JP2021068335A - Program and system for determining admission possibility - Google Patents

Abstract

To perform a determination of possibility of admission to a nursey to which a user wish to be admitted at high accuracy.SOLUTION: An admission possibility determination program for determining possibility of admission to a nursery to which a user wishes to be admitted, makes a computer execute: an association level acquisition step of previously acquiring an association level of three or more levels between reference health state information obtained by digitizing a health state of a past admission applicant to the nursery and an admission possibility determination for the nursery; an information acquisition step of acquiring health state information obtained by digitizing the health state of each new admission applicant to the nursery; and a determination step of determining the possibility of admission to the nursery for each admission applicant on the basis of the health state information acquired via the information acquisition step and with reference to the association level acquired in the association level acquisition step.SELECTED DRAWING: Figure 3

Description

The present invention relates to an admission possibility determination program and a system for determining the admission possibility to a nursery school desired to enter the kindergarten.

The shortage of childcare workers has become a problem these days. It has also been pointed out that the number of nursery school teachers cannot be dramatically increased due to this shortage of nursery teachers, and the imbalance of applicants for admission to the nursery school has become a problem. Under these circumstances, the admission possibility is judged for those who wish to enter the nursery school, but it is necessary to read a considerable amount of documents for the selection of admission applicants and the admission possibility judgment. The burden of labor was excessive.

Although techniques for improving the efficiency of administrative procedures by utilizing artificial intelligence have been proposed (see, for example, Patent Document 1), the selection of applicants for admission to a nursery school and the determination of admission possibility are automatically performed. The technology to be performed is not particularly disclosed.

Japanese Patent Application No. 2011-197850

Therefore, the present invention has been devised in view of the above-mentioned problems, and the purpose of the present invention is to automatically and highly accurately determine the possibility of admission to a nursery school in which the child wishes to enter the kindergarten. The purpose is to provide a program and system for determining the possibility of entering a kindergarten.

The admission possibility determination program according to the present invention is a reference that digitizes the health status of past admission applicants to the above nursery school in the admission possibility determination program for determining the admission possibility to the nursery school desired to enter the nursery school. A step to acquire the degree of association between the information on the health condition for use and the determination of the possibility of admission to the nursery school in advance, and the health condition of each applicant for admission to the above-mentioned nursery school are newly converted into data. It is possible to enter the nursery school based on the information acquisition step for acquiring the health condition information and the association degree acquired in the association degree acquisition step, and based on the health condition information acquired through the information acquisition step. It is characterized in that a computer is made to execute a determination step of determining the sex for each applicant for admission.

The admission possibility determination system according to the present invention is an admission possibility determination system that determines the admission possibility to a nursery school that desires admission, and is a reference that digitizes the health condition of a person who wishes to enter the nursery school in the past. A means of acquiring the degree of association between the information on the health condition for use and the determination of the possibility of admission to the nursery school in advance, and the new data on the health condition of each applicant for admission to the above-mentioned nursery school. It is possible to enter the nursery school based on the information acquisition means for acquiring the health condition information and the association degree acquired by the association degree acquisition means, and based on the health condition information acquired through the information acquisition means. It is characterized in that it is provided with a determination means for determining the sex for each applicant for admission.

It is possible to automatically and accurately determine the possibility of entering a nursery school that you wish to enter.

It is a block diagram which shows the whole structure of the admission possibility determination system which implements the admission possibility determination program to which this invention is applied. It is a figure which shows the specific configuration example of the discrimination apparatus. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied. It is a figure for demonstrating operation in the admission possibility determination program to which this invention is applied.

Hereinafter, the admission possibility determination program to which the present invention is applied will be described in detail with reference to the drawings.

FIG. 1 is a block diagram showing an overall configuration of an admission possibility determination system 1 in which an admission possibility determination program to which the present invention is applied is implemented. The admission possibility determination system 1 includes an information acquisition unit 9, a discrimination device 2 connected to the information acquisition unit 9, and a database 3 connected to the discrimination device 2.

The information acquisition unit 9 is a device for a person who uses this system to input various commands and information, and specifically, is composed of a keyboard, buttons, a touch panel, a mouse, a switch, and the like. The information acquisition unit 9 is not limited to a device for inputting text information, and may be configured by a device such as a microphone that can detect voice and convert it into text information. Further, the information acquisition unit 9 may be configured as an image pickup device capable of capturing an image of a camera or the like. The information acquisition unit 9 may be configured by a scanner having a function of recognizing a character string from a paper-based document. Further, the information acquisition unit 9 may be integrated with the discrimination device 2 described later. The information acquisition unit 9 outputs the detected information to the determination device 2.

Database 3 stores information used in the past to determine the admission possibility of a person who wishes to enter a nursery school, which was conducted by government agencies, government offices, and other private companies. Actually, the materials referred to for judging the admission possibility for each nursery school in the jurisdiction city, ward, town, and village are not only the judgment result of the admission possibility, but also for judging the admission possibility. The materials and information that became the decisive factor in the above may also be recorded in association with these.

The discrimination device 2 is composed of, for example, an electronic device such as a personal computer (PC), but is realized by any other electronic device such as a mobile phone, a smartphone, a tablet terminal, a wearable terminal, etc. in addition to the PC. It may be converted. By obtaining the search solution by the discriminating device 2, the user can obtain the determination result of the possibility of admission to the nursery school of the person who wishes to enter the kindergarten.

