JP7360643B1 - Childcare product recommendation device and childcare product recommendation program - Google Patents

Abstract

[Problem] To provide a childcare product recommendation device, a childcare product recommendation system, and a childcare product recommendation program in which childcare products suitable for a child's physical movement characteristics and constitution are presented as recommended products. A childcare product recommendation server (10) includes a feature data generation section (80) and a recommendation processing section (90). The characteristic data generation unit 80 determines whether the child's growth is going well or not using growth status data that includes operation availability data indicating whether or not each of a plurality of growth specific movements is possible for each movement code assigned to each growth specific movement. The apparatus includes a growth status determining means for executing the above-mentioned growth status determination, and a characteristic data generating means for generating characteristic data indicating characteristics related to the child's physical movements so as to include the results of the growth status determination. The recommendation processing unit 90 has a recommended product presenting means that presents childcare products that match the characteristic data as recommended products. [Selection diagram] Figure 4

Description

The present invention relates to a childcare product recommendation device and a childcare product recommendation program in which childcare products suitable for the child's characteristics are presented as recommended products so that differences in the developmental progress of the child are reflected.

BACKGROUND ART Childcare support services for parents who are raising children have been known. For example, childcare support helper services that provide housework assistance and childcare advice, childcare services and temporary custody services that take care of preschool children, and rental services for childcare supplies are well known.

In addition, as a service using the Internet, there is a service that provides childcare-related information, and a childcare support system that provides information on the facilities and costs necessary for childcare according to the user's situation (for example, Patent Document 1, Patent Document 1, (see Document 2), child care product purchasing support services (for example, see Patent Document 3), and the like.

Japanese Patent Application Publication No. 2002-56112 Japanese Patent Application Publication No. 2005-284844 Patent No. 7002087

In the childcare products purchase support service disclosed in Patent Document 3 mentioned above, childcare products according to the child's growth status are listed in a childcare products list, and the childcare products list is presented to users such as parents who are raising children.

On the other hand, in recent years, systems in which orders for the purchase of products and services are sent via communication using the Internet, and the products and services related to the orders are delivered to customers by mail or home delivery (also called Internet mail order) have become widespread. are doing. In conventional online shopping, recommended products and services are determined based on the user's past history of product purchases, searches, and product viewing, and the determined products and services are presented to the user. (also referred to as "presentation of recommended products, etc.").

For this reason, even in the conventional purchasing support service for childcare products mentioned above, in addition to childcare products according to the child's growth status, childcare products may be presented as recommended products based on past history such as product viewing.

However, there are individual differences in the developmental status of children, and while some children develop (growth) quickly, others develop (growth) slowly. It also differs from child to child. For example, while there are 6-month-old children who can roll over and 9-month-old children who can crawl, there are also 6-month-old children who cannot roll over and 9-month-old children who cannot crawl. In other words, since each child's developmental progress is different, when recommended childcare products are presented, childcare products that match the characteristics of physical movements are presented to reflect differences in developmental progress. It is desirable that Furthermore, each child has a different physical constitution. For example, some children are born with sensitive skin or are prone to contact dermatitis, while others are not. If this child's condition is overlooked or left untreated without adequate care, the child will develop repeated skin symptoms called allergic march or develop an atopic constitution, and be exposed to allergic diseases (dermatitis, rhinitis, rhinitis, etc.) for a lifetime. It has been reported by the medical society that this can make people more prone to developing asthma, food allergies, etc.

In particular, by being presented with recommended products that match the characteristics of physical movements and constitution, the likelihood of purchasing the recommended products is higher than when presented with recommended products that are not compatible with the characteristics of physical movements and constitution. It is thought that this will increase. In addition, it is thought that more importance will be placed on making such recommendations, and the spread of Internet searches and high-performance mobile phones (also called smartphones) is spurring this trend. Therefore, it is desirable to be presented with recommended products that are compatible with the child's physical movement characteristics and constitution, but this has not been achieved with conventional techniques.

The present invention has been made to solve the above-mentioned problems, and the present invention provides child care products that are recommended as recommended products that suit the physical movement characteristics and constitution of the child so as to reflect differences in the progress of development. The purpose is to provide a product recommendation device and a childcare product recommendation program.

In order to solve the above problems, the present invention provides data indicating the developmental status of a child, which is useful for identifying the developmental progress of the child among physical movements that are movements using the child's body. , crawling, rolling over, etc., which indicate whether each of the developmental specific movements is possible or not , are included for each movement code assigned to each developmental specific movement, and the child's date of birth is also indicated. A growth status data storage means that stores growth status data including date and month data, and a growth index code that is used as an index to grasp the characteristics of a child's development and is set to correspond to each movement code . a characteristic data storage means in which characteristic data including a developmental progress code indicating whether the child's development is normal, advanced, or delayed and has date of birth data is stored; A persona basic data storage means in which a plurality of persona basic data, which is image data representing the child, is stored, and date of birth data included in characteristic data of the persona basic data stored in the persona basic data storage means. Pre-persona image generation that selects image data according to the child's age calculated using an image presentation means for presenting a preliminary persona image generated by the preliminary persona image generation means; and a recommended product presentation means for presenting childcare products that match the characteristic data stored in the characteristic data storage means as recommended products. It features a childcare product recommendation device having the following features:

In the above-mentioned childcare product recommendation device, the preliminary persona image generation means measures the number of developmental progress codes included in the feature data, which is the number of data indicating that the child's development is delayed, and measures the number of developmental progress codes included in the characteristic data. Preferably , the preliminary persona image is generated by changing the facial expression of the child according to the number of delays .

