the same kind of business for the specific transaction information. In this case, the item classification method of the specific transaction information is the second classification method or the transaction information in which the accuracy of the item content classification described above is 80 to 89%.

On the contrary, if there is no member in the same business with the user, it can recommend about five items in the order of the items selected from the items selected by the members of the business type different from the user, for the specific transaction information. In this case, the item classification method of the specific transaction information is the third classification method or the transaction information in which the accuracy of the item content classification described above is 70 to 79%.

However, in the case where there is no member who has traded with the trading partner of the transaction information described above, it is important to know the business type of the trading partner in order to classify the contents of the transaction information.

If you can know the business type of the trading information, you can refer to the business type of the user and the business type of the customer, and recommend the contents of about 5 items that are set in advance. In this case, the item classification method of the specific transaction information is the fourth classification method or the transaction information having the accuracy of item category classification as described above is 60 to 69%. The business type of the customer of the transaction information may be known through collected transaction information (i.e., scraping data) or DB (not shown) of the member company (merchant). The contents of about 5 items set in advance can be known through the second category classification table for each business type, which is created in the form of a look-up table. Although not illustrated, in the second category classification table, contents of about five items (for example, a cost item or an expense item), which are considered to be most suitable considering the relationship between a business type of a user and a business type of a customer, Can be. For example, if there are three business partners (A, B, C), the second category classification table for each business category specifies contents of about five recommendation items in the case where the business category of the user corresponds to the business category of the business partner A, And the contents of the recommendation item of about five when the business type of the customer B is corresponded are specified and contents of the recommendation item of about five when the business type of the user and the business type of the business C are corresponded will be designated. The second category classification table for each category is prepared in advance and stored in the recommendation section 69a, and it is understood that the person skilled in the art can fully understand the above description.

On the other hand, if the business type of the customer of the transaction information can not be known, it is determined whether or not the business type is included in the business name of the customer. For example, in the case where the business partner's name is "@@ gas station", "%% restaurant", "&& mart", etc., the gas station, restaurant,

In the case of extracting the keywords that are classified as business type within the mutual business partners, the contents of about 5 items determined in advance based on the business type of the user and the business of the corresponding business partner based on the keyword extraction, . In this case, the item content classification method of the specific transaction information is the fifth classification method or the transaction information in which the accuracy of the item content classification described above is 50 to 59%. In this case, the contents of about 5 items set in advance are designated as the second category classification for each category and stored in the recommendation section 69a.

On the other hand, when the keywords that are classified as the business type are not extracted within the mutual business partners, that is, when there is no business keyword in the mutual business partners, a similar business type is estimated for the business partner through text comparison. For example, if the business partner's name is "Kagurepo Klee", the business type of hairdressing salon can be estimated as similar business type for the corresponding business. Meanwhile, in order to estimate the similar business type through the text comparison, the item classifying unit 54a may analyze the mutual customers and perform machine type automatic machine learning through text comparison. Then, the item classifying unit 54a will have the result of automatic type-machine learning of the industry type, and will utilize it.

If the similar business type is estimated for the corresponding business, the content of about 5 items determined in advance based on the business type of the user and the similar business type estimated for the business is designated as the content of the recommendation item for the specific transaction information. In this case, the item classification method of the specific transaction information is the sixth classification method or the transaction information in which the accuracy of the item content classification described above is 40 to 49%. In this case, the contents of about 5 items set in advance are designated as the second category classification for each category and stored in the recommendation section 69a.

FIGS. 6 and 7 are flowcharts for explaining a method of providing a transaction ledger service according to an embodiment of the present invention, and FIG. 8 is a diagram illustrating an example of a transaction ledger interface transmitted to the user terminal shown in FIG.

First, the transaction ledger service providing server 60 judges whether or not there is a transaction ledger automatic generation service request.

Accordingly, the transaction ledger service providing server 60 collects one or more pieces of transaction information of the corresponding user from the transaction information source 30 (S10) when receiving the request for automatic account generation service from the user terminal 10. Here, one or more pieces of transaction information may be referred to as a transaction information list. Collection of one or more pieces of transaction information can be done through scraping.

Thereafter, the transaction ledger service providing server 60 automatically classifies the contents of the items according to the transaction information based on the collected transaction information of the corresponding user (S20). Here, the transaction ledger service providing server 60 may sequentially perform an operation of determining which classification scheme is used among the six classification schemes in automatically classifying the contents of each item of transaction information, A more detailed description of the item content classification process will be given later.