FIG. 2 shows a specific configuration example of the discrimination device 2. The discrimination device 2 performs wired communication or wireless communication with a control unit 24 for controlling the entire discrimination device 2 and an operation unit 25 for inputting various control commands via an operation button, a keyboard, or the like. A communication unit 26 for the purpose, a judgment unit 27 for making various judgments, and a storage unit 28 for storing a program for performing a search to be executed represented by a hard disk or the like are connected to the internal bus 21, respectively. .. Further, a display unit 23 as a monitor that actually displays information is connected to the internal bus 21.

The control unit 24 is a so-called central control unit for controlling each component mounted in the discrimination device 2 by transmitting a control signal via the internal bus 21. Further, the control unit 24 transmits various control commands via the internal bus 21 in response to the operation via the operation unit 25.

The operation unit 25 is embodied by a keyboard or a touch panel, and an execution command for executing a program is input from the user. When the execution command is input by the user, the operation unit 25 notifies the control unit 24 of the execution command. Upon receiving this notification, the control unit 24, including the determination unit 27, executes a desired processing operation in cooperation with each component. The operation unit 25 may be embodied as the information acquisition unit 9 described above.

The judgment unit 27 is responsible for judging the possibility of admission to the nursery school of the applicant. The determination unit 27 reads out various information stored in the storage unit 28 and various information stored in the database 3 as necessary information when executing the estimation operation. The determination unit 27 may be controlled by artificial intelligence. This artificial intelligence may be based on any well-known artificial intelligence technique.

The display unit 23 is composed of a graphic controller that creates a display image based on the control by the control unit 24. The display unit 23 is realized by, for example, a liquid crystal display (LCD) or the like.

When the storage unit 28 is composed of a hard disk, predetermined information is written to each address based on the control by the control unit 24, and is read out as needed. Further, the storage unit 28 stores a program for executing the present invention. This program is read and executed by the control unit 24.

The operation in the admission possibility determination system 1 having the above-described configuration will be described.

In the admission possibility determination system 1, for example, as shown in FIG. 3, it is premised that a degree of association is formed between the reference health condition information and the admission possibility determination. The reference health information includes all information regarding the health of the infant as a prospective admission. For example, whether or not the infant who wishes to enter the kindergarten is in perfect health or has some kind of congenital disorder and the degree of the disorder, and whether or not there is an acquired disorder after birth and the degree of the disorder. In addition, whether or not you have some kind of illness after birth, whether or not the illness continues at present and its degree, allergic condition, inflammatory condition, injured condition, chronic condition, medication status, etc. Contains all information that indicates your health. this. The reference health condition information may be derived from medical data itself such as heart rate, pulse rate, blood data, electrocardiogram data, and X-ray image. All of these are obtained through declarations and documents submitted by each household, medical certificates of doctors, etc., and in actual implementation of this program, these reference health condition information must be converted into electronic data. Is a prerequisite.

FIG. 3 shows an example in which three or more levels of association between the reference health condition information and the admission possibility judgment (admission possible, admission not possible, conditional admission possible, etc.) are defined in advance. .. Each reference health condition information is arranged on the left side via this degree of association, and each admission possibility determination is arranged on the right side via this degree of association. The degree of association indicates the degree of relevance to which of the admission possibility determinations is high with respect to the reference health condition information arranged on the left side. In other words, this degree of association is an index indicating what kind of admission possibility judgment each reference health condition information is likely to be associated with, and the most probable admission possibility judgment from the reference health condition information. It shows the accuracy in selecting.

For example, in the reference health condition information P11 (egg allergy, rhinitis, blood pressure ●●), admission is associated with a degree of association w1 and non-admission is associated with a degree of association w2. For reference, health condition information P12 (drugs taken by Kawasaki disease at the age of 1 ●●, obese constitution due to the relationship between height and weight) is not admitted but can be admitted with a degree of association w3 (conditions) With) is associated with the degree of association w4. In the reference health condition information P13 (congenitally impaired ●●), admission is not possible with a degree of association w5, admission is possible with an association degree w6, and admission is possible (conditional) is associated with an association degree w7. There is.

Examples of the degree of association w1 to w7 are shown in Table 1 below. As shown in Table 1 below, these w1 to w7 are shown in 10 stages. The closer to 10 points, the higher the relevance to the admission possibility judgment, and conversely, the closer to 1 point, the more admission possibility judgment. It shows that the relevance is low. For example, when focusing on one case in which the judgment of admission in the past was made, and assuming that the reference health condition information P11, it was possible to enter the kindergarten based on the previous data, and what was the point of admission. The degree of association is set based on the extraction of the priority level and the like.

The degree of association may be composed of a model that can be updated through so-called machine learning, or may be composed of a neural network. Further, this degree of association may be configured by a network on the premise that deep learning is performed.

When newly determining the admission possibility of each applicant for admission to the nursery school, the estimation unit 27 refers to the degree of association stored in the database 3 in this way, and the newly input health condition information is displayed. It is determined which corresponds to the reference health condition information arranged on the left side of the degree of association. If the health status information of a new applicant for admission is P12 or is similar to this, it is judged that it corresponds to the reference health status information P12, and "No admission" with the highest degree of association w3 is the most. It can be judged that the judgment is appropriate. In addition, as a second opinion, it can be determined that the degree of association w4 is "admission possible (conditional)". If the health status information of a new applicant for admission is P13 or is similar to this, it is judged that it corresponds to the reference health status information P13, and "admission possible" with the highest degree of association w6 is the most. It can be judged that the judgment is appropriate. Further, as the second opinion, it can be determined that the degree of association w5 is "not admitted" and the degree of association w7 is "possible admission (conditional)".