Further, in the above-mentioned childcare product recommendation device, the characteristic data storage means stores a tooth index data section in which a developmental progress code is stored as data indicating whether the child's dental development is normal, advanced, or delayed. Further, the tooth index data section has an eruption start index field in which a developmental progress code is stored as data indicating whether the child's teeth are starting to erupt normally, ahead of time, or delayed. can do.

The childcare product recommendation device has individual areas corresponding to each growth index code, a progress code area corresponding to the growth progress code is assigned to each of the individual areas, and a recommended product presentation means for each of the progress code areas. Recommended product determination data storage means, in which recommended products presented by the above, which are suitable for each specific growth motion, are associated with recommendation propriety data indicating whether they can be recommended or not; The apparatus further includes recommended product determining means for determining recommended products according to the recommendability data stored in the product determining data storage means, and the recommended product presenting means presents the recommended products determined by the recommended product determining means. You can do it like this.

Further, the progress determination processing means determines whether the child's growth is normal, ahead, or delayed for each operation code using the operation availability data of the growth status data stored in the growth status data storage means; It is possible to further include characteristic data generation means for generating characteristic data such that data corresponding to the result determined by the progress determination processing means is included as a growth progress code.

Further, a growth guideline data section storing data indicating a guideline for when the child's growth is normal and a number of months after birth data section storing data indicating the number of months since the child's birth are associated. It further includes a guideline data storage means, and the guideline data section has a field corresponding to each movement code, and each of the fields is associated with the number of months after birth data section, and indicates whether the body movement is possible or not. In each field, the availability data is set for each number of months after birth, and in each field, the initial possible number of months corresponding to the time when physical movement becomes possible for the first time is set from the minimum number of months, which is the minimum number of months after birth. Disapproval data indicating that physical movements are not possible in the feasibility data is set by the number of months after birth that is less than or equal to the number of months after birth, and physical movements in the enablement data are possible within the number of months after birth that is equal to or greater than the initial possible number of months. Possibility data can be set to indicate the

Further, the progress judgment processing means converts all the operation codes from the growth guideline data storage means into the child's age in months calculated using the date of birth data included in the growth status data stored in the growth status data storage means. Reads the availability data set for the appropriate number of months after birth and compares the read availability data with the behavior availability data included in the growth status data to determine whether the child's growth is normal, ahead of schedule, or delayed. It is preferable to do so.

The above-mentioned childcare product recommendation device includes a recommended comment storage means in which recommended comments regarding appropriate recommended products stored in the recommended product determination data storage means are stored in association with growth index codes, and a prior persona image in the recommended comment storage means. It is preferable to further include a post-persona image generation means for generating a post-persona image by changing it according to the stored recommended comments.

Furthermore, it is possible to further include a presentation control means for controlling the pre-persona image and the post-persona image to be presented side by side together with the recommended product when the recommended product is presented by the recommended product presentation means.

Furthermore, the pre-persona image generation means can change the child's facial expression in accordance with the number of improvements after the number of delays has been corrected by the numerical value set in the recommended comment.

The present invention is a childcare product recommendation program for causing a computer to function as a childcare product recommendation device, and in which the computer is used to collect data indicating the developmental status of a child, and to perform physical movements using the child's body. Motion availability data indicating whether multiple developmental specific behaviors such as crawling, rolling over, etc., which are useful for identifying the child's developmental progress , are possible or not can be assigned to each developmental specific behavior. growth status data storage control means for storing growth status data in a growth status data storage means that stores growth status data that is included for each operation code and includes date of birth data indicating the child's date of birth ; A developmental progress code that is used as an indicator to understand the characteristics of a child's development, and indicates whether the child's development is normal, ahead, or delayed for each developmental indicator code that is set to correspond to each behavior code. and feature data storage control means for storing feature data in a feature data storage means in which feature data including date of birth data is stored, and persona basics that are image data representing a typical child according to the age of the month. Image data corresponding to the child's age calculated using the date of birth data included in the characteristic data of the persona basic data stored in the persona basic data storage means in which a plurality of pieces of data are stored is selected, Pre-persona image generation means for generating a pre-persona image by changing a child's facial expression indicated by image data according to a developmental progress code included in the feature data, and presenting a pre-persona image generated by the pre-persona image generation means. To provide a childcare products recommendation program which functions as an image presentation means for displaying images and a recommended product presentation means for presenting childcare products suitable for characteristic data stored in a characteristic data storage means as recommended products .

As described in detail above, according to the present invention, a childcare product recommendation device presents childcare products that are suitable for the physical movement characteristics and constitution of the child as recommended products so as to reflect differences in developmental progress. and child care product recommendation program.

