JP2020187698A - Collation support device, collation support method, program, and recording medium - Google Patents

Abstract

To prevent wrong sticking of identification information.SOLUTION: In a collation support device 1 of the present invention, a storage unit 11 stores a subject list in which identification information is given to every subject, an acquisition unit 12 acquires text data, a collation unit 13 collates two or more types of the text data with the subject list, a calculation unit 14 calculates the reliability of every text data based on the collation, a determination unit 15 determines, as proper identification information, the identification information corresponding to the text data in which the reliability exceeds a threshold and the highest reliability is calculated.SELECTED DRAWING: Figure 1

Description

The present invention relates to a collation support device, a collation support method, a program, and a recording medium.

Generally, a sample (subject) such as blood is managed by, for example, a sample container to which a sample label is attached. Generally, the sample label is given identification information such as a name, a date of birth, a barcode, and an ID (identification) in order to identify the type of the subject (for example, Patent Document 1 and the like).

Japanese Unexamined Patent Publication No. 2006-106455

However, the identification information is given manually, for example, by a worker inspecting the subject based on the information written on the sample label. Further, the identification information is information managed by the worker side, and it is not always possible to collate the identification information with a subject list owned by a facility such as a hospital or a laboratory. Therefore, there is a possibility that human error such as addition of identification information that does not correspond to the subject or duplication of identification information may occur.

Therefore, an object of the present invention is, for example, to provide a collation support device, a collation support method, a program, and a recording medium capable of preventing misattachment of identification information.

In order to achieve the above object, the collation support device of the present invention
Including a storage unit, an acquisition unit, a collation unit, a calculation unit, and a determination unit,
The storage unit stores a subject list with identification information for each subject.
The acquisition unit acquires text data and
The collation unit collates two or more types of the text data with the subject list.
The calculation unit calculates the reliability of each text data based on the collation.
The determination unit is an apparatus that determines the identification information corresponding to the text data whose reliability exceeds the threshold value and whose highest reliability is calculated as appropriate identification information.

The collation support method of the present invention
Including acquisition process, collation process, calculation process, and judgment process
The acquisition process acquires text data and
In the collation step, two or more types of the text data are collated with a subject list to which identification information is attached to each subject.
In the calculation step, the reliability of each text data is calculated based on the collation.
The determination step is a method of determining the identification information corresponding to the text data for which the reliability exceeds the threshold value and the highest reliability is calculated as appropriate identification information.

According to the present invention, for example, it is possible to prevent an erroneous attachment of identification information.

FIG. 1 is a block diagram showing a configuration of an example of the collation support device of the first embodiment. FIG. 2 is a block diagram showing an example of the hardware configuration of the collation support device of the first embodiment. FIG. 3 is a flowchart showing an example of processing in the collation support device of the first embodiment. FIG. 4 is a schematic diagram showing an example in which a name and an ID are used as text data in the second embodiment. FIG. 5 is a block diagram showing a configuration of an example of the collation support device according to the fifth embodiment.

In the collation support device of the present invention, the calculation unit may calculate the reliability by the ratio of the number of characters matched by the collation to the total number of characters included in the text data.

In the collation support device of the present invention, the collation unit may collate character by character from the beginning to the end of the text data.

In the collation support device of the present invention, the collation unit may collate for each predetermined character unit.

In the collation support device of the present invention, the acquisition unit further includes an image acquisition unit and a conversion unit, the image acquisition unit acquires image data including subject information, and the conversion unit obtains the image. The image data obtained by the acquisition unit may be converted into text data by optical character recognition processing.

The collation support device of the present invention may further include an output unit, and the output unit may output the appropriate identification information.

In the collation support device of the present invention, the output unit may output the appropriate identification information as a unique code for the appropriate identification information.

In the collation support method of the present invention, the calculation step may be an embodiment in which the reliability is calculated by the ratio of the number of characters matched by the collation to the total number of characters included in the text data.

