KR20230092048A - System and method for collecting business information and computer program for the same - Google Patents

Abstract

The operator information collection system includes a data collection unit configured to collect data related to operator information from one or more information holding organizations; a data recognizing unit configured to match the data to the plurality of data items using preset recognition rules for each of the plurality of data items; and a data storage unit configured to store values matched to the plurality of data items as standardized operator information. The data recognizing unit is configured to determine values matched to the plurality of data items by sequentially determining candidate data of the plurality of data items based on a preset order for the plurality of data items. The data recognizing unit determines candidate data of a data item that precedes in the matching order based on a preset rule for each of the plurality of data items, and determines candidate data of the preceding data item based on the preset rule. The value of the following data item in the matching order is determined, and a value matched to the preceding data item may be determined by erasing data determined as the value of the succeeding data item among the candidate data.

Description

Business operator information collection system and method and computer program for the same

Embodiments relate to a business operator information collection system and method and a computer program for the same, and more specifically, by collecting data from a plurality of organizations holding business operator information and standardizing the collected data through characteristics unique to business operator information. It is about a technology that can increase the utility value of the business operator information.

In economic activities between companies, business information such as business registration number, business type, type of business, address, representative name, etc. is often used. Accordingly, a service providing business information to trading companies or consumers is sometimes operated by companies or public institutions. For example, the Fair Trade Commission provides "identity information" of telecommunications distributors reported to cities, counties, and districts nationwide so that consumers can conduct safe transactions with accurate business information in the e-commerce market.

However, since the data standards for providing business information are not unified according to subjects such as public institutions, governments, and companies that provide business information, when a consumer or consumer receives business information from multiple institutions, each institution There are problems such as data inconsistency or duplicate data. However, a system for collecting and standardizing operator information provided by different organizations does not exist until now.

Registered Patent Publication No. 10-0575956

According to one aspect of the present invention, data is collected from a plurality of unspecified organizations holding operator information, the collected data is standardized through the characteristics of operator information, and the standardized data is refined and provided as standardized operator information. It is possible to provide a business operator information collection system that increases the utility value of information, a business operator information collection method, and a computer program therefor.

An operator information collection system according to an aspect of the present invention includes a data collection unit configured to collect data related to operator information from one or more information holding organizations; a data recognizing unit configured to match the data to the plurality of data items using preset recognition rules for each of the plurality of data items; and a data storage unit configured to store values matched to the plurality of data items as standardized operator information.

The data recognizing unit may be further configured to determine values matched with the plurality of data items by sequentially determining candidate data of the plurality of data items based on a preset order for the plurality of data items.

In an embodiment, the data recognizing unit determines candidate data of a data item preceding in the matching order based on the recognition rule for each of the plurality of data items, and among the candidate data of the preceding data item, the following data item and determine a value matched to each said data item by erasing the data determined to be the value of .

In one embodiment, the data recognizing unit is further configured to determine a unique candidate data of each of the plurality of data items as a value matched to the data item.

In one embodiment, the data storage unit is further configured to store exception word information for each preset data item. In this case, the data recognizer determines a value matched to the data item among the candidate data based on the exceptional word information, and selects a word not included in the exceptional word information among values matched with the data item in the exceptional word information. It is further configured to store in the data storage unit.

In one embodiment, the standardized operator information includes redundant data in which values matched to the data items are partially identical. At this time, the operator information providing system determines the priority of the redundant data based on the similarity of values matched to the data items or the calling pattern of the standardized operator information, and removes the duplicate data based on the priority. It further includes a configured data refinement unit.

In an embodiment, the data refining unit is further configured to generate error data for a rule set in advance for the data item based on a value matched to the data item in the redundant data.

The operator information providing system according to an embodiment determines new data of data related to the operator information, and the similarity between the new data and the standardized operator information associated with the new data or the call pattern of users for the new data. Based on the new data analysis unit configured to update the recognition rule for each of the plurality of data items further includes.

The operator information providing system according to an embodiment determines a call pattern of users by receiving a call request from users for the standardized operator information, and generates recommendation data based on a value matched to the call pattern and the data item. It further includes a data utilization unit configured to do so.

An operator information collection method according to an aspect of the present invention includes the steps of a business operator information collecting system collecting data related to business operator information from one or more information holding organizations; matching the data to a plurality of preset data items using a recognition rule for each of the plurality of data items, by the operator information collection system; and storing, by the operator information collection system, values matched with the plurality of data items as standardized operator information.

The matching with the plurality of data items may include determining candidate data of the plurality of data items sequentially based on an order set in advance for the plurality of data items by the business operator information collecting system, thereby matching the plurality of data items with the plurality of data items. and determining the matched value.

In one embodiment, the step of determining values matched with the plurality of data items may include, by the operator information collection system, candidate data of a data item that precedes in the matching order based on a recognition rule for each of the plurality of data items. determining; and determining, by the business operator information collection system, a value matched to each of the data items by erasing data determined as a value of a succeeding data item among candidate data of the preceding data item.