1 is a system configuration diagram of a childcare product recommendation system including a childcare product recommendation server according to an embodiment of the present invention. FIG. 2 is a block diagram mainly showing the internal configuration of a childcare products recommendation server. FIG. 2 is a block diagram mainly showing the internal configuration of a user terminal device. 1 is a functional block diagram showing the main configuration of a childcare product recommendation server according to an embodiment of the present invention. FIG. FIG. 2 is a functional block diagram showing the main configuration of a recommendation processing unit along with various main storage units or DBs. FIG. 2 is a functional block diagram showing the main configuration of a registration processing section. It is a diagram showing an example of a record layout of a member master. It is a figure which shows an example of the record layout of a child master. It is a figure which shows an example of the record layout of growth status data storage DB. It is a figure which shows an example of the record layout of feature data storage DB. FIG. 3 is a diagram showing an example of a database structure of a growth guideline table. It is a flowchart which shows an example of the operational procedure of member support processing. 12 is a flowchart illustrating an example of an operation procedure of child care product recommendation processing. 3 is a flowchart illustrating an example of an operation procedure of feature data generation processing. 3 is a flowchart illustrating an example of an operation procedure of feature extraction processing. It is a flowchart which shows an example of the operating procedure of tooth index data generation processing. 3 is a flowchart illustrating an example of an operation procedure of a body movement index data generation process. FIG. 3 is a diagram showing an example of a database structure of a recommended product determination table. FIG. 2 is a diagram illustrating an example of processing performed by a childcare products recommendation server and a user terminal device, and an operation performed by the two in cooperation. FIG. 3 is a diagram showing an example of a database structure of a recommended comment storage unit. It is a graph showing an example of a growth pattern stored in a growth pattern registration DB held by a childcare product recommendation server. It is a figure which shows an example of the screen layout of a growth record form. FIG. 3 is a diagram illustrating an example of a mixed image that includes a recommended product list, a pre-persona image, a post-persona image, and recommendation comments.

Embodiments of the present invention will be described below with reference to the drawings. Note that the same elements are denoted by the same reference numerals, and duplicate explanations will be omitted.

(Overall structure of childcare product recommendation system)
First, the configuration of a childcare product recommendation system 1 including a childcare product recommendation server 10 according to an embodiment of the present invention will be described.

FIG. 1 is a system configuration diagram of a childcare product recommendation system 1. As shown in FIG. 1, the childcare product recommendation system 1 includes a childcare product recommendation server (hereinafter also referred to as "recommendation server") 10, and a plurality of user terminal devices 30 (in FIG. , a fixed terminal device 30A, and mobile terminal devices 30B, 30C, 30D), which are connected to each other via the Internet N1.

The recommendation server 10 performs data processing according to a childcare product recommendation program and provides a childcare product recommendation service to the user. The child care products recommendation service is a service realized by applying the present invention. The childcare products recommendation service is a service in which childcare products that match characteristic data described below are presented to the user as recommended products. In this embodiment, the recommendation server 10 also provides a service other than the childcare products recommendation service if the user so desires.

The user terminal device 30 receives or transmits data to/from the recommendation server 10 .

In the childcare product recommendation system 1, the recommendation server 10 executes the following processes a), b), and c), and the childcare product determined in step c) is presented to the user terminal device 30 as a recommended product.
a) Judging the child's growth status to determine whether or not the child's growth is on track b) Generating characteristic data to include the results of the growth status judgment in a) c) Determining childcare products that match the characteristic data in b)

The user of the user terminal device 30 can purchase childcare products presented as recommended products. The recommendation server 10 executes a growth status determination to determine whether the child's growth is normal or not, and presents childcare products that match the characteristic data including the results as recommended products. Therefore, parents who are raising children can purchase childcare products based on their child's developmental progress, rather than their past history of product browsing.

(Configuration of recommended server 10)
Next, the configuration of the recommendation server 10 will be described with reference to FIG. 2. FIG. 2 is a block diagram mainly showing the internal configuration of the recommendation server 10. As shown in FIG. The recommendation server 10 is a server operated by a specialized business that provides childcare product recommendation services.

The recommendation server 10 includes a CPU (Central Processing Unit) 11, a ROM (Read Only Memory) 12, and a RAM (Random Access Memory) 13. The CPU 11 operates according to a program stored in the ROM 12, and inputs input data obtained by operating the keyboard 19 and mouse 20 via the KBC (Key board controller) 17 via the main bus 19A. It inputs and outputs signals with other components and controls the overall operation of the recommendation server 10. The CPU 11 operates a registration processing section 60, a growth status data recording processing section 70, a characteristic data generation section 80, and a recommendation processing section 90, which will be described later, in accordance with a child care product recommendation program, which will be described later. The ROM 12 stores a BIOS (Basic Input/Output System), control programs, and permanent data. The RAM 13 stores data used when the CPU 11 operates, and programs such as a member support program (a program used to execute member support processing, including the childcare products recommendation program according to the present invention).

In addition, the recommended server 10 includes a hard disk drive (HDD) 14, a communication control section 15, a communication processing section 16, and a video controller 18.

The hard disk device 14 stores middleware such as an OS (Operating System), a DBMS (Database Management System), and a Web server program. In addition, the hard disk device 14 is formed with programs such as a childcare products recommendation program, various storage units or DBs (databases) shown in FIGS. 4 and 5 necessary for their execution, and other storage units, DBs, and files. There is. Here, FIG. 4 is a functional block diagram showing the main configuration of the recommendation server 10 that implements childcare product recommendation processing, and FIG. 5 is a functional block diagram showing the main configuration of the recommendation processing unit 90 together with various main storage units or DBs. It is a block diagram.