In the collation support method of the present invention, the collation step may be in the form of collating character by character from the beginning to the end of the text data.

In the collation support method of the present invention, the collation step may be in the form of collating for each predetermined character unit.

In the collation support method of the present invention, the acquisition step further includes an image acquisition step and a conversion step, the image reading step acquires image data including subject information, and the conversion step is the image. The image data obtained in the acquisition step may be converted into text data by optical character recognition processing.

The collation support method of the present invention may further include an output step, and the output step may output the appropriate identification information.

In the collation support method of the present invention, the output step may be in the form of outputting the appropriate identification information as a unique code for the appropriate identification information.

The program of the present invention is a program capable of executing the collation support method of the present invention on a computer.

The recording medium of the present invention is a computer-readable recording medium on which the program of the present invention is recorded.

An embodiment of the present invention will be described. The present invention is not limited to the following embodiments. In each of the following figures, the same parts are designated by the same reference numerals. Further, the explanations of the respective embodiments can be referred to each other's explanations unless otherwise specified. Further, the configurations of the respective embodiments can be combined unless otherwise specified.

[Embodiment 1]
FIG. 1 is a block diagram showing a configuration of an example of the collation support device 1 of the present embodiment. As shown in FIG. 1, the apparatus 1 includes a storage unit 11, an acquisition unit 12, a collation unit 13, a calculation unit 14, and a determination unit 15. Further, as will be described later, in the present device 1, the acquisition unit 12 may further include an image acquisition unit 16 and a conversion unit 17.

The device 1 may be, for example, one device including the above-mentioned parts, or a device in which the above-mentioned parts can be connected via a communication network. The communication network is not particularly limited, and a known network can be used. For example, it may be wired or wireless. Examples of the communication network include an Internet line, a telephone line, a LAN (Local Area Network), WiFi (Wireless Fidelity), and the like. The apparatus 1 may be incorporated in the server as a system, for example. Further, the present device 1 may be, for example, a personal computer (PC) in which the program of the present invention is installed.

FIG. 2 illustrates a block diagram of the hardware configuration of the present device 1. The device 1 includes, for example, a central processing unit (CPU, GPU, etc.) 101, a memory 102, a bus 103, a storage device 104, an input device 105, a display device (display) 106, a communication device 107, and the like. Each part of the apparatus 1 is connected to each other via the bus 103 by each interface (I / F).

The central processing unit (central processing unit) 101 is responsible for overall control of the device 1. In the present device 1, for example, the program of the present invention and other programs are executed by the central processing unit 101, and various information is read and written. Specifically, for example, the central processing unit 101 functions as an acquisition unit 12, a collation unit 13, a calculation unit 14, and a determination unit 15.

The bus 103 can also be connected to, for example, an external device. Examples of the external device include an imaging device such as a camera, an external storage device (external database, etc.), a printer, and the like. The device 1 can be connected to an external network (communication network) by, for example, a communication device 107 connected to the bus 103, and can also be connected to another device or device via the external network. Other devices include, for example, an administrator's terminal (PC, server, smartphone, tablet, etc.).

In the present device 1, the memory 102 and the storage device 104 can also store access information and log information from an administrator, and information acquired from an external database (not shown).

In the present device 1, the acquisition unit 12 acquires the text data described later by using, for example, the input device 105. Alternatively, the acquisition unit 12 may acquire the text data described later by, for example, the communication device 107 via the external network. Examples of the external network include an Internet line, WWW (World Wide Web), a telephone line, LAN (Local Area Network), DTN (Delay Tolerant Networking), and the like. Communication by the communication device 107 may be wired or wireless. Examples of wireless communication include WiFi (Wireless Fidelity) and Bluetooth (registered trademark). The wireless communication may be either a form in which each device directly communicates (Ad Hoc communication) or an indirect communication via an access point.