In one embodiment, the step of determining a value matched with the plurality of data items may include determining, by the operator information collection system, a unique candidate data of each of the plurality of data items as a value matched to the data item. include

In one embodiment, the step of determining the value of the following data item may include determining a value matched to the data item among the candidate data based on exception information for each data item set in advance by the business operator information collection system. includes At this time, the operator information collection method further includes the step of the operator information collection system storing, as the exception word information, words not included in the exception word information among values matched with the data items in the operator information collection system. do.

In one embodiment, the standardized operator information includes redundant data in which values matched to the data items are partially identical. In this case, the operator information providing method may include determining, by the operator information collection system, a priority among the redundant data based on a similarity of values matched to the data items or a calling pattern of the standardized operator information; and removing, by the operator information collection system, the redundant data based on the priority.

The operator information providing method according to an embodiment further includes generating, by the operator information collecting system, error data for a rule preset in the data item based on a value matched to the data item in the redundant data. do.

The operator information providing method according to an embodiment includes the step of determining, by the operator information collection system, new data of data related to the operator information; and updating, by the operator information collection system, a recognition rule for each of the plurality of data items based on a similarity between the new data and the standardized operator information associated with the new data or a call pattern of users for the new data. contains more

A method for providing operator information according to an embodiment includes: determining, by the operator information collecting system, call patterns of users by receiving users' call requests for the standardized operator information; and generating, by the operator information collection system, recommendation data based on a value matched to the call pattern and the data item.

The computer program according to one aspect of the present invention is for executing the operator information collection method according to the above-described embodiments in combination with hardware, and may be stored in a computer-readable recording medium.

According to the business operator information collection system and method according to an aspect of the present invention, it is possible to embrace data of various standards from a plurality of organizations in relation to business operator information, recognize the meaning of the contents of the accumulated data, and unify it. By standardizing according to the format, there is an advantage of being able to generate standardized operator information.

Using the business operator information collection system and method according to one aspect of the present invention, it is possible to standardize data constituting business operator information according to a unified form and to merge and/or delete redundant data through data priority definition. There is an advantage in maximizing the utility value of standardized operator information by refining data.

1 is a schematic block diagram of a business operator information collection system according to an embodiment.
2 is a flowchart illustrating each step of a method for collecting operator information according to an embodiment.
3 is a conceptual diagram illustrating a process of determining each column value of operator information in a method for collecting operator information according to an embodiment.
4 is a flowchart illustrating each step of a process of removing redundant data and detecting an error in a method for collecting operator information according to an embodiment.
5 is a flowchart illustrating each step of a process of updating a standard form by analyzing new data in a method for collecting business operator information according to an embodiment.

Hereinafter, with reference to the drawings, look at the embodiments of the present invention in detail.

1 is a schematic block diagram of a business operator information collection system according to an embodiment.

Referring to FIG. 1, the operator information collection system 3 according to this embodiment collects operator information from one or more information holding organizations 11-13, and standardizes the collected operator information according to a predetermined standard. It functions to transmit operator information to the information consumer's user device 21-23.

The information holding institutions 11 to 13 in this specification are arbitrary institutions that provide business information such as business registration number, business type, type of business, address, representative name, etc., and may correspond to companies, public institutions, or the government. For example, the information holding organization (11-13) may be, but is not limited to, a NTS server that provides electronic tax invoice information, and is a server of an organization that operates a service itself that provides business information, or a company's fund management. It may be any server that utilizes operator information in its operation, such as a Cash Management Service (CMS) or Enterprise Resource Planning (ERP) system.

In addition, the user devices 21 to 23 are devices used by an information consumer who wants to receive and use standardized operator information from the operator information providing system 3, and is a mobile communication terminal such as a smartphone, a laptop computer, or a personal device. A computing device such as a computer or a server associated with a CMS or ERP system in a company or used by a company may correspond to the user devices 21 to 23 .

The operator information providing system 3 according to the embodiments receives operator information provided by the information holding organizations 11 to 13 in an independent format, converts it into a standardized format, and converts the standardized operator information to the user of the information consumer. It can be transmitted to devices 21-23. For the above operation, the operator information collection system 3 is configured to be communicatively connected to the information holding organization 11-13 and the user device 21-23 through a wired and/or wireless network.

The communication method of the present specification may include all communication methods capable of networking between objects through wired and / or wireless networks, and is not limited to wired communication, wireless communication, 3G, 4G, or other methods. . For example, wired and/or wireless communication networks include Local Area Network (LAN), Metropolitan Area Network (MAN), Global System for Mobile Network (GSM), Enhanced Data GSM Environment (EDGE), High Speed Downlink Packet Access (HSDPA) ), W-CDMA (Wideband Code Division Multiple Access), CDMA (Code Division Multiple Access), TDMA (Time Division Multiple Access), Bluetooth, Zigbee, Wi-Fi, VoIP ( Voice over Internet Protocol), LTE Advanced, IEEE802.16m, WirelessMAN-Advanced, HSPA+, 3GPP Long Term Evolution (LTE), Mobile WiMAX (IEEE 802.16e), UMB (formerly EV-DO Rev. C), Flash-OFDM, Refers to a communication network by one or more communication methods selected from the group consisting of iBurst and MBWA (IEEE 802.20) systems, HIPERMAN, Beam-Division Multiple Access (BDMA), Wi-MAX (World Interoperability for Microwave Access), and ultrasound-enabled communication It can be done, but is not limited thereto.