Then, the transaction ledger service providing server 60 determines the accuracy of the content classification for each transaction information item (S30). For example, when the classification result is the first classification method, the accuracy of the content classification of the item of the transaction information may be 90 to 99%. And when the classification result is the second classification method, the accuracy of the content classification of the item of the transaction information is 80 to 89%. In the case where the classification result is the third classification method, the accuracy of the content classification of the item of the transaction information is 70 to 79%. In the case where the classification result is the fourth classification method, the accuracy of the content classification of the items of the transaction information is 60 to 69%. In the case where the classification result is the fifth classification method, the accuracy of the content classification of the item of the transaction information is 50 to 59%. In the case where the classification result is the sixth classification method, the accuracy of the content classification of the items of the transaction information is 40 to 49%.

Thereafter, the transaction ledger service providing server 60 creates a user interface in the form of a ledger indicating the accuracy of the content classification of each item of transaction information (S40). More specifically, in the user interface, the contents of the items automatically classified for each transaction information are written, and a predetermined color is displayed for each transaction information based on the accuracy of the content classification for each item of the transaction information Reference). In FIG. 8, since the color can not be displayed properly in black and white, the color display according to the accuracy of the item content classification is replaced by the hatching for each transaction information. In FIG. 8, all the regions of each transaction information are displayed in color, but only a part of each transaction information (for example, a field column) may be colored if necessary.

For example, if the item classification result is the first classification method, and the accuracy of the content classification of the item of the transaction information is 90 to 99%, the corresponding transaction information can be displayed in the color of " If the classification result of the item classification is the second classification method, and the accuracy of the content classification of the items of the transaction information is 80 to 89%, the corresponding transaction information can be displayed in the color of " marginal orange ". Since the item classification result is the third classification method, when the accuracy of the content classification of the item of the transaction information is 70 to 79%, the corresponding transaction information can be displayed in the color of " If the classification result of the item classification is the fourth classification method, and the accuracy of the content classification of the item of the transaction information is 60 to 69%, the corresponding transaction information can be displayed in the color of " marginal orange ". If the classification result of the item classification is the fifth classification method and the accuracy of the content classification of the item of the transaction information is 50 to 59%, the corresponding transaction information can be displayed in the color of "performance yellow". Since the item classification result is the sixth classification method, if the accuracy of the content classification of the item of the transaction information is 40 to 49%, the corresponding transaction information can be displayed in the color of " orange ".

In this way, the transaction book service server 60 automatically classifies and writes the contents (item information) of the items for each transaction information. Thus, it is possible to solve the conventional problem (troublesome, long time-consuming, trouble of entry error of item contents, etc.) that the user has directly written.

Then, if the accuracy of the item content classification is displayed in color by transaction information as described above, the user can select a few transaction information (that is, transaction information with low accuracy of item classification) Since only the contents of the item can be checked, the error rate of entry of the item contents can be minimized.

Then, the transaction ledger service providing server 60 transmits a book-shaped user interface (see FIG. 8) to the corresponding user terminal 10 in which item and accuracy are displayed for each transaction information (S50).

Accordingly, the user can check the accuracy of the item and the content classification for each transaction information in the user interface on the terminal 10.

Thereafter, if the user intends to modify the contents of the item of the specific transaction information in the user interface, the user selects the corresponding transaction information to be modified (S60). More specifically, it will click on the field of the transaction information to be modified. For example, when the user wants to modify "transaction date; 2/3 day, client: KCP-settlement, item content; textbook / book" among the transaction information illustrated in FIG. 8, , The contents of the item), and then press the left push switch of the mouse once. Accordingly, an item selection signal of specific transaction information (i.e., transaction date; 2/3 day, customer, KCP-settlement, item content, textbook / book) is generated and transmitted through the network 20 to the transaction- Lt; / RTI > That is, when there is a request to modify the item contents of the user, the transaction service providing server 60 may present a certain number of recommendation contents for the selected transaction information as described below. In selecting the transaction information to be modified, the user will mainly select transaction information with a low accuracy of classification of items. The fact that the classification of the item's content classification is low means that it is likely that it is relatively misclassified. In particular, the lower the accuracy of the content classification of the item is, the darker the color is displayed, so the user can easily grasp which transaction information should be checked first.