The memory 102 includes, for example, a main memory, and the main memory is also referred to as a main storage device. When the central processing unit 101 performs processing, for example, the memory 102 reads various operation programs such as the program of the present invention stored in the storage device 104 described later, and the central processing unit 101 reads from the memory 102. Receive the data and run the program. The main memory is, for example, a RAM (random access memory). The memory 102 further includes, for example, a ROM (read-only memory).

The storage device 104 is also referred to as a so-called auxiliary storage device with respect to the main memory (main storage device), for example. As described above, the storage device 104 stores an operation program including the program of the present invention. The storage device 104 includes, for example, a storage medium and a drive for reading and writing to the storage medium. The storage medium is not particularly limited, and may be, for example, an internal type or an external type. HD (hard disk), FD (floppy (registered trademark) disk), CD-ROM, CD-R, CD-RW, MO, Examples thereof include a DVD, a flash memory, a memory card, and the like, and the drive is not particularly limited. The storage device 104 may be, for example, a hard disk drive (HDD) in which a storage medium and a drive are integrated. The storage device 104 functions as, for example, a storage unit 11.

The device 1 further includes, for example, an input device 105 and a display 106. The input device 105 is, for example, a touch panel, a keyboard, a mouse, or the like. Examples of the display 106 include an LED display and a liquid crystal display.

The storage unit 11 stores a subject list to which identification information is attached to each subject. The type of the subject is not particularly limited, and examples thereof include biological tissues such as blood, saliva, tissues and cells, and excretion such as urine. The subject may be collected from, for example, humans or from other organisms (animals, plants, microorganisms, etc.). Examples of the identification information include an ID (identification), a barcode, and the like. The subject list is not particularly limited, and examples thereof include a subject list owned by a facility such as a hospital and a laboratory.

The acquisition unit 12 acquires text data. The acquisition unit 12 may acquire the text data such as a sample label by using the input device 105 or the communication device 107, for example, as described above. Information such as the name (name and name) of the patient to be collected from the subject, the type of the subject, the date of collection, the patient ID, and the like is described in the sample label. Since the present device 1 uses two or more types of the text data as described later, for example, even if a part of the text data to be acquired is unknown, the collation described later can be performed. Further, the acquisition unit 12 may acquire the text data from the image data, for example. In this case, as shown in FIG. 1, the acquisition unit 12 may further include an image acquisition unit 16 and a conversion unit 17.

The image acquisition unit 16 acquires image data including subject information. Examples of the subject information include living tissues such as blood, saliva, tissues and cells, and excretion such as urine. The image acquisition unit 16 may acquire the image data by using, for example, an image pickup device such as a camera, or similarly, the image data is acquired by the communication device 107 via an external network. May be good.

The conversion unit 17 converts the image data obtained by the image acquisition unit 16 into text data by optical character recognition processing. The optical character recognition process is not particularly limited, and a known technique can be used.

The collation unit 13 collates two or more types of the text data with the subject list. The collation is not particularly limited, and for example, characters may be collated by brute force, or characters may be collated from the beginning to the end of the text data. The character-by-character is not particularly limited, but is preferably character-by-character. Further, the collation unit 13 may collate for each predetermined character unit. The character unit is, for example, a unit such as "year", "month", and "day" in the date of birth. That is, the four-digit number indicating the year of the date of birth in the acquired text data is used as one unit, and the one unit (four-digit number) indicating the year of the date of birth in the subject list is collated. Specifically, it will be described in Embodiment 4.

The calculation unit 14 calculates the reliability of each text data based on the collation. The reliability is a ratio indicating the consistency between the text data and the subject list. Specifically, the calculation unit 14 may calculate the reliability by the ratio of the number of characters matched by the collation to the total number of characters included in the text data, for example. That is, the higher the ratio of the number of matching characters, the higher the reliability.

The determination unit 15 determines that the identification information corresponding to the text data whose reliability exceeds the threshold value and which has calculated the highest reliability is appropriate identification information. The threshold value is not particularly limited and can be set arbitrarily.