As shown in FIGS. 4 and 5, the hard disk drive 14 includes a member master 101, a child master 102, a growth status data storage DB 103, a characteristic data storage DB 104, a growth guideline table (TBL) 110, a growth pattern registration DB 111, and recommended products. A decision table (TBL) 112, a recommended product master 113, a recommended comment storage section 114, a recommended product data file 116, a preliminary image data storage section 117, a subsequent image data storage section 118, and a persona basic data storage section 121 are formed. Each storage unit, DB, and file will be described later.

The communication control unit 15 operates according to instructions from the CPU 11 to control connection and disconnection of lines for communicating with the user terminal device 30 and a server (not shown). The communication processing unit 16 operates according to instructions from the communication control unit 15 to execute data transmission and reception via the Internet N1.

The video controller 18 controls image display on a display device (not shown) to display screens used for various settings.

The various storage units, DB, and files of the hard disk device 14 will be explained as follows. The member master 101 is a master file that stores data regarding members. In this embodiment, a member is a user who receives the childcare product recommendation service. Members are primarily expected to be parents of infants, but pregnant mothers and their spouses who are about to give birth can also become members. For example, as shown in FIG. 7, the member master 101 stores a record having nine fields from a member number field 101a to a held points field 101j.

The membership number unique to each member is stored in the member number field 101a. The member's name is stored in the member name field 101b. The membership classification field 101c stores the membership classification. The membership classification is data indicating whether the member is the member himself/herself who receives the childcare products recommendation service, his or her family (family member), or furthermore, whether the member is a friend or related person (friend member). The address field 101d and the Tel-No field 101e store the member's address and telephone number, respectively. The child name field 101f stores the member's child name. The gender field 101g stores data indicating the gender of the child (gender data). The birth order classification field 101h stores the birth order classification. The birth order category is data indicating the order in which children were born. For example, the data is "1" for the first child, and "2" for the second child. The held points field stores data indicating points held by the member. Points are earned by members using the childcare product recommendation service (or other optional services).

The child master 102 is a master file that stores data regarding children of members. The child master 102 and the member master 101 have a relationship using the member number as a key, and form an RDB (Relational Data Base).

As shown in FIG. 8, the child master 102 has a member number field 102a, a birth order classification field 102b, a child name field 102c, a gender field 102d, a date of birth field 102e, and birth information fields 102f, 102g, and 102h. The record is stored. Data common to the member master 101 is stored in the member number field 102a, birth order classification field 102b, child name field 102c, and gender field 102d. The date of birth field 102e stores data indicating the child's date of birth (date of birth data). The childbirth information fields 102f, 102g, and 102h store height data, weight data, and head circumference data at the time of childbirth.

(Development status data storage DB, characteristic data storage DB)
The growth status data storage DB 103 stores growth status data indicating the child's growth status. The growth status data storage DB 103 has a relationship with the member master 101 using the member number as a key. Growth status data mainly shows the physical growth status, but it also shows the growth status of the child's physical constitution, such as having dermatitis, asthma, food allergies, crying at night, being fussy, and being reluctant. Can contain data.

As shown in FIG. 9, the growth status data storage DB 103 includes a member number field 103a, a child name field 103b, a gender field 103c, a date of birth field 103cc, a physical data storage section 103d, a tooth data storage section 103g, and an operation availability data storage section. A record having a section 103h is stored. Data common to the member master 101 is stored in the member number field 103a, child name field 103b, and gender field 103c, respectively. The child's date of birth (same as the date of birth field 102e of the child master 102) is stored in the date of birth field 103cc.

The physical data storage unit 103d stores physical data (data used to identify the child's body, such as height, weight, and head circumference). The physical data storage section 103d includes a birth time storage section 103e and a measurement date data storage section 103f. The birth storage unit 103e and the measurement date data storage unit 103f each have fields corresponding to the child's height, weight, and head circumference. Data indicating the child's height, weight, and head circumference is stored in each field. The birth storage unit 103e stores data indicating the child's height, weight, and head circumference at the time of birth. The measurement date data storage unit 103f stores data indicating the height, weight, and head circumference at the time the measurement was performed (based on measurement days from measurement day 1 to measurement day 100).

The measurement date data storage unit 103f stores ratio data based on the height, weight, and head circumference at the time of birth (data in the storage unit 103e at the time of birth). For example, if the birth weight is 2.6 kg and the weight on the first measurement day (measurement day 1) is 3.6 kg, the "weight" on "measurement day 1" is 1.38 (3.6 kg). The ratio of .6 kg to 2.6 kg) is stored. The measurement date data storage unit 103f may store measurement values instead of ratio data.

The tooth data storage unit 103g has a tooth eruption start field g1 and a tooth number field g2 (the tooth eruption start field g1 and the tooth number field g2 are also collectively referred to as a tooth data field 103kc). A growth start code is set in the growth start field g1. The eruption code is data indicating whether teeth have started to erupt or not, and is set to "0" which means there is no teeth eruption, or "1" which means there is teeth eruption. The number field g2 stores number data ("0" to "9") indicating the number of erupting teeth.