At this time, the estimation unit 27 may select the admission possibility determination having the highest degree of association. This is because, as described above, the higher the degree of association, the higher the accuracy of the selection. However, the estimation unit 27 is not limited to the case of selecting the judgment of the possibility of admission having the highest degree of association, and even if the one with a medium degree of association or the one with a low degree of association is intentionally selected. Good. In addition to this, it is of course possible to select the admission possibility judgment in which the degree of association between the reference health condition information and the admission possibility judgment is 0%. The estimation unit 27 is not limited to selecting one of the admission possibility determinations, and may dare to select a plurality of admission possibility determinations with reference to the degree of association. The admission possibility determination searched by the estimation unit 27 is displayed via the display unit 23.

The method of displaying the admission possibility determination is not limited to the above-mentioned one, and may be displayed by points as shown in FIG. 4, for example. The higher the points, the more positive the decision to enter the nursery school, and the lower the points, the negative the admission to the nursery school. When determining the possibility of admission of each applicant to the nursery school by forming such a degree of association, if the health condition information of the applicant is the same as or similar to P11, the reference health condition In order to correspond to the information P11, it can be understood that 80 points of the highest degree of association w1 is the most appropriate, and the degree of association w2 as the second opinion is 25 points.

Assuming that the maximum number of children in a nursery school is one, it is assumed that there are three applicants for admission. At this time, assuming that the health condition information of the applicant for admission applies to P11, P12, and P13, respectively, and if the admission is judged at the point with the highest degree of association, the applicant for admission in the home environment of P11 is associated. 80 points via degree w1, 35 points for those who wish to enter the home environment of P12 via association w3, and 70 points for those who wish to enter the home environment of P13 via association degree w6. Those who wish to enter the home environment on P11 will be able to enter the park, and the rest will not be able to enter the park. In this way, the judgment of admission possibility based on points can be applied when it is necessary to narrow down the number of successful applicants in relation to the capacity and applicants.

That is, the admission possibility as this output solution may output the judgment result of admission permission itself, and does not actually display the admission permission itself as in the above points, but it is possible. It may output a parameter indicating high or low sex.

As another example, as shown in FIG. 5, for example, a degree of association may be formed between the reference damage information and the admission possibility determination. The reference damage information indicates whether or not the family as a person wishing to enter the park was damaged by the disaster, and if so, the degree of the damage. The degree of damage depends on whether the house is partially destroyed or completely destroyed and evacuated to a shelter.

FIG. 5 shows an example in which three or more levels of linkage between the reference damage information and the admission possibility determination (admission possible, admission not possible, conditional admission possible, etc.) are defined in advance. The damage information for each reference is arranged on the left side via this degree of association, and each admission possibility judgment is arranged on the right side via this degree of association. The degree of association indicates the degree of relevance to which of the admission possibility judgments is high with respect to the reference damage information arranged on the left side. In other words, this degree of association is an index showing what kind of admission possibility judgment each reference damage information is likely to be associated with, and the most probable admission possibility judgment is selected from the reference damage information. It shows the accuracy in doing so.

For example, in the reference damage information P14 (the house is partially destroyed by the typhoon and the electricity is stopped), admission is associated with the association degree w1 and non-entrance is associated with the association degree w2. In the reference damage information P15 (house is completely destroyed by a typhoon), admission is not possible with a degree of association w3, and admission is possible (conditional) is associated with a degree of association w4.

When newly determining the admission possibility of each applicant for admission to the nursery school, the estimation unit 27 refers to the degree of association stored in the database 3 in this way, and the newly input disaster information is associated. Determine which one corresponds to the reference damage information arranged on the left side of the degree. If the damage information of the new applicant is P15 or similar, it is judged that it corresponds to the reference damage information P15, and "No admission" with the highest degree of association w3 is the most appropriate. It can be judged that it is a judgment. In addition, as a second opinion, it can be determined that the degree of association w4 is "admission possible (conditional)".

The method of displaying the admission possibility determination is not limited to the above-mentioned one, and may be displayed by points as shown in FIG. 6, for example. When such a degree of association is formed and the possibility of newly admitting each applicant to the nursery school is determined, if the damage information of the applicant is P14, it corresponds to the reference damage information P14. Therefore, it can be understood that the point 80 points of w1 having the highest degree of association is the most appropriate, and the point w2 of the degree of association w2 as a second opinion is 25 points. Regarding the degree of association, for example, when focusing on one case in which past admission was determined, and assuming that it was the disaster information P16 for reference, was it possible to enter the kindergarten in the previous data, and what was the point? , What was the priority of admission, etc. are extracted and set based on this.

Assuming that the maximum number of children in a nursery school is one, it is assumed that there are three applicants for admission. At this time, assuming that the damage information of the person who wishes to enter the kindergarten applies to P14, P15, and P16, respectively, if the admission is judged at the point with the highest degree of association, the person who wishes to enter the kindergarten of the damage information of P14 has the degree of association. 80 points via w1, 35 points for those who wish to enter the disaster information on P15 via w3, and 70 points for those who wish to enter the disaster information on P16 via w6. Those who wish to enter the kindergarten in the family environment will be able to enter the kindergarten, and the rest will not be able to enter the kindergarten. In this way, the judgment of admission possibility based on points can be applied when it is necessary to narrow down the number of successful applicants in relation to the capacity and applicants.