The number of information holding organizations 11-13 and user devices 21-23 and the device type of the user devices 21-23 shown in the drawings of this specification are merely exemplary, and the operator information providing system 3 and It will be readily understood by those skilled in the art that the actual number or type of communicable information holding organizations and user devices is not limited.

Also, the devices described herein may have aspects that are entirely hardware, or partly hardware and partly software. For example, each unit constituting the business operator information collection system 3 and each module or unit included in each system, device, server, etc. communicating with it provides data in a specific format and content in an electronic communication method. Devices for receiving and related software may be collectively referred to. In this specification, terms such as "unit", "module", "server", "system", "platform", "device" or "terminal" are intended to refer to a combination of hardware and software driven by the hardware. do. For example, the hardware herein may be a data processing device including a CPU or other processor. Also, software driven by hardware may refer to a running process, an object, an executable file, a thread of execution, a program, and the like.

In one embodiment, the operator information collection system 3 may be communicatively connected to one or more information holding organizations 11-13 through a dedicated line. Further, in one embodiment, the operator information collection system 3 may be configured to perform communication with the user devices 21-23 in a call method using a URL (Uniform Resource Locator). For example, the operator information collection system 3 may provide operator information to user devices 21 to 23 based on a predefined application programming interface (API).

However, the communication method between the operator information collection system 3, the information holding organization 11-13, and the user device 21-23 according to the embodiments is not limited to what is described herein.

In one embodiment, the operator information providing system 3 includes a data collection unit 31 , a data recognition unit 32 and a data storage unit 33 . In one embodiment, the operator information providing system 3 further includes a data purification unit 34 . Also, in one embodiment, the operator information providing system 3 further includes a new data analysis unit 35 . Furthermore, in one embodiment, the operator information providing system 3 further includes a data utilization unit 36 .

In this specification, each device constituting the business operator information collection system 3 is not necessarily intended to refer to a separate physically distinct component. That is, in FIG. 1, each unit 31-36 constituting the business operator information collection system 3 and a database (DB) or detailed unit included in each unit 31-36 are separated from each other. Although shown as a block, this functionally divides the operator information collection system 3 by the operation executed by it. Depending on embodiments, some or all of the aforementioned parts may be integrated into the same device, or one or more parts may be implemented as a separate device physically separated from other parts. For example, each device constituting the business operator information collection system 3 may be components communicatively connected to each other under a distributed computing environment.

The data collection unit 31 is configured to collect data related to operator information from one or more information holding organizations 11-13. At this time, data related to operator information is operator information provided by each information holding organization 11-13 in an independent form, and raw data before processing such as standardization by operator information collection system 3 is performed. it means.

The data recognition unit 32 is configured to match the raw data of the business operator information received by the data collection unit 31 with a plurality of preset data items. In this case, the plurality of data items means the division of individual information items constituting the standardized operator information, and may be, for example, each column of a database. Data items are set according to characteristics of operator information in order to standardize and store operator information, and may include, for example, one or a plurality of items exemplified in Table 1 below, but are not limited thereto.

Company Registration Number Business Closure Information Registrant ID Classification of businesses Date of renewal of business closure information Registration date business type business number Business tax type change date Modifier ID Business company name Business corporation registration number date of modification Business representative name business code business fax number business status Postal code of representative business place Business Notice Notice Mailing address of representative business place Business person in charge Detailed address of representative business place Additional business information Business representative industry code business memo business name business latitude Business representative business status code business hardness business name

The data recognizing unit 32 may match raw data provided in an independent form by each information holding organization 11 to 13 with a form of standardized business information composed of the above-described data items. In this case, the data recognizer 32 may match raw data to data items in a manner of sequentially determining candidate data of each data item based on a preset order for each data item.

More specifically, the data recognition unit 32 matches each data value of raw data with a data item according to a recognition rule for each data item, determines the candidate data of the preceding data item, and then determines the data item that follows the next data item. A value to be matched with each data item may be determined by deleting the data for which the recognition result is determined as a result of determining the candidate data for . This will be described later in detail with reference to FIGS. 2 and 3 .

The data storage unit 33 is configured to store values matched to a plurality of data items from raw data as standardized operator information. To this end, the data storage unit 33 includes an operator DB 331 in which standardized operator information is stored. In addition, the data storage unit 33 may include a form DB 332 in which form information of standardized operator information composed of the above-described data items and recognition rules for standardizing raw data of different forms is stored. there is.

In one embodiment, the form DB 332 of the data storage unit 33 includes exception word information (eg, exception word dictionary) for each data item to facilitate matching of expressions that do not match data items based on rules. Including, among data matched to a specific data item through sequential assignment and deletion of candidate data, expressions not previously registered as exception words are newly stored as exception word information, thereby facilitating data matching in the future.