The operation propriety data storage unit 103h has a plurality of operation fields 103ka corresponding to growth specific operations described later, and each operation field 103ka is assigned an operation code ("h1" to "h20") specific to the growth specific operation. ing. Operation propriety data 103kb is stored in each operation field 103ka, and based on the operation propriety data 103kb, it is possible to grasp whether or not the corresponding growth specifying operation is possible. The operation availability data 103kb is data indicating whether the corresponding growth specific operation is possible (possible) or not (impossible), and in this embodiment, "1" or "0" is set. Ru. "1" indicates that the growth specifying operation is possible, and "0" indicates that the growth specifying operation is not possible.

Developmental specific movements are movements performed by children that use the body (mainly limbs) (also called physical movements) and are useful for determining the progress of a child's development. It means an action. There are several growth specific movements, such as "crawling", "rolling over", "sitting down", and "grabbing and standing", and the others are illustrated in FIG. 9 (the growth specific movements are: Although there are other devices other than those shown in FIG. 9, their illustration is omitted). Unique motion codes such as "h1", "h2", "h3", etc. are assigned to these growth specifying motions. For example, "h6", "h5", "h3", and "h7" are assigned as action codes to "crawl", "turn over", "sit", and "stand up", respectively.

The feature data storage DB 104 stores feature data (also referred to as growth feature data) indicating features related to child development. In this embodiment, since the child's growth is understood mainly from the aspect of movements using the body including limbs (body movements), the characteristic data storage DB 104 includes a growth index data storage section 104g, which will be described later. It is provided.

The characteristic data storage DB 104 stores records having a member number field 104a, a child name field 104b, a gender field 104c, a date of birth field 104cc, a physical data storage section 104d, and a growth index data storage section 104g. Among these, the member number field 104a, child name field 104b, gender field 104c, date of birth field 104cc, and physical data storage section 104d are respectively stored in the member number field 103a, child name field 103b, and gender of the developmental status data storage DB 103. Data common to the field 103c, date of birth field 103cc, and physical data storage section 103d is stored.

The growth index data storage section 104g includes a body motion index section 104h, a tooth index section 104j, and a growth pattern section 104k. The body movement index section 104h has a plurality of growth index fields 104ma. A growth index code is assigned to each growth index field 104ma. The growth index code is used as an index for grasping the characteristics related to the child's growth, and is set to correspond to each of the above-mentioned movement codes ("h1" to "h20"). In this embodiment, growth index codes "h1f" to "h20f" are set to correspond to operation codes ("h1" to "h20"). A growth progress code 104mb is stored in each growth index field 104ma. The developmental progress code 104mb indicates whether the child's development is on track, ahead of schedule, or delayed. In the present embodiment, "0", "8", and "9" are set as data indicating respectively on track, advance, and delay.

The tooth index section 104j has a tooth index field g1f and a number index field g2f (the tooth index field g1f and the number index field g2f are collectively referred to as a tooth index field 104mc). are doing. A growth progress code 104mb is stored in the growth index field g1f and the number index field g2f, similarly to the growth index field 104ma. A growth pattern described later is stored in the growth pattern section 104k.

(growth guideline table)
The growth guideline table 110 is a growth guideline data storage means according to the present invention, and has a data structure as shown in FIG. 11 in this embodiment. The growth guideline table 110 stores data indicating a guideline when a child's growth is normal. As shown in FIG. 11, the growth guideline table 110 has a number of months after birth data section 110a and a guideline data section 110b, both of which are associated with each other and set with availability data 110e or number guideline data 110f, which will be described later. ing.

The number of months after birth data section 110a stores the number of months after birth of the child (in FIG. 11, positive integers from "2" to "18"). In this embodiment, since "2" is the minimum number of months after birth, the minimum number of months is "2".

The guideline data section 110b includes a tooth guideline data section 110c and a body movement guideline data section 110d. The tooth guideline data section 110c has a tooth eruption start field gg1 and a tooth number field gg2. The beginning of eruption field gg1 and the number field gg2 are formed to correspond to the beginning of eruption field g1 and the number field g2 of the tooth data storage section 103g, respectively. In the eruption start field gg1, availability data 110e is set, and in the number field gg2, number guideline data 110f (data indicating the guideline for the number of teeth; in FIG. 11, an integer from "0" to "7") is set. It is set. The body motion guideline data section 110d has a plurality of fields ("hh1" to "hh20"), each of which is formed to correspond to a motion code ("h1" to "h20").

Then, in each field unit of the tooth guideline data section 110c and the body motion guideline data section 110d, the time when physical motion becomes possible (possible) for the first time (for teeth, the time when the first teeth start to grow) is determined. The availability data 110e is set so that the timing) becomes clear. For example, in the case of the body motion guideline data section 110d, for the field "hh3", the feasibility data 110e are sequentially "0", "0", "0", " They are set as 0", 1, 1, 1, etc. "0" and "1" in the availability data 110e indicate that the growth specifying operation is not possible and that the growth specifying operation is possible, respectively, similar to the operation availability data 103kb described above. "1" corresponds to possible data according to the present invention.

In the field "hh3", "0" is set in the acceptability data 110e for the number of months after birth "2" to "5", and "1" is set for all months after birth "6". This means that the physical movement corresponding to field "hh3" ("sitting" corresponding to motion code "h3") becomes possible for the first time at the age of "6" (in this case, "6" is the initial possible number of months). ). In addition, since "0" is set in the availability data 110e for the number of months after birth "2" to "5", physical movement is not possible from the minimum number of months to the number of months smaller than the initial possible number of months. It is shown that. Further, the availability data 110e is set so that the physical movement becomes possible after the initial possible number of months ("6" in the field "hh3").