As another example, as shown in FIG. 7, for example, a degree of association may be formed between the reference-approved childcare facility use information and the admission possibility determination. The information on the use of non-licensed childcare facilities for reference indicates whether or not the infant as an applicant for admission was previously unable to enter the licensed nursery school and had been admitted to the non-licensed nursery school. If so, it includes detailed information. If you have used an unlicensed nursery school, it may have a positive effect on the admission decision, so this is included in the decision.

FIG. 7 shows an example in which three or more levels of linkage are defined in advance between the information on the use of unlicensed childcare facilities for reference and the judgment of admission possibility (admission possible, admission not possible, conditional admission possible, etc.). Shown. Information on the use of unlicensed childcare facilities for reference is arranged on the left side via this degree of association, and each admission possibility judgment is arranged on the right side via this degree of association. The degree of association indicates the degree of relevance to which of the admission possibility judgments is high with respect to the information on the use of unlicensed childcare facilities for reference arranged on the left side. In other words, this degree of association is an index showing what kind of admission possibility judgment each reference-approved childcare facility use information is likely to be associated with, and is the most from the reference-approved childcare facility use information. It shows the accuracy in selecting a probable admission possibility judgment.

For example, in the reference non-licensed childcare facility usage information P14 (without the use of an unlicensed childcare center), admission is associated with a degree of association w1 and non-admission is associated with a degree of association w2. For reference, the non-licensed childcare facility usage information P15 (which has a track record of going to an unlicensed childcare center for one year) is associated with a degree of association w3 for non-admission and a degree of association w4 for admission (conditional).

When determining the admission possibility of each applicant for admission to a new nursery school, the estimation unit 27 refers to the degree of association stored in the database 3 in this way and uses the newly entered unlicensed childcare facility. Determine which of the information corresponds to the reference-approved childcare facility usage information arranged on the left side of the degree of association. If the information on the use of unlicensed childcare facilities for new admission applicants is P15 or is similar to this, it is judged that it corresponds to the information on the use of unlicensed childcare facilities for reference P15, and the highest degree of association w3. It can be judged that "no admission" is the most appropriate judgment. In addition, as a second opinion, it can be determined that the degree of association w4 is "admission possible (conditional)". The method of displaying the admission possibility determination is not limited to the above-mentioned one, and may be displayed by points as shown in FIG. 6, for example.

As another example, as shown in FIG. 8, for example, a degree of association may be formed between the reference school attendance information and the admission possibility determination. For reference, the school information is available if the family or guardian of the applicant is currently enrolled in or wishes to attend a university, graduate school, vocational school, etc., and if enrolled or wishes to attend school. It also includes detailed information about the school where you are attending or the school you wish to attend. If the family or guardian of the applicant is currently enrolled in a university, graduate school, vocational school, etc., or wishes to enroll, it may have a positive effect on the admission decision, so make a judgment including this. Is what you do.

FIG. 8 shows an example in which three or more levels of association between the reference school information and the admission possibility determination (admission possible, admission not possible, conditional admission possible, etc.) are defined in advance. Each reference school attendance information is arranged on the left side via this degree of association, and each admission possibility judgment is arranged on the right side via this degree of association. The degree of association indicates the degree of relevance to which admission possibility judgment is high with respect to the reference school attendance information arranged on the left side. In other words, this degree of association is an index showing what kind of admission possibility judgment each reference school information is likely to be associated with, and the most probable admission possibility judgment is selected from the reference school information. It shows the accuracy in doing so.

For example, in the reference school information P14 (the father is attending university), admission is associated with the degree of association w1 and non-admission is associated with the degree of association w2. In the reference school information P15 (mother wants to attend a vocational school), admission is not possible with a degree of association w3, and admission is possible (conditional) with a degree of association w4.

When newly determining the admission possibility of each applicant for admission to the nursery school, the estimation unit 27 refers to the degree of association stored in the database 3 in this way, and the newly input school attendance information is associated. Determine which of the reference school information arranged on the left side of the degree corresponds to. If the enrollment information of a new applicant is P15 or similar, it is judged that it corresponds to the reference enrollment information P15, and "No admission" with the most related degree w3 is the most appropriate. It can be judged that it is a judgment. In addition, as a second opinion, it can be determined that the degree of association w4 is "admission possible (conditional)". The method of displaying the admission possibility determination is not limited to the above-mentioned one, and may be displayed by points as shown in FIG. 6, for example.

In the example of FIG. 9, such reference health condition information and reference home environment information are arranged as input data. The intermediate node 61 shown in FIG. 9 is a combination of the reference health condition information and the reference home environment information as such input data. Each intermediate node 61 is further connected to an output. In this output, the point of determining the possibility of entering a kindergarten as an output solution is given as an example, but it is of course possible to set the admission possibility itself as an output.