Since the information holding organizations 11 to 13 provide business operator information in their own form, standardized business operator information through the matching process by the data recognition unit 32 overlaps with only partially identical values matched to data items. It may contain data. In this case, the data refiner 34 functions to detect redundant data in the standardized operator information and remove redundant data through data merging and/or deletion. For example, the duplicate removal unit 341 of the data refining unit 34 determines the priority of duplicate data based on the similarity of values matched to data items or the calling pattern of standardized operator information, and removes duplicate data accordingly. can be removed

In one embodiment, the data cleaning unit 34 further includes an error detection unit 342. The error detection unit 342 functions to generate error data for a matching rule of a data item based on values matched to each data item in the redundant data detected by the duplicate removal unit 341 . The operator information providing system 3 can reduce the possibility of future errors by updating the matching rule between each data item and data value of the form DB 332 based on such error data.

The new data analysis unit 35 analyzes the new data based on the similarity with the existing business operator information related to the new data generated from the information holding institution and the call patterns of information consumers for the business information. can do. In addition, the new data analysis unit 35 may selectively add standardized new data to the standardized operator information based on the analysis result.

The data utilization unit 36 receives a call request for operator information from the user device 21-23, and accordingly, provides operator information that meets the user's call request among standardized operator information stored in the operator DB 331 to the user. Devices 21-23 may be provided. In this specification, a call request refers to specifying operator information to be retrieved or received by designating a specific operator or one or more information items of operator information.

In one embodiment, the data utilization unit 36 may perform a function of generating recommendation data of business information that is expected to be of particular interest to the information consumer and providing it to the user devices 21 to 23 . For example, the data utilization unit 36 analyzes call patterns of users for operator information, and provides operator information including a value of a specific data item corresponding to the call pattern in standardized operator information as recommendation data. can The specific type and process of recommendation will be described later in detail.

2 is a flowchart illustrating each step of a method for collecting operator information according to an embodiment. For convenience of explanation, a method for collecting business operator information according to the present embodiment will be described with reference to FIGS. 1 and 2 .

First, the data collection unit 31 of the operator information collection system 3 may collect operator information-related data from one or more information holding organizations 11 to 13 (S11). For example, the data collection unit 31 is communicatively connected to the information holding organization 11-13 through a direct connection method between the operator information collection system 3 and the server of the information holding organization 11-13 to collect data. It can be received, but is not limited thereto.

The data collecting unit 31 may store data collected from the information holding organizations 11 to 13 in a virtual DB table. At this time, the table consists of, for example, only the title and body so that data of different specifications can be stored for each information holding organization 11-13 as it is, and each data received from the information holding organization 11-13 is stored in one column. It can be. For example, the data collection unit 31 may classify the received data by assigning unique identifiers to the received data in the order of reception.

The data recognition unit 32 of the operator information collection system 3 recognizes the contents of the data collected by the data collection unit 31 by utilizing the characteristics of the operator information to recognize what kind of data it is (S12), Based on the recognition result, raw data provided by the information holding organizations 11-13 may be matched with standardized data items of the form DB 332 (S13).

At this time, in order to increase the accuracy of recognition and reduce the possibility of being recognized as the wrong type of information, the data recognition unit 32 sequentially compares one raw data with data items (eg, each column) of a standard format to determine candidate rankings. By designating and deleting matched data, the content of raw data can be recognized and matched to a standard form.

3 is a conceptual diagram illustrating a process of determining each column value of operator information in a method for collecting operator information according to an embodiment.

Referring to FIG. 3, a data package 400 corresponding to raw data of operator information has been received from an information holding institution, and the data package 400 includes 3078168243 (401), Gane Kim (402), Gil-dong Hong (403), and Seoul City (404). ), and the strings of the restaurant 405 are assumed to be included. At this time, assuming that each column (ie, data item) of the standard form of business information is composed of business number, type of business/type of business, business company name, representative name, and representative address, in the business operator information collection method according to the embodiments, each column By designating the order of the columns in advance, values corresponding to each column can be sequentially deleted from the data package 400 and recognized. For example, it is assumed that recognition is performed in the order of business number, type of business/type of business, business company name, representative name, and representative address.

A character string corresponding to each column from the data package 400 may be designated as candidate data after being recognized. For the process of recognizing candidate data, taking the business operator number recognition process as an example, extracting a string consisting of 10 numbers, 12 letters including numbers and hyphens (-), or letters among "one, three, four, six, seven eight nines", the corresponding character string Recognition rules may be set to recognize as an operator number.

In one embodiment, the string extracted in this way may be converted into a form of 3 numbers - 2 numbers - 5 numbers, which is a component of the business operator number. To this end, a string consisting of 10 numbers without a hyphen can be separated into 3, 2, and 5 numbers and hyphens can be inserted, and a string consisting of Korean characters can be converted into numbers and then separated to insert hyphens. Also, if the number contains hyphens in a configuration other than 10 digits or between 3 numbers - 2 - 5, such as 02-1234-5678, it can be separated into 3 numbers - 2 - 5 after removing the hyphen. .

In one embodiment, for a format that business information cannot have, such as a leading 0, this may be designated as an exclusion rule, and other numeric information other than business number, such as 02-1234-5678, may be filtered.