A plurality of growth patterns are registered in the growth pattern registration DB 111. For example, growth patterns Pa, Pb, Pc, and Pd as shown in FIG. 21 are registered in the growth pattern registration DB 111. In general, children are small at birth but grow quickly afterward (relatively fast weight gain), and children are large at birth but grow slowly afterward (relatively fast weight gain). There are multiple patterns, such as the slow) pattern. The child's growth status data is collected, a plurality of growth patterns are set from the data, and data indicating the growth pattern is registered in advance in the growth pattern registration DB 111 as growth pattern data. For example, the correspondence between the number of days after birth and body weight can be quantified (further, linear approximation, logarithmic approximation, exponential approximation, etc., and the result can be expressed as a formula) and registered as growth pattern data.

Next, the registration processing section 60, growth status data recording processing section 70, characteristic data generation section 80, and recommendation processing section 90 will be explained.

The registration processing unit 60 includes a member registration unit 61 and a child data registration unit 62, as shown in FIG. The member registration unit 61 transmits a member registration form (not shown) (input screen data used for member registration) to the user terminal device 30, and causes the member master 101 to store the data input using the member registration form. The child data registration unit 62 is a child data input means, and transmits a child registration form (not shown) (input screen data used for registering data regarding children) to the user terminal device 30, and input data using the child registration form. Data such as date of birth data is stored in the child master 102.

The growth status data recording processing section 70 corresponds to growth status data input means. The growth status data recording processing unit 70 transmits the growth record form 300 to the user terminal device 30, and stores the data input using the growth record form 300 in the growth status data storage DB 103.

As shown in FIG. 22, the growth record form 300 includes a member child data display section 301, a growth status data input section 302, and progress status input sections 303 and 304. The member child data display section 301 displays data that has been input into the member master 101 and child master 102, such as member number, member name, child name, and date of birth. The growth status data input section 302 has input sections for measurement date, height, weight, and head circumference. The input data using these are stored in the corresponding fields of the physical data storage section 103d. The progress status input section 303 receives input as to whether or not the child has been able to perform growth specific movements such as sitting down and rolling over. In the progress status input section 304, whether or not teeth have started to grow and the number of teeth when teeth have started to grow are input. Using the data input from the progress status input unit 303, 103kb of operation availability data is stored in the corresponding operation field 103ka of the operation availability data storage unit 103h (at the time of childbirth, all of the 103KB of operation availability data is set to "0". " is set, and "1" is set in the operation propriety data 103kb of the completed growth specific motion). Data input from the progress status input section 304 is used to store data in the tooth data field 103kc.

The characteristic data generation unit 80 uses the growth condition data stored in the growth condition data storage DB 103 to execute the growth condition determination described later while accessing the growth guide table 110 and the growth pattern registration DB 111, thereby generating characteristic data. generate. Details of the feature data generation section 80 will be described later.

The recommendation processing section 90 has a function of presenting childcare products that match the characteristic data as recommended products, and corresponds to recommended product presentation means according to the present invention. Further, since the recommendation processing unit 90 has a function of presenting a pre-persona image and a post-persona image, which will be described later, it also corresponds to image presentation processing.

As shown in FIG. 5, the recommendation processing section 90 includes a determination processing section 91, a list creation section 92, a pre-persona image generation processing section 93, a post-persona image generation processing section 94, and a presentation processing section 95. The determination processing unit 91 uses the characteristic data stored in the characteristic data storage DB 104 to perform a recommended product determination process described later while accessing a recommended product determination table 112 and a recommended product master 113, which will be described later. A data file 116 is generated. The list creation unit 92 inputs the data stored in the recommended product data file 116 and creates a recommended product list L1 in which recommended products are listed. The preliminary persona image generation processing unit 93 performs preliminary image generation processing, which will be described in detail later, generates preliminary image data, and stores the preliminary image data in the preliminary image data storage unit 117. As will be described in detail later, the post-persona image generation processing section 94 performs post-image generation processing, generates post-image data, and stores the post-image data in the post-image data storage section 118. The presentation processing unit 95 inputs the recommended product list L1, the prior image data in the prior image data storage unit 117, and the post-image data in the post-image data storage unit 118, and creates the recommended product list L1, the pre-persona image, and the post-persona image. Execute presentation processing to present to the user (details will be described later).

(Configuration of user terminal device 30)
As shown in FIG. 1, the user terminal device 30 is equipped with a connection environment to the Internet N1 and can communicate with the recommendation server 10. Note that in the following description, a mobile terminal device 30B (portable notebook personal computer) is assumed as the user terminal device 30, but the user terminal device 30 may be a fixed terminal device 30A. The fixed terminal device 30A is, for example, a stationary personal computer. The mobile terminal devices 30C and 30D are assumed to be, for example, a high-performance mobile phone (also referred to as a smartphone) or a tablet-type terminal device.

As shown in FIG. 3, the user terminal device 30 includes a CPU 31, a ROM 32, a RAM 33, a data storage section 34, and a liquid crystal display section 35. Further, the user terminal device 30 includes a voice conversion processing section 36, a communication control section 37, a communication processing section 38a, a wireless communication section 38b, a speaker 39, and a microphone 40.