The reference home environment information referred to here includes all information regarding the home environment of an infant as a person who wishes to enter the kindergarten. For example, if the mother of an infant who wants to enter the park is pregnant, the guardian is chasing a disability or illness, whether or not she lives with her grandparents, whether or not the care recipient is at home, whether or not she is suffering from domestic violence, DV Whether or not there is abuse or abuse, whether or not parents are divorced, income (household income), whether or not there is livelihood protection, whether or not there are siblings, and their age structure. All of these are obtained through declarations and submitted documents from each household, and in order to actually implement this program, it is a prerequisite that these reference household environment information is converted into electronic data.

Each combination (intermediate node) of the reference health condition information and the reference home environment information is associated with each other through three or more levels of association with this output solution. In the example of FIG. 9, w13 to w22 are shown as the degree of association. These w13 to w22 are shown in 10 stages as shown in Table 2 below, and the closer to 10 points, the higher the degree of relevance of each combination as an intermediate node to the possibility of entering the kindergarten as an output. On the contrary, the closer to one point, the lower the degree of relevance of each combination as an intermediate node to the possibility of entering the kindergarten as an output.

The discriminating device 2 acquires in advance the degree of association w13 to w22 of three or more stages shown in FIG. That is, the discriminating device 2 accumulates reference health condition information, reference home environment information, and data on how much the past admission possibility was determined in that case when actually determining the admission possibility. By analyzing and analyzing these, the degree of association shown in FIG. 9 is created.

For example, when focusing on one case in which the past admission was determined, if the reference health condition information P11 and the reference home environment information P19 were used, it was possible to enter the kindergarten based on the previous data. Extract the points, the priority of admission, and so on. This analysis and analysis may be performed by artificial intelligence. In such a case, for example, in the case of reference health condition information P11 and reference home environment information P19, was it actually possible to enter the kindergarten, what was the point, and what was the priority of admission? Etc. are analyzed from past data. The higher the admission, the higher the points, and the higher the priority of admission, the higher the degree of association is set. In the example of the intermediate node 61a linked in the case of the reference health condition information P11 and the reference home environment information P19, the output is linked to the output of 80 points and 35 points. Yes, the points are high, and the priority of admission is high, so the degree of association of w13 that leads to 80 points is set to 7 points, and the degree of association of w14 that leads to 35 points is set to 2 points.

Further, the degree of association shown in FIG. 9 may be composed of the nodes of the neural network in artificial intelligence. That is, the weighting coefficient for the output of the node of this neural network corresponds to the above-mentioned degree of association. Further, the network is not limited to a neural network, and may be composed of all decision-making factors constituting artificial intelligence.

In the example of the degree of association shown in FIG. 9, the node 61b is a node in which the reference home environment information P17 is combined with the reference health condition information P11, and the degree of association of 70 points is w15 and the point is 50 points. The degree of association is w16. The node 61c is a node that is a combination of the reference home environment information P15 and P17 with respect to the reference health condition information P12, and the degree of association of 35 points is w17 and the degree of association of 25 points is w18. ..

Such a degree of association is what is called learned data in artificial intelligence. After creating such learned data, when actually determining the possibility of entering a kindergarten from now on, the possibility of entering a kindergarten will be determined using the above-mentioned learned data. In such a case, the health condition information of those who wish to enter the nursery school will be newly acquired, and the home environment information will be acquired. The health condition information corresponds to the reference health condition information, and the home environment information corresponds to the reference home environment information.

Based on the newly acquired health condition information and the home environment information in this way, the output solution (point of admission possibility determination or admission availability itself) is actually obtained. In such a case, the degree of association shown in FIG. 9 (Table 1) acquired in advance is referred to. For example, when the newly acquired health condition information is the same as or similar to P12 and the acquired home environment information is P20, the node 61d is associated via the degree of association. In this node 61d, 70 points are associated with w19 and 25 points are associated with each other with a degree of association w20. In such a case, "70 points" having the highest degree of association is selected as the optimum solution. However, it is not essential to select the one with the highest degree of association as the optimum solution, and the “point 25 points” that have the lowest degree of association but the association itself is recognized may be selected as the optimum solution. In addition to this, it goes without saying that an output solution to which the arrows are not connected may be selected, and any other output solution may be selected in any other priority as long as it is based on the degree of association.

In this way, the selection of these optimal solutions is performed by using the trained model shown in FIG. 9 and inputting the input data (health condition information and home environment information) for which the solution is actually desired, and the output solution (possibility of admission). ) Is output through artificial intelligence. However, it is not essential for the present invention to utilize artificial intelligence, and it utilizes three or more levels of association between the reference health condition information, the reference home environment information, and the admission possibility for the combination. Any form may be realized as long as it is.

Table 1 shows examples of the degrees of association w1 to w12 extending from the input.

The intermediate node 61 may be selected based on the degree of association w1 to w12 extending from this input. That is, the larger the degree of association w1 to w12, the heavier the weighting in the selection of the intermediate node 61 may be. However, the association degrees w1 to w12 may all have the same value, and the weightings in the selection of the intermediate node 61 may all be the same.

As an alternative to the reference home environment information, a degree of association with the reference employment information may be formed as shown in FIG. The reference employment information is, for example, the occupation of the head of the household, whether or not he / she is assigned to work alone, whether he / she is currently looking for a job, the day of the week or time of work, the address of the workplace, the commuting route, and the like. All of these are obtained through declarations and submitted documents from each household, and in order to actually implement this program, it is a prerequisite that these reference employment information is converted into electronic data.