Next, an example of the collation support method of the present embodiment will be described based on the flowchart of FIG. The collation support method of the present embodiment is implemented as follows, for example, using the collation support device 1 of FIG. The collation support method of the present embodiment is not limited to the use of the collation support device 1 of FIG.

First, the acquisition unit 12 acquires the text data (S1). The format of the acquisition is not particularly limited, and for example, as described above, the acquisition may be performed using the input device 105 or the communication device 107. Further, as described above, the image acquisition unit 16 may acquire image data including the subject information, and the conversion unit 17 may convert the acquired image data into text data by optical character recognition processing. .. For the optical character recognition process, for example, a known technique may be used.

Next, the collation unit 13 collates two or more types of the text data with a subject list to which identification information is attached to each subject (S2). In the collation, for example, characters may be collated by brute force, or characters may be collated for each character such as one character from the beginning to the end of the text data. Further, the collation may be performed for each predetermined character unit. The character unit is, for example, the same as described above.

Next, the calculation unit 14 calculates the reliability of each text data based on the collation (S3). The reliability may be calculated by, for example, the ratio of the number of characters matched by the collation to the total number of characters included in the text data.

Next, the determination unit 15 determines whether or not the reliability exceeds the threshold value (S4). When the threshold value is exceeded (YES), the identification information corresponding to the text data for which the highest reliability has been calculated is determined to be appropriate identification information (S5), and the process ends (END). On the other hand, when the threshold value is not exceeded (NO), for example, it is not determined as appropriate identification information and the process ends (END). The step (S5) may be performed before the step (S4).

According to the present invention, since two or more types of the text data are used, for example, highly reliable collation can be performed, and an error in attaching identification information can be prevented. Further, according to the present invention, since two or more types of the text data are used, for example, even if a part of the text data is unknown due to stains such as blood, it is possible to determine appropriate identification information. Is. Further, when the optical character recognition process is performed, it is possible to determine appropriate identification information even if the performance of an imaging device such as a camera and the performance of the optical character recognition process are not high. Further, according to the present invention, since the identification information can be collated with a subject list owned by a facility such as a hospital or a laboratory, for example, identification information that does not correspond to the subject is given or identified. It is possible to suppress the possibility of human error such as duplication of information.

[Embodiment 2]
Based on FIG. 4, a case where a name and an ID are used as the text data will be described as an example. FIG. 4A is an example of the text data acquired by the acquisition unit 12, and FIG. 4B is an example of the subject list. In addition, in FIG. 4A, the sample label corresponding to the sample collected from the patient is shown as the text data, but it is an example and is not limited thereto. Moreover, each item shown in FIG. 4A and FIG. 4B is an example, and is not limited thereto. In FIG. 4A, the part indicated by ◯ is an unknown character due to, for example, dirt or the performance of the imaging device.

For example, the collation unit 13 uses the name "Taro Omoto" and the patient ID "123456780" as the text data shown in FIG. 4 (A), and the collation unit 13 uses the subject shown in FIG. 4 (B). Collate with the list. For example, when the collation unit 13 performs character collation by brute force, "○ Hontaro" and "Nippon Taro" in the subject list match 3 characters out of 4 characters. Similarly, in the collation result of "123456789" and the list ID "123456789" of "Nippon Taro" in the subject list, 8 out of 9 characters match. Then, the calculation unit 14 calculates the reliability. The reliability can be calculated, for example, as follows.

[(Total number of matching characters) / (Total number of collated characters)] x 100 = Reliability (%)

When applied to the above formula, the total number of matching characters is the number of matching characters (3 characters) in "○ Hontaro" and "Nippon Taro" and the number of matching characters (8 characters) in "123456789" and "123456789". Add up to 11 characters. In addition, the total number of collation characters is 13 characters by adding 4 characters of the name and 9 characters of the ID. That is, the reliability is about 85%.