In addition, when explaining the process of recognizing the type of business and type of business, from the string in the data package 400, "~ up", "~ agency" such as system operation and management, personal credit information management, fintech service, advertising agency, public relations agency, etc. It is possible to recognize a preset word as a type of business/type of business, such as a word in which a preset character is included in a specific position, or a word whose meaning itself has attributes of a type of business or type of business, such as a clinic, service, real estate, or fishing. In addition, a recognition rule may be determined to learn words that can be business types and words that can be business types using electronic tax invoices, business type information of business registration certificates, item information, and the like, and designate these words as candidate data.

In one embodiment, even if it is not defined as a recognition rule, a character string stored as a corresponding column value through past data analysis is stored as exception word information, and a character string including the exception word is used as candidate data by referring to the exception word information in the data recognition process. may decide For example, the exceptional word information has the form of an exceptional word dictionary, and a character string registered in the exceptional word dictionary according to a recognition rule may be determined as candidate data of a corresponding column such as business type/type of industry.

However, since the recognition and exclusion rules for business information and business type/type of business described above may differ depending on the system of the target country where the embodiment of the present invention is implemented, the scope of the present invention is limited by the rules described in this specification. It is not.

Through the above operation, each character string of raw data of business information can be classified into one or more data items and its meaning can be recognized. In this case, the column for recognizing the meaning of the raw data may be the same as the standardized form of operator information, but is not limited thereto, and may include, for example, some of the data items described above with reference to Table 1.

It is assumed that 3078168243 (401) of the character strings 401 to 405 of the data package 400 shown in FIG. 3 is recognized as candidate data for a business operator number. In this case, since no other candidate data exists for the business operator number and only one candidate data is confirmed, the meaning of 3078168243 (401) is determined as the business operator number. At this time, the character string for which the data item is determined in the data package 400 is deleted, and the recognition is performed in a manner of sequentially determining whether each data item corresponds to the remaining character strings.

In the example of the drawing, it is assumed that recognition of the type of business/type of business is performed next to the business number for which data is confirmed, and as a result of character-based recognition, Gane Kim 402 and restaurant 405 are determined as candidate data of the type of business/type of business. For example, Gane Kim 402 may be designated as candidate data 1 and restaurant 405 may be designated as candidate data 2 according to the arrangement order in the data package 400 .

Next, it is possible to recognize a corresponding character string based on the rules of the operator company name data item following the type of business/industry, and check whether the candidate data of the preceding data item is recognized as the candidate data of the following data item. When Kimgane 402 is recognized as the operator company name in the operator company name recognition result data package 400, Kimgane 402 is changed from the second candidate data of the business type/type of business to the operator company name candidate data, and the business type/type of business In the candidate data of , Gane Kim 402 is deleted and the restaurant 405 is changed to the first candidate data. As a result of checking the entire data package 400, only Kimgane 402 is recognized as the operator's company name, and when other operator's company names are not recognized, Kimgane 402 is determined as candidate data for the operator's company name.

Similarly, for the representative name, which is a data item following the operator company name, the character strings determined as the values of other data items are deleted and the rest is recognized, but the preceding data items, business number, business type/type of business, and operator company name Candidate data is also recognized, and in the example of FIG. 3, as a result, Hong Gil-dong 403 can be recognized as representative name candidate data.

As in the process described above, candidate data for each item based on a preset order and recognition rule for a plurality of data items (in the example of FIG. Recognition is performed by sequentially determining and erasing them from the data package 400, but recognition rules may also be applied to candidate data of preceding data items in subsequent data items. As a result of sequential recognition, when the candidate data of the preceding data item is finally determined as the value of the following data item (for example, when there is only one candidate data of the following data item), the candidate data duplicated in the following data item is preceded. By deleting the candidate data of the data item to be selected, it is possible to determine a value matched to each data item and reduce the possibility of misrecognition.

In an embodiment, a character string included in exception word information may be determined as candidate data by referring to exception word information in a data recognition process. For example, exception word information may have a form of an exception word dictionary.

For example, a data package containing the string "Arduino Study" was collected, but a string identified as a business type/industry based on the recognition rule was not searched, and "study" exists as an exception word for the business type/industry. suppose to do In this case, "Arduino study" including an exception word can be determined as the candidate data for the type of business/industry. In one embodiment, as described above, when "Arduino Study" is finally determined as the business type or industry name as a result of matching in a manner of erasing data of other data items, other than the already registered character string among the determined character strings Exception word information may be updated to store a character string, that is, "Arduino" as a new exception word.

Referring back to FIGS. 1 and 2 , the data recognizer 32 may store data values for each data item defined by the above process in the operator DB 331 as standardized operator information. For example, a 10-digit number determined as an operator number through the above-described data recognition process may be stored in a "business operator number" column of standardized operator information. At this time, the string of the collected data is changed by adding hyphens between 3, 2, and 5 numbers so that the 10-digit number is in the form of 000-00-00000, or deleting the explanatory phrase from the string of the collected data. can also be processed.

In one embodiment, the business information collection system 3 determines whether the character string matched with the business type/type of business name matches the actual type of business type and word of the business type through communication with the National Tax Service server (not shown) or the National Statistical Office server (not shown). It can also be confirmed by comparing it with the standard attribute industry code, Korea Standard Industrial Classification, etc.