The transaction ledger service providing server 60 recommends the contents of a specific number (for example, within 5) of items of the specific transaction information (S70). In this case, the transaction ledger service providing server 60 can provide about five items of recommendation items according to the item content classification method of the specific transaction information or the accuracy of the item content classification.

When the user selects any one of the recommendation item contents from about five recommendation item contents, the corresponding signal (that is, the recommendation item content selection signal) is transmitted to the transaction book service server 60 (S80).

Upon receipt of the recommendation item content selection signal from the user terminal 10, the transaction ledger service providing server 60 updates the user interface based on the selected recommendation content (S90). That is, the transaction ledger service providing server 60 modifies the contents of the current item of the specific transaction information to the contents of the selected recommendation item. In this case, the accuracy indication of the modified specific transaction information may follow the previous display color. Alternatively, the accuracy indication for the particular transaction information modified by the user as if the item was modified as such would be colorless, unlike the previous display color.

Then, the transaction ledger service providing server 60 transmits the updated transaction ledger interface (i.e., GUI type user interface) to the user terminal 10 (S100).

Thereafter, finally, the transaction ledger service providing server 60 transmits a confirmation signal from the corresponding user terminal 10 (i.e., a user interface (transaction ledger interface) in the form of a book in which the accuracy of item content classification is indicated for each transaction information (For example, a form of a bookkeeper, a simple book, or a journal) based on transaction information that is displayed on the current transaction account interface.

FIG. 9 and FIG. 10 are flowcharts for more specifically illustrating the item content classification process for each transaction information shown in FIG.

The transaction book service server 60 automatically classifies the items of the transaction information by automatically selecting items previously selected by the user (member, for example, a cost item or an expense item) Based on the transaction information in the database 40 (S130).

If the user (member) has previously selected the item of the transaction information, the contents of the item of the transaction information are classified into the previously selected item (first classification method) (S132).

As a result of the determination in step S100, if there is no content of the previously selected item, the transaction ledger service providing server 60 determines whether there is a member who has traded with the account of the transaction information (S134).

If there is a member who has traded with the trading partner of the corresponding transaction information, the transaction ledger service providing server 60 determines whether there is a member of the same type of business with the user among the members who have traded with the trading partner of the corresponding transaction information (S136). Here, since the membership information is stored in the database 40 in advance, it can be determined based on this information.

If there is a member of the same type of business as the user, the transaction ledger service providing server 60 classifies the contents of the item most selected by the members of the same type of industry into the transaction information, Method) (S138).

On the other hand, if there is no member in the same kind of business as the user, the transaction book service server 60 transmits the contents of the items most selected by the members of the business type different from the user to the transaction information, (Third classification method) (S140).

If it is determined in step S134 that there is no member who has made a transaction with the trading partner of the transaction information, it is important to know the business type of the trading partner of the transaction information in order to classify the item information of the transaction information. (S142). ≪ / RTI > Here, the business type of the customer of the transaction information may be known through collected transaction information (that is, scraping data) or DB (not shown) of the member company (member shop).

When the business type of the business entity of the transaction information is identified in this way, the transaction ledger service providing server 60 classifies the contents of the predetermined item into the contents of the item of the corresponding transaction information by referring to the business type of the user and the business type of the corresponding business partner The fourth classification method) (S144).

On the other hand, if it is determined in step S142 that the business type of the customer of the transaction information can not be known, the transaction ledger service providing server 60 determines whether the business type of the customer is included in the business name of the customer in step S146. For example, in the case where the business partner's name is "@@ gas station", "%% restaurant", "&& mart", etc., the gas station, restaurant,

If the keyword is extracted from the business partner's mutual name, the transaction book service providing server 60 transmits the content of the predetermined item based on the business type of the user and the business type of the corresponding business partner in keyword extraction to the corresponding transaction information (Fifth classification method) (S148).

On the contrary, when the keyword that is classified as the business type is not extracted within the mutual business partners, that is, when there is no business keyword in the mutual business of the corresponding business partner, the transaction book service providing server 60 searches the similar The business type is estimated (S150). For example, if the business partner's name is "Kagurepo Klee", the business type of hairdressing salon can be estimated as similar business type for the corresponding business.

If the similar business type for the corresponding business partner is estimated, the transaction ledger service providing server 60 classifies the contents of the predetermined items on the basis of the business type of the user and the similar business type estimated for the business partner into the content of the item of the corresponding transaction information (Sixth sorting method) (S152).