In such a case, as shown in FIG. 10, a combination of reference health condition information, reference employment information that digitizes the employment status of parents of past applicants for admission to the nursery school, and the nursery school concerned Obtain in advance the degree of association with the judgment of the possibility of entering the kindergarten at three or more levels. Then, employment information that digitizes the employment status of the guardians of each applicant for admission to the nursery school is newly acquired. Based on the acquired employment information of the guardians of each applicant for admission, the possibility of admission to the nursery school is determined for each applicant as described above.

As an alternative to the reference home environment information, a degree of association with the reference employment information may be formed as shown in FIG. The reference employment information shows the employment status of the family of the applicant for admission, for example, the occupation of the head of the household, whether or not he / she is assigned to work alone, whether he / she is currently looking for a job, the day and time of work, the address of the workplace, and commuting. The route, etc. All of these are obtained through declarations and submitted documents from each household, and in order to actually implement this program, it is a prerequisite that these reference employment information is converted into electronic data.

In such a case, as shown in FIG. 10, a combination of reference health condition information, reference employment information that digitizes the employment status of parents of past applicants for admission to the nursery school, and the nursery school concerned Obtain in advance the degree of association with the judgment of the possibility of entering the kindergarten at three or more levels. Then, employment information that digitizes the employment status of the guardians of each applicant for admission to the nursery school is newly acquired. Based on the acquired employment information of the guardians of each applicant for admission, the possibility of admission to the nursery school is determined for each applicant as described above.

As an alternative to the reference home environment information, a degree of association may be formed with the reference delinquency information as shown in FIG. The reference delinquency information indicates the past delinquency status of childcare fees for visitors. If the younger brother or sister of a past visitor (brother, sister) wishes to enter the park and the delinquency status affects the judgment of the possibility of admission, the delinquency status and the influence of the judgment of the possibility of admission The degree of is acquired in advance and reflected in the degree of association. If the childcare fees of past visitors (brother, sister) were delinquent once in two years, but it took three months to pay, the judgment of the possibility of admission of the younger brother or sister would be adversely affected and the points would be lowered. If there is, set the degree of association accordingly.

In such a case, as shown in FIG. 11, a combination of reference health condition information, reference delinquency information indicating the delinquency status of childcare fees of past visitors to the nursery school, and admission to the nursery school. Obtain three or more levels of association with the possibility judgment in advance. Then, a new delinquency information indicating the delinquency status of the childcare fee regarding the brothers and sisters of each applicant for admission to the above nursery school is acquired. Based on the acquired delinquency information, the possibility of admission to the nursery school is determined for each applicant as described above.

As an alternative to the reference home environment information, a degree of association may be formed with the reference admission record information as shown in FIG. The reference admission record information indicates the past record of visitors. If the older brother or sister of the applicant has a record of entering the kindergarten and it has influenced the judgment of the possibility of entering the kindergarten, obtain the record of admission and the degree of influence of the judgment of the possibility of entering the kindergarten in advance. , Reflected in the degree of association. If past visitors (brother, sister) enter the park, make a positive assessment in determining the possibility of entering the park for their younger brother or sister, and if the points increase, set the degree of association accordingly. ..

In such a case, as shown in FIG. 12, the combination of the reference health condition information and the reference admission record information indicating the past admission record of the siblings of the applicant for admission to the nursery school is combined with the nursery school. Obtain in advance the degree of association with the admission possibility judgment of 3 or more levels. Then, new admission record information indicating the admission record of the siblings of each applicant for admission to the above nursery school is acquired. It is the same as the above to judge the possibility of admission to the nursery school for each applicant based on the acquired admission record information.

In the above-mentioned examples of FIGS. 9 to 12, the degree of association between the reference health condition information and the reference home environment information, the reference employment information, the reference delinquency information, and the reference admission record information is determined. I explained the example of forming, but by forming the same degree of association with other reference disaster information, reference unlicensed childcare facility usage information, and reference school attendance information, childcare is also possible. It is possible to determine the possibility of admission to the place for each applicant.

In the above-mentioned degree of association, the degree of association is expressed by a 10-step evaluation, but it is not limited to this, and it may be expressed by a degree of association of 3 or more levels, and conversely, it may be expressed by 3 or more levels. For example, 100 steps or 1000 steps may be used. On the other hand, this degree of association does not include those expressed in two stages, that is, whether or not they are related to each other, either 1 or 0.

According to the present invention having the above-described configuration, anyone can easily determine and search for the possibility of admission without any special skill or experience. Further, according to the present invention, it is possible to make a judgment of this search solution with higher accuracy than a human being. Further, by configuring the above-mentioned degree of association with artificial intelligence (neural network or the like), it is possible to further improve the discrimination accuracy by learning this.

Since there are many cases where the input data and the output data described above do not exist exactly the same in the process of learning, the input data and the output data may be classified by type. That is, the information P01, P02, ... P15, 16, ... That constitute the input data are classified according to the criteria classified in advance on the system side or the user side according to the content of the information, and the classified inputs. A dataset may be created between the data and the output data and trained.

In the above-mentioned degree of association, reference home environment information, reference employment information, and reference for any of reference health condition information, reference damage information, reference unlicensed childcare facility usage information, and reference school attendance information. An example of forming a degree of association with a combination of delinquent payment information and reference admission record information has been explained, but the present invention is not limited to this. In other words, the degree of association is for reference health condition information, reference disaster information, reference unlicensed childcare facility usage information, reference school attendance information, reference home environment information, reference employment information, reference delinquency information. , It may be composed of a combination with any two or more of the reference admission record information. In addition, when the reference health condition information, the reference disaster information, the reference unlicensed childcare facility usage information, and the reference school attendance information form a degree of association with the output, factors other than the above are used in this combination. In addition, a degree of association may be formed.