The CPU 31 operates according to a program stored in the ROM 32 and controls the operation of the user terminal device 30 as a whole. The ROM 32 stores a control program executed by the CPU 31. The RAM 33 stores a communication control program for data communication, data necessary for the CPU 31 to execute the program, and the like.

The data storage unit 34 stores various data and application programs. The liquid crystal display section 35 is an image display means that includes an LCD (Liquid Crystal Display) and its driving section, and displays images such as characters, figures, and symbols. The audio conversion processing section 36 expands the audio data and outputs it to the speaker 39, while converting and compressing the analog audio signal input from the microphone 40 into digital audio data and inputting it to the communication processing section 38a. The communication control unit 37 operates in response to instructions from the CPU 31 and controls connection and disconnection of lines for data communication. The communication processing unit 38a operates according to instructions from the communication control unit 37 to execute data transmission and reception via the Internet N1. The wireless communication unit 38b is a wireless communication means that transmits and receives data wirelessly under the control of the communication control unit 37. The speaker 39 is an audio output means that outputs audio, and the microphone 40 inputs audio such as the contents of a user's conversation and converts it into an electrical signal.

Then, the CPU 31 operates a list acquisition section 401, a list display control section 402, a preliminary image acquisition section 403, a post-image acquisition section 404, and an image display control section 405, which will be described later, in accordance with a recommended product acquisition program, which will be described later. reference). As a result, a recommended product list L1, a pre-persona image, and a post-persona image, which will be described later, are displayed on the liquid crystal display section 35 of the user terminal device 30.

(Operation details of childcare product recommendation system)
Next, with reference to FIGS. 12 to 17 as well as FIGS. 4 and 5, the operation contents of the member support process including the childcare product recommendation process by the recommendation server 10 will be described.

In the recommendation server 10, the CPU 11 executes member support processing according to the member support program. Since the childcare products recommendation program according to the present invention is incorporated into the member support program, the childcare products recommendation process is executed by executing the member support process.

When the childcare product recommendation process is executed, the CPU 11 uses the growth guideline table according to the data input using the user terminal device 30 (mainly growth status data including child's date of birth and weight data). 110, operate the feature data generation section 80 and recommendation processing section 90 while accessing the recommended product determination table 112 and the like. As a result, child care product recommendation processing is executed. The childcare product recommendation program is a program that realizes the characteristic data generation section 80 and the recommendation processing section 90 in the recommendation server 10, and causes the recommendation server 10 to function as a growth status determination means, a characteristic data generation means, and a recommended product presentation means. be.

When the recommendation server 10 executes the member support process, the CPU 11 executes the process according to the flowchart shown in FIG. 12 according to the member support program. FIG. 12 is a flowchart illustrating an example of the operating procedure of the member support process executed by the CPU 11. Note that "S" in FIGS. 12, 13, etc. is an abbreviation for step.

When starting the member support process, the CPU 11 first performs a member registration process in step 1. Here, the member registration section 61 operates and transmits a member registration form to the user terminal device 30. When the user uses the user terminal device 30 to input data according to the member registration form, the user terminal device 30 receives data necessary for registering a member to receive the childcare products recommendation service, such as member number and member name. The data is sent to the recommendation server 10, and the member registration unit 61 stores the data in the member master 101.

Next, the CPU 11 advances the process to step 2 and performs child data registration processing. Here, the child data registration unit 62 operates and transmits the child registration form to the user terminal device 30. When the user uses the user terminal device 30 to input data according to the child registration form, data such as the child's name and date of birth are transmitted from the user terminal device 30 to the recommendation server 10. Then, the child data registration unit 62 stores data such as the child's name and date of birth data in the child master 102.

Subsequently, the process proceeds to step 3, and a growth recording process is executed. Here, the growth status data recording processing unit 70 operates and transmits the growth record form 300 to the user terminal device 30. When the user uses the user terminal device 30 to input data according to the growth record form 300, data such as weight data, height data, measurement date, etc. as growth status data, and whether each growth specific action was completed or not are displayed. data is transmitted from the user terminal device 30 to the recommendation server 10. Then, the growth status data recording processing unit 70 stores the data in the growth status data storage DB 103.

Subsequently, when the process proceeds to step 4, the CPU 11 executes a childcare product recommendation process, which will be described later, in accordance with the childcare product recommendation program. Thereafter, the process proceeds to step 5, where it is determined based on the input data from the user terminal device 30 whether or not to use the optional service. If it is determined that the optional service is to be used, the process proceeds to step 6, and if it is not determined that the optional service is to be used, the process proceeds to step 7.

In step 6, optional service processing is executed. Optional services are services related to member support and are separate from the child care product recommendation service. Optional services are performed according to member requests. For example, optional services include providing information on childcare supplies, making reservations at childcare support facilities available to members, using a chat function regarding childcare support, consulting with experts on childcare support, receiving remote medical examinations from medical institutions, and receiving vaccinations. , sample monitor business, etc.

Upon completion of step 6, the process proceeds to step 7, where point calculation processing is executed. In the point calculation process, points earned by the user are added by purchasing childcare products (childcare products different from recommended products), recommended products, and other optional services are added, and points are subtracted by using points. be done. When step 7 ends, the member support process ends.

(Recommended processing for childcare products: S4)
The CPU 11 executes childcare product recommendation processing according to the flowchart shown in FIG. The details of the recommended processing for childcare products are as follows.