As described above, the transaction book service server 60 sequentially performs the classification methods from the first classification method to the sixth classification method, and determines which classification method is classified among the six classification methods for each item of transaction information As shown in FIG.

In addition, the transaction book service providing method of the present invention described above can be implemented as a computer readable code on 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. Examples of the computer-readable recording medium include ROM, RAM, CD-ROM, magnetic tape, floppy disk, optical data storage, and the like. In addition, the computer-readable recording medium may be distributed over network-connected computer systems so that computer readable codes can be stored and executed in a distributed manner. And, functional programs, codes and code segments for implementing the above method can be easily inferred by programmers of the technical field to which the present invention belongs.

As described above, an optimal embodiment has been disclosed in the drawings and specification. While specific terms have been employed herein, they are used for the purpose of describing the invention only and are not used to limit the scope of the invention as defined in the claims or the claims. Therefore, those skilled in the art will appreciate that various modifications and equivalent embodiments are possible without departing from the scope of the present invention. Accordingly, the true scope of the present invention should be determined by the technical idea of the appended claims.

10: User terminal
20: Network
30: Source of transaction information
40: Database
60: a transaction book service providing server
62: Scraping section
64: a transaction ledger interface generating section
66: Output section
67: Item classification section
68:
69: User interface generation unit
69a: Recommendation

Claims (20)