In addition, among reference health condition information, reference disaster information, reference unlicensed childcare facility usage information, reference school attendance information, reference home environment information, reference employment information, reference delinquency information, reference admission record information The degree of association may be configured by any combination of two or more factors.

Further, as shown in FIG. 13, the present invention determines the selling price based on the degree of association between two or more types of information, the reference information U and the reference information V. This reference information Y is any of reference health condition information, reference disaster information, reference unlicensed childcare facility usage information, and reference school attendance information, and reference information V is reference home environment information and reference employment. It shall be one of information, delinquency information for reference, and admission record information for reference.

At this time, as shown in FIG. 13, the output obtained for the reference information U may be used as input data as it is, and may be associated with the output via the intermediate node 61 in combination with the reference information V, for example. , For reference information U (reference market information), after outputting an output solution as shown in FIG. 3, this is used as an input as it is, and the degree of association with other reference information V is used for output. You may try to search for.

Further, according to the present invention, it is characterized in that an optimum solution search is performed through the degree of association set in three or more stages. The degree of association can be described by, for example, a numerical value from 0 to 100% in addition to the above-mentioned 10 steps, but the degree of association is not limited to this and can be described by a numerical value of 3 or more steps at any stage. It may be configured.

By determining the most probable selling price based on the degree of association represented by the numerical values of three or more levels, in a situation where there are multiple possible candidates for the search solution, the order of the degree of association is high. It is also possible to search and display. If the users can be displayed in descending order of the degree of association in this way, it is possible to preferentially display more probable search solutions.

In addition to this, according to the present invention, it is possible to judge without overlooking the discrimination result of the output having an extremely low degree of association such as 1%. It warns the user that even a judgment result with an extremely low degree of association is connected as a slight sign, and may be useful as the judgment result once every tens or hundreds of times. be able to.

Further, according to the present invention, there is an advantage that the search policy can be determined by the method of setting the threshold value by performing the search based on the degree of association of three or more stages. If the threshold value is lowered, even if the above-mentioned degree of association is 1%, it can be picked up without omission, but it is unlikely that a more appropriate discrimination result can be detected favorably, and a lot of noise may be picked up. is there. On the other hand, if the threshold value is raised, there is a high possibility that the optimum search solution can be detected with high probability, but the degree of association is usually low and it is passed through, but it is suitable that it appears once every tens or hundreds of times. Sometimes the solution is overlooked. It is possible to decide which one to prioritize based on the ideas of the user side and the system side, but it is possible to increase the degree of freedom in selecting the points to be emphasized.

Further, in the present invention, the above-mentioned degree of association may be updated. This update may reflect information provided via a public communication network such as the Internet. In addition, when each reference information such as reference market information is acquired and knowledge, information, and data on the selling price and improvement measures for these are acquired, the degree of association is increased or decreased according to these.

In other words, this update corresponds to learning in the sense of artificial intelligence. It can be said that it is a learning act because it acquires new data and reflects it in the learned data.

In addition, this update of the degree of association is done by the system side or the user side based on the contents of research data, papers, conference presentations, newspaper articles, books, etc. by experts, except when it is based on information that can be obtained from the public communication network. It may be updated artificially or automatically. Artificial intelligence may be utilized in these update processes.

Further, the process of first creating the trained model and the above-mentioned update may use not only supervised learning but also unsupervised learning, deep learning, reinforcement learning, and the like. In the case of unsupervised learning, instead of reading and learning the data set of input data and output data, information corresponding to the input data is read and trained, and the degree of association related to the output data is self-formed from there. You may let it.

The degree of association may be composed of the nodes of the neural network in artificial intelligence. That is, the weighting coefficient for the output of the node of this neural network corresponds to the above-mentioned degree of association. Further, the network is not limited to a neural network, and may be composed of all decision-making factors constituting artificial intelligence.

In such a case, as shown in FIG. 14, reference health condition information is input as input data, for example, the above-mentioned points are output as output data, and at least one or more hidden layers are formed between the input node and the output node. It may be provided and machine-learned. The above-mentioned degree of association is set in either one or both of the input node and the hidden layer node, and this is the weighting of each node, and the output is selected based on this. Then, when the degree of association exceeds a certain threshold value, the output may be selected.

1 Admission possibility judgment system 2 Judgment device 21 Internal bus 23 Display unit 24 Control unit 25 Operation unit 26 Communication unit 27 Estimate unit 28 Storage unit 61 node

Claims (9)