In the same manner, the results of calculating the reliability with other names and IDs in the subject list are shown in Table 1 below. In the present embodiment, for example, when the threshold value is 75% or more, the determination unit 15 sets the list ID "123456789" of "Nippon Taro" having a reliability of 75% or more and calculating the highest reliability. It is determined as a proper ID (that is, proper identification information). In addition, in this embodiment, the name is collated without being divided into the name, but the name and the name may be collated separately. The name may be separated by inserting a space between the name and the name, or each item may be created.

[Embodiment 3]
An example in which the collation unit 13 collates character by character from the beginning to the end of the text data will be described with reference to FIG. In this embodiment, it is set for each character, but the present invention is not limited to this, and any setting can be made.

This embodiment will be described by taking as an example the case where the name and the name of the name are used as the text data. For example, the collation of the text data with the names "○" and the name "Taro" with the subject list with the names "Japan" and the name "Taro" is as follows. First, the first character of Mr. in the text data is unknown, and the first character of Mr. in the subject list is "day", so that they do not match, for example. On the other hand, the second character is a match because both are "books". Similarly, the first letter (thick) and the second letter (ro) of the name also match. Next, the reliability is calculated in the same manner as in the second embodiment. That is, when the total number of matching characters (3 characters) is divided by the total number of collation characters (4 characters), the reliability of the collation is 75%.

On the other hand, the collation between the text data "Taro Omoto" and the subject list "Ichitaro Japan" is as follows. The results of collation of the first character and the second character are the same as described above. On the other hand, the third character is, for example, inconsistent because the text data is "thick" and the subject list is "1". Similarly, the fourth character (ro and ta) also does not match. Further, the fifth character does not exist in the text data and inevitably becomes a mismatch. In this case, the total number of matching characters is only one character of Mr. In addition, the total number of collation characters is 5 characters by adding 2 characters of Mr. and 3 characters of the first name. Therefore, the reliability of the collation is 20%.

In the same manner, the results of calculating the reliability of the other names and names in the subject list are shown in Table 2 below. In the present embodiment, for example, when the threshold value is 70% or more, the determination unit 15 corresponds to "Nippon Taro" having a reliability of 70% or more and calculating the highest reliability as described above. The list ID to be used is determined to be an appropriate ID (that is, appropriate identification information).

[Embodiment 4]
An example in which the collation unit 13 collates for each predetermined character unit will be described with reference to FIG. In the present embodiment, the character unit is 4 digits for the year of birth and 2 digits for the month and day, but the character unit is not limited to this and can be set arbitrarily.

This embodiment will be described by exemplifying a case where a date of birth and an ID are used as the text data. For example, the date of birth of the text data "May 08, 1999" and the patient ID "123456789" and the date of birth of the subject list "May 08, 1994" and the list ID "123456789" The collation is as follows. First, in the date of birth of the text data, the year is unknown ("1990"), and in the date of birth of the subject list, the year is "1994", so that they do not match, for example. On the other hand, the month of birth is "05" for both, so they are the same. Similarly, the date of birth (“08”) is also the same. If the month of birth of the text data is "5", the character unit is not satisfied, and collation is not possible, for example. On the other hand, the collation of the patient ID "123456789" of the text data with the list ID "123456789" of the subject list is the same as that of the second embodiment, for example. After that, the reliability is calculated in the same manner as in the second and third embodiments. That is, the total number of matching characters (that is, in character units) is 10 characters by adding one each of the month and day of birth and the eight characters of the ID. In addition, the total number of collation characters is 12 characters by adding the three characters of the year, month, and day of the date of birth and the nine characters of the ID. Therefore, the reliability of the collation is about 83%.