In one embodiment, the data refining unit 34 of the operator information collection system 3 identifies redundant data in which a value matched to a data item in the standardized operator information is partially identical, and duplicates data through merging or deletion of the data. Data can be removed (S14).

4 is a flowchart illustrating each step of a process of removing redundant data and detecting an error in a method for collecting operator information according to an embodiment.

Referring to FIG. 4, in this embodiment, the business operator information collection system sorts standardized business operator information based on the value of a predetermined data item, so that some data items (eg, business number, business name, etc.) are the same, but some other data items are the same. Duplicate data with inconsistent item values may be derived (S21).

At this time, the operator information collection system determines the priority between redundant data based on the existing data distribution of the standardized operator information or the call pattern of the standardized operator information (S22), and the data with the highest priority is called real data (real data). ) (S23), the redundant data can be removed by merging and/or deleting the remaining redundant data based on this (S24). For example, the operator information collection system may perform redundant data removal so that operator information of one operator includes only one piece of data in each column.

More specifically, in the case of determining the priority of the value of the first column (eg, type of business) of a specific business operator among duplicate data by identifying existing items in which the phrases written in the column are common when compared with duplicate data, in existing similar items An item having a similar value of the business operator data and the value of the second column (eg, type of business) may be extracted. Next, based on the values of the first column of extracted similar items, it is possible to prioritize values to be described in the first column of the target business operator.

For example, as a result of collecting data from a number of information-holding organizations with a business name of "OO Market" and a business name of "sales", the business name is "wholesale", "wholesale", "retail", "service", etc. Assume that different data are collected. In this case, in order to prioritize redundant data with different business types, the value of the business type column among the existing business operator data is "wholesale and retail", "wholesale", "retail", and "service", and the value of the industry column is "OO Data similar to “sales business,” which is the business name of “market,” can be extracted as a similar business operator. If the type of business of the similar business operators extracted in this way is "retail" in most cases, the business name of "retail" among the operator data of "OO Market" is considered as real data, and redundant data can be removed based on this.

Alternatively, a score may be assigned to each data package detected as redundant data, and column values may be prioritized based on the score. In this case, the score given to the data package may be determined based on whether operator information is verified and/or the number of calls for target operator data.

For example, a higher score is given to a data package that has been verified by verifying whether the detailed address of the business data, whether the name of the representative is missing, whether the phone number is missing, or whether the detailed address or phone number actually exists. can do. In addition, based on the information with the largest number of data calls in each data package, scores are set for each data item so that the higher the number of calls, the higher the score (e.g., business registration number 5 points, business name 4 points, representative name 3 points) point, representative address 3 points, representative phone number 1 point, etc.), the sum of call scores for each column of each data package, e.g., [Package 1: business registration number 5 + business name 4 + representative name 3], [Package 2: business registration number 5+representative address 3+representative phone number 1], etc., the scores for each package are summed up, and the data package with the higher sum score is regarded as real data, and redundant data can be removed based on this.

Meanwhile, the occurrence of duplicate data as described above is because error data is collected from raw data of operator information. In order to prevent this, in one embodiment, the operator information providing system detects a rule error by generating error data for the recognition rule of each data item based on the value matched to the data item in the above-described redundant data (S23 ), rules for data recognition and matching of standardized operator information may be updated to remove errors (S24). The above process may be performed for each column of standardized operator information.

For example, if there is a missing data item from business operator data collected from a specific information holding institution, the business operator is specified through the business operator number, which is a mandatory value of the business operator data, and the data determined as redundant data and other redundant data Differences in column values between livers can be detected. For example, as a result of checking specific redundant data, if there is a difference with other data because the string "<br>" is further included in the entire column value, the string "<br>" is created as error data, and in the future Recognition rules can be updated to automatically delete the string "<br>" when recognizing imported business data.

Referring back to FIGS. 1 and 2, in one embodiment, the new data analysis unit 35 of the operator information collection system 3 generates new data in operator-related data of the information holding organizations 11-13. , New data can be analyzed based on the similarity between new data and existing standardized operator information and users' call patterns for operator information, and the new data can be selectively reflected in standardized operator information.

5 is a flowchart illustrating each step of a process of updating a standard form by analyzing new data in a method for collecting business operator information according to an embodiment.

Referring to FIG. 5, the business operator information collection system recognizes new data newly collected as standardized business operator information (S31) and compares the new data with the value of similar data items of existing business operator information. A value of a column that does not have data or is repeatedly collected more than a preset number of times may be determined (S32). In addition, the operator information collection system determines the importance of the data based on the semantic similarity of the search pattern for the new data and the value of the new data (S33), and the operator standardized to reflect the new data whose importance is a certain level or higher. Data items of information can be updated (S34).

In one embodiment, updating a data item based on new data may include a change to the name of a data item of standardized operator information, and whether or not to change the name of the data item is determined by changing the character string of the data item before the change. It can be determined based on the calling pattern for the character string of the later data item.