In the admission possibility judgment program that determines the admission possibility to the nursery school you wish to enter
A linking degree acquisition step for acquiring in advance three or more levels of association between the reference health condition information that digitizes the health condition of past applicants for admission to the nursery school and the determination of the possibility of entering the nursery school. ,
An information acquisition step to newly acquire health condition information that digitizes the health condition of each applicant for admission to the above nursery school, and
A determination step for determining the possibility of admission to the nursery school for each applicant based on the health condition information acquired through the information acquisition step with reference to the association degree acquired in the association degree acquisition step. An admission possibility determination program characterized by having a computer execute and. In the admission possibility judgment program that determines the admission possibility to the nursery school you wish to enter
Degree of association to obtain in advance three or more levels of association between the reference damage information that digitizes the damage situation caused by a disaster in the home of a person who wishes to enter the nursery school in the past and the judgment of the possibility of entering the nursery school. Acquisition step and
The information acquisition step to newly acquire the damage information that digitizes the damage situation due to the disaster in the home of each applicant to the above nursery school, and
With reference to the degree of association acquired in the above-mentioned degree of association acquisition step, and based on the above-mentioned damage information acquired through the above-mentioned information acquisition step, a determination step for determining the possibility of admission to the above-mentioned nursery school for each person who wishes to enter the kindergarten. A park admission possibility determination program characterized by having a computer execute the above. In the admission possibility judgment program that determines the admission possibility to the nursery school you wish to enter
Three or more levels of linkage between the information on the use of non-licensed childcare facilities for reference, which digitizes the usage status of other non-licensed childcare facilities of past applicants for admission to the above-mentioned nursery school, and the judgment of the possibility of admission to the nursery school. The association degree acquisition step to acquire the degree in advance and
An information acquisition step to acquire information on the use of unlicensed childcare facilities, which is a new data on the usage status of other unlicensed childcare facilities of those who wish to enter the above nursery school.
The possibility of admission to the nursery school is determined for each applicant based on the information on the use of the unlicensed childcare facility acquired through the information acquisition step with reference to the degree of association acquired in the association degree acquisition step. An admission possibility judgment program characterized by having a computer execute a judgment step to be performed. In the admission possibility judgment program that determines the admission possibility to the nursery school you wish to enter
Linkage acquisition step to acquire in advance three or more levels of association between the reference school information that digitizes the enrollment status of the family of the past applicants for admission to the nursery school and the determination of the possibility of admission to the nursery school. When,
The information acquisition step to newly acquire the enrollment information that digitizes the enrollment status of the family of each applicant to the above nursery school, and
With reference to the degree of association acquired in the above-mentioned degree of association acquisition step, and based on the above-mentioned school attendance information acquired through the above-mentioned information acquisition step, a determination step for determining the possibility of admission to the above-mentioned nursery school for each person who wishes to enter the kindergarten. A park admission possibility determination program characterized by having a computer execute the above. In the above-mentioned degree of association acquisition step, there are three or more stages of association between the combination with the reference home environment information that digitizes the home environment of the past applicants for admission to the nursery school and the determination of the possibility of admission to the nursery school. Get the degree in advance,
In the above information acquisition step, new home environment information that digitizes the home environment of each applicant for admission to the above nursery school is acquired.
The determination step is characterized in that the possibility of admission to the nursery school is determined for each applicant based on the home environment information of each applicant through the information acquisition step. The admission possibility determination program according to any one of items 1 to 4. In the above-mentioned linkage degree acquisition step, there are three or more stages of combining with reference employment information that digitizes the employment status of parents of parents who wish to enter the nursery school in the past and determining the possibility of entering the nursery school. Obtain the degree of association in advance,
In the above information acquisition step, employment information that digitizes the employment status of the guardians of each applicant for admission to the above nursery school is newly acquired.
The determination step is characterized in that the possibility of admission to the nursery school is determined for each applicant based on the employment information of the guardian of each applicant for admission acquired in the step of acquiring the degree of association. The admission possibility determination program according to any one of claims 1 to 5. In the above-mentioned degree of association acquisition step, a combination with the reference delinquency information indicating the delinquency status of the childcare fees of the past visitors to the above-mentioned nursery school and the degree of association of three or more stages of the admission possibility judgment for the combination are obtained in advance. Acquired,
In the above information acquisition step, further acquisition of delinquency information indicating the delinquency status of childcare fees for the brothers and sisters of each applicant to the above nursery school is newly acquired.
In the determination step, the possibility of admission to the nursery school is determined for each person who wishes to enter the nursery school, based on the delinquency information acquired through the information acquisition step, with reference to the association degree acquired in the association degree acquisition step. The admission possibility determination program according to any one of claims 1 to 6, wherein the determination is made. In the above-mentioned degree of association acquisition step, there are three or more levels of association between the combination with the reference admission record information showing the past admission record of the siblings of the applicant for admission to the nursery school and the admission possibility judgment for the combination. In advance,
In the above information acquisition step, further acquisition of admission record information showing the admission record of the siblings of each applicant for admission to the above nursery school is newly acquired.
In the determination step, the possibility of admission to the nursery school is determined for each person who wishes to enter the nursery school, based on the association degree acquired in the association degree acquisition step and the admission record information acquired through the information acquisition step. The admission possibility determination program according to any one of claims 1 to 7, wherein the determination is made in 1. In the admission possibility judgment system that judges the admission possibility to the nursery school that you want to enter
With reference health condition information that digitizes the health condition of past applicants for admission to the above nursery school, and a means for acquiring the degree of association that obtains in advance three or more levels of association between the determination of the possibility of admission to the nursery school. ,
Information acquisition means for newly acquiring health condition information that digitizes the health condition of each applicant for admission to the above nursery school,
Judgment means for determining the possibility of admission to the nursery school for each applicant based on the health condition information acquired through the information acquisition means by referring to the association degree acquired by the association degree acquisition means. A system for determining the possibility of entering a kindergarten, which is characterized by having.

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