In the same manner, the results of calculating the reliability between the other date of birth and the ID in the subject list are shown in Table 3 below. In the present embodiment, for example, when the threshold value is 80% or more, the determination unit 15 has a reliability of 80% or more and the date of birth “1994) for which the highest reliability is calculated, as described above. The list ID corresponding to "May 08" is determined to be an appropriate ID (that is, appropriate identification information).

[Embodiment 5]
In this embodiment, the collation support device 1 outputs the appropriate identification information.

FIG. 5 is a block diagram showing a configuration of an example of the collation support device 1 of the present embodiment. As shown in FIG. 5, in the present embodiment, the collation support device 1 is the same as the collation support device 1 of each embodiment except that the output unit 18 is further included. Unless otherwise specified, the description of each of the above embodiments can be incorporated in this embodiment.

The output unit 18 outputs the appropriate identification information. In the present device 1, for example, the output unit 18 may display the appropriate identification information on the display device 106, or may output the appropriate identification information to a printer (not shown) for printing. The printing may be printed on a sticker, for example. By printing on the sticker, for example, the appropriate identification information can be attached to the sample label. Alternatively, the output unit 18 may transmit and output the appropriate identification information to a device outside the present device 1 via, for example, the communication device 107 and the external network.

For example, the output unit 18 may output the appropriate identification information as a unique code for the appropriate identification information. The code is not particularly limited, and examples thereof include a bar code and a two-dimensional code.

In the collation support method in the present embodiment, after the step (S5) shown in FIG. 3, the output unit 18 further outputs the appropriate identification information. The proper identification information may be output as a unique code for the proper identification information, for example, as described above.

According to this embodiment, for example, as in each of the above-described embodiments, it is possible to prevent erroneous attachment of identification information.

[Embodiment 6]
The program of this embodiment is a program that can execute the collation support method of each of the above embodiments on a computer. Further, the program of the present embodiment may be recorded on a computer-readable recording medium, for example. The recording medium is not particularly limited, and examples thereof include a read-only memory (ROM), a hard disk (HD), and an optical disk.

Although the present invention has been described above with reference to the embodiments, the present invention is not limited to the above embodiments. Various changes that can be understood by those skilled in the art can be made to the structure and details of the present invention within the scope of the present invention.

<Additional notes>
Some or all of the above embodiments may be described as, but not limited to, the following appendices.
(Appendix 1)
Including a storage unit, an acquisition unit, a collation unit, a calculation unit, and a determination unit,
The storage unit stores a subject list with identification information for each subject.
The acquisition unit acquires text data and
The collation unit collates two or more types of the text data with the subject list.
The calculation unit calculates the reliability of each text data based on the collation.
The determination unit determines that the identification information corresponding to the text data whose reliability exceeds the threshold value and whose highest reliability is calculated is appropriate identification information.
Collation support device.
(Appendix 2)
The collation support device according to Appendix 1, wherein the calculation unit calculates the reliability by the ratio of the number of characters matched by the collation to the total number of characters included in the text data.
(Appendix 3)
The collation support device according to Appendix 1 or 2, wherein the collation unit collates each character from the beginning to the end of the text data.
(Appendix 4)
The collation support device according to any one of Supplementary note 1 to 3, wherein the collation unit collates for each predetermined character unit.
(Appendix 5)
The acquisition unit further includes an image acquisition unit and a conversion unit.
The image acquisition unit acquires image data including subject information, and obtains image data.
The collation support device according to any one of Supplementary note 1 to 4, wherein the conversion unit converts the image data obtained by the image acquisition unit into text data by optical character recognition processing.
(Appendix 6)
In addition, including the output section
The collation support device according to any one of Appendix 1 to 5, wherein the output unit outputs the appropriate identification information.
(Appendix 7)
The collation support device according to Appendix 6, wherein the output unit outputs the appropriate identification information as a unique code for the appropriate identification information.
(Appendix 8)
Including acquisition process, collation process, calculation process, and judgment process
The acquisition process acquires text data and
In the collation step, two or more types of the text data are collated with a subject list to which identification information is attached to each subject.
In the calculation step, the reliability of each text data is calculated based on the collation.
In the determination step, the identification information corresponding to the text data whose reliability exceeds the threshold value and whose highest reliability is calculated is determined as appropriate identification information.
Collation support method.
(Appendix 9)
The collation support method according to Appendix 8, wherein the calculation step calculates the reliability by the ratio of the number of characters matched by the collation to the total number of characters included in the text data.
(Appendix 10)
The collation support method according to Appendix 8 or 9, wherein the collation step collates character by character from the beginning to the end of the text data.
(Appendix 11)
The collation support method according to any one of Appendix 8 to 10, wherein the collation step is collation for each predetermined character unit.
(Appendix 12)
The acquisition step further includes an image acquisition step and a conversion step.
In the image acquisition step, image data including subject information is acquired, and the image data is acquired.
The collation support method according to any one of Appendix 8 to 11, wherein the conversion step converts the image data obtained in the image acquisition step into text data by optical character recognition processing.
(Appendix 13)
In addition, it includes an output process
The collation support method according to any one of Supplementary note 8 to 12, wherein the output step outputs the appropriate identification information.
(Appendix 14)
The collation support method according to Appendix 13, wherein the output step outputs the appropriate identification information as a unique code for the appropriate identification information.
(Appendix 15)
A program capable of executing the method according to any one of Appendix 8 to 14 on a computer.
(Appendix 16)
A computer-readable recording medium on which the program described in Appendix 15 is recorded.