For example, it is assumed that a column called "Company Introduction" exists in the existing standardized business information format, but a string of "company vision" repeatedly appears in business data provided by an information holding institution. In this case, the business information providing system checks whether the content of the text provided in connection with the "company vision" is the same as the value of the "company information" column of the existing business information, and the paragraph type in which both data are the same (e.g., core , provision, company vision, etc.) and/or the same words, it is possible to determine whether to change the "company information" column to the "company vision" column based on the importance of the string "company vision". . At this time, the importance of the "company vision" string may be determined based on which string has a higher call rate when comparing "company information" and "company vision" in the call patterns of users who call standardized operator information. However, it is not limited thereto.

In another embodiment, updating a data item based on new data may include a change to add a new value to a data item of standardized business operator information, and whether to add a new value depends on the string of the column value to be added and the existing value. It may be determined based on similarity of values matched to data items.

For example, if the word "NFT" appears in the data collected as new data for a specific business operator more than a certain number of times (eg, 5 times) as industry data, operator data containing "NFT" is compared to the existing standardized data. Similarity can be calculated by comparing with operator information. Calculation of the similarity may be determined based on the similarity between the string and "NFT", such as company introduction, representative message, investment information, etc. of existing business information. Since the calculation of the similarity can be performed based on any word similarity measuring technology known or to be developed in the future, a detailed description thereof is omitted in the present specification to clarify the subject matter of the present invention. For example, if the similarity value between the dictionary meaning of the industry of existing business information and the dictionary meaning of "NFT" exceeds a preset standard (eg, 0.8), "NFT" is set as one of the new industry values Recognition rule for industry data items can be reflected in

Referring back to FIG. 1, in one embodiment, the data utilization unit 36 of the operator information providing system 3 determines call patterns of users by receiving call requests from users for standardized operator information, and determines call patterns and Recommendation data based on values matched with data items may be generated and provided to user devices 21 to 23 of information consumers.

In one embodiment, the operator information providing system 3 receives characteristic information (eg, what kind of service the company provides) of the information consumer when calling for operator information from the user devices 21-23 of the information consumers, By collecting and analyzing call patterns for operator information for each information consumer's characteristics, operator information determined based on call patterns of other information consumers classified into similar categories can be provided to each information consumer as recommendation data.

For example, as a result of analyzing the type of business information requested by company A, which corresponds to a securities company, among information consumers, more than 80% of the business types of business operators in the business information inquired were "service", and among them, the industry was "meta". It is assumed that the case of "bus" is more than 60%. In this case, the business information providing system determines the type of "service business" determined based on the calling pattern of company A for company B, which is in the same securities industry as company A, or company C, which has a similar service structure to company A, among other information consumers. And business information of the "metaverse" industry or contents suggesting a search for such business information may be provided as recommendation data.

As another example, it is assumed that company A causes load by calling a large amount of operator information at once in the above example. In this case, business information of the "service" business type and "metabus" business type matching the calling pattern of company A is separately classified, and among the classified business information, changed or newly generated business information is used as recommendation data for company A. can also be provided.

In another embodiment, the operator information providing system categorizes standardized operator information based on one or more criteria, classifies and provides the categorized operator information based on location, type of business, type of business, etc. Alternatively, location information of the information consumer may be received from the user devices 21 to 23 of the information consumer, and business information corresponding thereto may be provided as recommendation data. Alternatively, the operator information providing system may provide recommendation data, such as information on a trend of change in the categorized operator information or information on a calling pattern thereof.

For example, the operator information providing system replaces address information of operator information with coordinate information, stores it in a column of standardized operator information, and provides operator information as a service in the form of a map based on the coordinate information, or/or Business information of business operators located within a predetermined distance from a specific location based on the address or selection of the information consumer may be provided in the form of commercial district information. For example, commercial area information may include information such as the names of businesses located in a specific area, the number of businesses, and types of business.

As another example, the operator information providing system provides information on the number of operators and/or trends in operator information according to business type or type of business, or uses coordinate-based information and business type/type of business information together to provide queue It is also possible to provide customized recommendation data. For example, if a prospective founder selects or inputs a specific region for a prospective entrepreneur, an industry or commercial district with a small number of entrepreneurs in the region may be extracted, and business items that may be recommended as new businesses may be provided as recommendation data.

As another example, the operator information providing system may provide a call pattern of operator information according to a time series flow or operator information pre-searched to correspond to the call pattern as recommendation data. For example, at 9:00 am, as banks open, the number of requests for business information for loan review increases. There is a case where there is a specific time or period (period) in which operator information is particularly required for each information consumer's characteristics, such as an increase in the number of requests for operator information. In this case, the operator information providing system identifies the data call pattern according to the time series flow, such as configuring the corporate operator information (separately separating only the corporate operator through the operator number in advance) for which a quarterly report is required as a data set in advance, A data set corresponding to a calling pattern may be provided as recommendation data.

Operations by the business operator information collection method according to the above-described embodiments may be at least partially implemented as a computer program and recorded on a computer-readable recording medium. Computer-readable recording media on which programs for implementing operations by methods according to embodiments are recorded include all types of recording devices in which computer-readable data is stored. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disk, and optical data storage devices. In addition, computer-readable recording media may be distributed in computer systems connected through a network, and computer-readable codes may be stored and executed in a distributed manner. In addition, functional programs, codes, and code segments for implementing this embodiment can be easily understood by those skilled in the art to which this embodiment belongs.