A scraping unit for collecting at least one transaction information of a user;
A transaction book that generates an account book interface based on the transaction information and displays the accuracy of the content of each transaction information item and presents the content of the recommendation item for the transaction information selected by the user based on the displayed accuracy; An interface generation unit; And
And an output unit for sending the transaction ledger interface to the user terminal,
The transaction ledger interface generation unit
If the content of the item of the transaction information is automatically classified according to the execution of the plurality of sequential classification methods, the accuracy of the content classification of the item of the transaction information is determined according to the classification method corresponding to the content classification result of the item And an accuracy determining unit
The accuracy determination unit may determine,
Wherein the classification method automatically performed in correspondence with the classification result is a classification method in which the transaction information and the classification condition required for classification are different from each other and the classification method is selected from among a plurality of classification methods with different classification accuracies of classification results, Determine the accuracy range of the classification
Transaction book service providing device. The method according to claim 1,
The transaction ledger interface may include:
And recommending the contents of the recommended items within a predetermined number of times. The method according to claim 1,
The transaction ledger interface may include:
Wherein the transaction service providing unit assigns a different color to each transaction information according to the accuracy of content classification of the items of the transaction information. The method according to claim 1,
The transaction ledger interface may include:
An item classifying unit for automatically classifying the contents of the items of the transaction information, sequentially performing the plurality of classifying methods, and classifying the contents of items according to which classifying method; And
The contents of the items classified by the transaction information are automatically written and a user interface corresponding to the transaction ledger interface showing the accuracy of the content classification of the item is generated, And a user interface generating unit for presenting the recommended item contents. The method of claim 4,
Wherein the user interface generation unit comprises:
If there is a member who has traded with the supplier of the selected transaction information and there is a member in the same kind of industry as the user, a predetermined number of recommendation items are presented in order of the most used item among the items selected by the members of the same kind of industry for the selected transaction information And the transaction history service providing apparatus. The method of claim 4,
Wherein the user interface generation unit comprises:
If there is a member who has traded with the customer of the selected transaction information and there is no member in the same business as the user, the selected transaction information may include a predetermined number of recommendation items To the service provider. The method of claim 4,
Wherein the user interface generation unit comprises:
If there is no member who has made a transaction with the customer of the selected transaction information and knows the business type of the customer of the selected transaction information, the recommendation contents are presented with a predetermined number of recommendation contents predetermined with reference to the business type of the user and the business type of the corresponding customer Book service providing device. The method of claim 4,
Wherein the user interface generation unit comprises:
If there is no member who has made a transaction with the customer of the selected transaction information and the business type of the customer of the selected transaction information is not known, a keyword that is classified as a business type within the mutual supplier of the selected transaction information is extracted, And presents a predetermined number of recommendation contents determined in advance based on the business type of the customer. The method of claim 4,
Wherein the user interface generation unit comprises:
If there is no member who has made a transaction with the customer of the selected transaction information and there is no keyword that is classified into a business category by the customer of the selected transaction information without knowing the business type of the customer of the selected transaction information, Estimating a similar business type, and presenting a predetermined number of recommendation contents determined in advance based on the business type of the user and the similar business type estimated for the business partner. The method of claim 4,
The sequential classification method includes:
A first classification scheme for classifying the contents of the items of the transaction information into contents of items that have been previously selected;
A second sorting method of sorting contents of items selected most frequently by members of the same industry as the user into contents of items of the corresponding transaction information;
A third classification scheme for classifying contents of items selected most frequently by members of a business type different from the user into contents of items corresponding to the transaction information;
A fourth classification scheme for classifying the contents of the items determined in advance on the basis of the business type of the business type of the user and the business partner of the transaction information into the content of the item of the transaction information;
A fifth sorting method for sorting the contents of an item set in advance based on the business type of the user and the business type of the trading information of the corresponding transaction information according to the keyword extraction into the contents of the item of the transaction information; And
And a sixth sorting method of sorting the contents of the items determined in advance on the basis of the similar business type estimated for the business type of the user and the business partner of the transaction information into the content of the item for the transaction information Transaction book service providing device. The method of claim 10,
The item classification unit may classify,
And the classification is performed according to which classification method among the six classification methods the contents of the items of the transaction information are classified by sequentially performing the six classification methods. . A transaction book service providing method in a transaction book service providing apparatus,
A first step of collecting at least one transaction information of a user;
A transaction history interface for generating transaction information based on the transaction information, displaying the accuracy of the content of each transaction information item, and presenting the content of the recommendation item for the transaction information selected by the user based on the displayed accuracy, step; And
And a third step of sending the transaction ledger interface to the user terminal,
The second step comprises:
If the content of the item of the transaction information is automatically classified according to the execution of the plurality of sequential classification methods, the accuracy of the content classification of the item of the transaction information is determined according to the classification method corresponding to the content classification result of the item , ≪ / RTI >
Wherein determining the accuracy of the content classification comprises:
Wherein the classification method automatically performed in correspondence with the classification result is a classification method in which the transaction information and the classification condition required for classification are different from each other and the classification method is selected from among a plurality of classification methods with different classification accuracies of classification results, Characterized in that the accuracy range of the classification is determined
Method of providing transaction book service. The method of claim 12,
The second step comprises:
And the recommendation item contents limited within a predetermined number of times are presented. The method of claim 12,
The second step comprises:
Wherein a color of each transaction information is differentiated according to the accuracy of content classification of the items of transaction information. The method of claim 12,
The second step comprises:
Automatically sorting the contents of the items of the transaction information, sequentially sorting the plurality of classification methods, and classifying the contents of the items according to which classification method; And
The contents of the items classified by the transaction information are automatically written and a user interface corresponding to the transaction ledger interface showing the accuracy of the content classification of the item is generated, And presenting the content of the recommendation item. 16. The method of claim 15,
The step of presenting the content of the recommendation item,
If there is a member who has traded with the supplier of the selected transaction information and there is a member in the same kind of industry as the user, a predetermined number of recommendation items are presented in order of the most used item among the items selected by the members of the same kind of industry for the selected transaction information Wherein the transaction history service providing method comprises: 16. The method of claim 15,
The step of presenting the content of the recommendation item,
If there is a member who has traded with the customer of the selected transaction information and there is no member in the same business as the user, the selected transaction information may include a predetermined number of recommendation items And providing the transaction ledger service. 16. The method of claim 15,
The step of presenting the content of the recommendation item,
If there is no member who has made a transaction with the customer of the selected transaction information and knows the business type of the customer of the selected transaction information, the recommendation contents are presented with a predetermined number of recommendation contents predetermined with reference to the business type of the user and the business type of the corresponding customer Method of providing book service. 16. The method of claim 15,
The step of presenting the content of the recommendation item,
If there is no member who has made a transaction with the customer of the selected transaction information and the business type of the customer of the selected transaction information is unknown, a keyword that is classified into the business category within the mutual customers of the selected transaction information is extracted, And providing a predetermined number of recommendation contents determined in advance based on the business type of the customer. 16. The method of claim 15,
The step of presenting the content of the recommendation item,
If there is no member who has made a transaction with the customer of the selected transaction information and there is no keyword that is classified into a business category by the customer of the selected transaction information without knowing the business type of the customer of the selected transaction information, Estimating a similar business type, and presenting a predetermined number of recommendation contents determined in advance based on the business type of the user and the similar business type estimated for the business partner.

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