According to the present invention, for example, it is possible to prevent an erroneous attachment of identification information. Therefore, the present invention is particularly useful for giving identification information such as a barcode when the sample label is contaminated with blood or the like in a facility such as a hospital or a laboratory.

1 Collation support device 11 Storage unit 12 Acquisition unit 13 Collation unit 14 Calculation unit 15 Judgment unit 16 Image acquisition unit 17 Conversion unit 18 Output unit 101 Central processing unit 102 Memory 103 Bus 104 Storage device 105 Input device 106 Display device 107 Communication device

Claims (10)

Including a storage unit, an acquisition unit, a collation unit, a calculation unit, and a determination unit,
The storage unit stores a subject list with identification information for each subject.
The acquisition unit acquires text data and
The collation unit collates two or more types of the text data with the subject list.
The calculation unit calculates the reliability of each text data based on the collation.
The determination unit determines that the identification information corresponding to the text data whose reliability exceeds the threshold value and whose highest reliability is calculated is appropriate identification information.
Collation support device. The collation support device according to claim 1, wherein the calculation unit calculates the reliability by the ratio of the number of characters matched by the collation to the total number of characters included in the text data. The collation support device according to claim 1 or 2, wherein the collation unit collates character by character from the beginning to the end of the text data. The collation support device according to any one of claims 1 to 3, wherein the collation unit collates for each predetermined character unit. The acquisition unit further includes an image acquisition unit and a conversion unit.
The image acquisition unit acquires image data including subject information, and obtains image data.
The collation support device according to any one of claims 1 to 4, wherein the conversion unit converts the image data obtained by the image acquisition unit into text data by optical character recognition processing. In addition, including the output section
The collation support device according to any one of claims 1 to 5, wherein the output unit outputs the appropriate identification information. The collation support device according to claim 6, wherein the output unit outputs the appropriate identification information as a unique code for the appropriate identification information. Including acquisition process, collation process, calculation process, and judgment process
The acquisition process acquires text data and
In the collation step, two or more types of the text data are collated with a subject list to which identification information is attached to each subject.
In the calculation step, the reliability of each text data is calculated based on the collation.
In the determination step, the identification information corresponding to the text data whose reliability exceeds the threshold value and whose highest reliability is calculated is determined as appropriate identification information.
Collation support method. A program capable of executing the method according to claim 8 on a computer. A computer-readable recording medium on which the program according to claim 9 is recorded.

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