Further, each block or each step shown in the flowcharts herein may represent a module, segment or portion of code that includes one or more executable instructions for executing specified logical function(s). Also, in some alternative embodiments, it is possible for the functions mentioned in the blocks or steps to occur out of order. For example, two blocks or steps shown in succession may in fact be performed substantially concurrently, or the blocks or steps may sometimes be performed in reverse order depending on their function.

The present invention reviewed above has been described with reference to the embodiments shown in the drawings, but this is only exemplary, and those skilled in the art will understand that various modifications and variations of the embodiments are possible therefrom. However, such modifications should be considered within the technical protection scope of the present invention. Therefore, the true technical protection scope of the present invention should be determined by the technical spirit of the appended claims.

Claims (17)

a data collection unit configured to collect data related to operator information from one or more information holding organizations;
a data recognizing unit configured to match the data to the plurality of data items using preset recognition rules for each of the plurality of data items; and
A data storage unit configured to store values matched to the plurality of data items as standardized operator information,
The data recognition unit is further configured to determine values matched to the plurality of data items by sequentially determining candidate data of the plurality of data items based on a preset order for the plurality of data items.
According to claim 1,
The data recognition unit,
Based on the recognition rules for each of the plurality of data items, candidate data of a data item that precedes in the matching order is determined;
The operator information collecting system further configured to determine a value matched to each of the data items by canceling data determined as a value of a succeeding data item among candidate data of the preceding data item.
According to claim 2,
The data recognition unit is further configured to determine unique candidate data of each of the plurality of data items as a value matched to the data item.
According to claim 2,
The data storage unit is further configured to store exception word information for each preset data item,
The data recognizer determines a value matched with the data item among the candidate data based on the exceptional word information, and among the values matched with the data item, a word not included in the exceptional word information is used as the exceptional word information. Operator information collection system further configured to store in the data storage unit.
According to claim 1,
The standardized operator information includes redundant data in which a value matched to the data item is partially identical,
Further comprising a data refining unit configured to determine a priority among the redundant data based on a similarity of values matched to the data item or a call pattern of the standardized operator information, and to remove the redundant data based on the priority Operator information collection system.
According to claim 5,
The data refiner is further configured to generate error data for a rule set in advance for the data item based on a value matched to the data item in the redundant data.
According to claim 1,
Determines new data of the data related to the operator information, and recognizes rules for each of the plurality of data items based on similarity between the new data and the standardized operator information associated with the new data or a call pattern of users for the new data. Operator information collection system further comprising a new data analysis unit configured to update the.
According to claim 1,
Operator information collection further comprising a data utilization unit configured to determine call patterns of users by receiving call requests from users for the standardized operator information, and to generate recommendation data based on values matched to the call patterns and the data items. system.
Collecting, by an operator information collection system, data related to operator information from one or more information holding organizations;
matching the data to a plurality of preset data items using a recognition rule for each of the plurality of data items, by the operator information collection system; and
Including the step of the operator information collection system storing values matched with the plurality of data items as standardized operator information,
The step of matching the plurality of data items,
determining, by the operator information collection system, values matched with the plurality of data items by sequentially determining candidate data of the plurality of data items based on a preset order for the plurality of data items. How we collect information.
According to claim 9,
Determining a value matched to the plurality of data items,
determining, by the operator information collection system, candidate data of a data item that precedes in the matching order based on the recognition rule for each of the plurality of data items; and
and determining, by the operator information collection system, a value matched to each of the data items by erasing data determined as a value of a succeeding data item among candidate data of the preceding data item.
According to claim 10,
The determining of values matched with the plurality of data items may further include determining, by the business operator information collection system, unique candidate data of each of the plurality of data items as a value matched with the data items. collection method.
According to claim 10,
The step of determining the value of the succeeding data item includes determining, by the operator information collection system, a value matched to the data item among the candidate data based on exception information for each data item set in advance;
The business operator information collection method,
and storing, by the operator information collection system, words not included in the exception word information among values matched with the data items in the operator information collection system as the exception word information.
According to claim 9,
The standardized operator information includes redundant data in which a value matched to the data item is partially identical,
determining, by the operator information collecting system, a priority among the redundant data based on a similarity of values matched to the data items or a calling pattern of the standardized operator information; and
The operator information collection method further comprising removing, by the operator information collection system, the redundant data based on the priority.
According to claim 13,
The method of collecting business information further comprising generating, by the business operator information collecting system, error data for a rule preset in the data item based on a value matched to the data item in the redundant data.
According to claim 9,
determining, by the operator information collection system, new data of data related to the operator information; and
Updating, by the operator information collection system, a recognition rule for each of the plurality of data items based on a similarity between the new data and the standardized operator information associated with the new data or a call pattern of users for the new data. How business information is collected, including;
According to claim 9,
determining, by the operator information collection system, call patterns of users by receiving users' call requests for the standardized operator information; and
The method of collecting operator information further comprising generating, by the operator information collection system, recommendation data based on a value matched to the call pattern and the data item.
A computer program stored in a computer-readable recording medium combined with hardware to perform the business operator information collection method according to any one of claims 9 to 16.

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