When the child care product recommendation process starts, the process proceeds to step 11. In step 11, the feature data generation section 80 operates according to instructions from the CPU 11. The feature data generation unit 80 executes feature data generation processing according to the flowchart shown in FIG. The characteristic data generating section 80 has a function as a growth status determining means and a characteristic data generating means according to the present invention.

(Feature data generation process: S11)
In the feature data generation process, feature data is generated so as to include the results of growth status determination, which will be described later, by executing a feature extraction process, which will be described later.

Then, as shown in FIG. 14, when the feature data generation unit 80 starts the feature data generation process, the process proceeds to step 21. In step 21, the growth status data stored in the growth status data storage DB 103 is read. Processing then proceeds to step 22. In step 22, the data stored in the member number field 103a, child name field 103b, gender field 103c, date of birth field 103cc, and physical data storage section 103d among the growth status data is transferred to an output record (not shown). It is set in the corresponding field of the output record (corresponding to the record layout of the feature data storage DB 104). Subsequently, the process proceeds to step 23, where a feature extraction process to be described later is executed. In the feature extraction process, data set in the growth index data storage section 104g is generated using the growth status data. After the feature extraction process is executed, the process proceeds to step 24. In step 24, a process is executed in which the output record is written to the feature data storage DB 104, and the feature data is stored in the feature data storage DB 104. When step 24 is executed, the feature data generation process ends. Then, in FIG. 13, the process advances to step 12, and a recommended product determination process, which will be described later, is executed.

(Feature extraction process: S23)
The feature extraction process is executed by the feature data generation unit 80 according to the flowchart shown in FIG.

When the feature data generation unit 80 starts the feature extraction process, the process proceeds to step 31. In step 31, "0" is set in the field corresponding to the tooth index section 104j of the output record. In the next step 32, "0" is set in the field corresponding to the body movement index section 104h of the output record. In steps 31 and 32, the tooth index section 104j and the body motion index section 104h are initialized.

Next, the process proceeds to step 33, where the number of months Ma of birth is calculated using the date of birth in the date of birth field 103cc. In the following steps 34, 35, and 36, the growth status determination according to the present invention is executed (in detail, steps 34 and 36). In the growth status determination, whether or not the child's growth is going well is determined for each operation code ("h1" to "h20") using the growth status data.

In step 34, the birth month Ma is set as a search key, and the birth month data section 110a of the growth guideline table 110 is searched. Then, a record in which the number of months of birth Ma matches the number of months of birth data section 110a (data corresponding to the number of months of birth Ma in the growth guideline table 110, and corresponds to corresponding guideline data of the present invention) is stored in the growth guideline table. 110. In the subsequent step 35, tooth index data generation processing, which will be described later, is executed to generate data (tooth index data) to be set in the tooth index section 104j. In the next step 36, a body motion index data generation process to be described later is executed to generate data (body motion index data) to be set in the body motion index section 104h. Then, in the next step 37, a growth pattern determination process to be described later is executed, and data (growth pattern data) to be set in the growth pattern section 104k is generated. Thereafter, when the process proceeds to step 38, the tooth index data, body movement index data, and growth pattern data generated in steps 35 to 37 are set in the respective corresponding fields of the output record. When step 38 is executed, the feature extraction process ends.

(Tooth index data generation process: S35)
Then, the tooth index data generation process is executed according to the flowchart shown in FIG. 16. When the tooth index data generation process is started, the process proceeds to step 41. In step 41, regarding the growth status data, whether the data in the eruption start field g1 (eruption start code) in the tooth data storage section 103g matches the data in the eruption start field gg1 in the tooth guideline data section 110c (approval data 110e)? It is determined whether or not. If the two match, the process proceeds to step 43, but if the two do not match, the process proceeds to step 42.

When the process proceeds to step 42, it is determined whether the growth start code of the growth start field g1 matches "1". When the growth start code matches "1", the process proceeds to step 45, but when the growth start code does not match "1", the process proceeds to step 46. When the process proceeds to steps 45 and 46, "8" and "9" are respectively set in the field corresponding to the growth start index field g1f in the output record.

When the process proceeds to step 43, regarding the growth status data, the data in the number field g2 of the tooth data storage section 103g (teeth number data) is changed to the data in the number field gg2 of the tooth guideline data section 110c (number guideline data 110f). It is determined whether or not they match. When the tooth number data matches the number guideline data 110f, the tooth index check process ends, but when the tooth number data does not match the number guideline data 110f, the process proceeds to step 44.

When the process proceeds to step 44, it is determined whether the tooth number data in the number field g2 is greater than the tooth number guideline data 110f in the number field gg2. When the tooth number data in the number field g2 is greater than the tooth number guideline data 110f in the number field gg2, the process proceeds to step 47, but when the tooth number data is smaller than the number guideline data 110f, the process proceeds to step 48. . When the process proceeds to steps 47 and 48, "8" and "9" are respectively set in the fields corresponding to the number index field g2f of the output record. When steps 47 and 48 are executed, the tooth index checking process ends.

In steps 41 and 42, the growth start field g1 and the number field g2 are compared with the growth guide table 110, respectively. When it is determined that they match in steps 41 and 42, it is determined that the tooth-related growth (in this embodiment, the beginning of tooth eruption and the number of teeth) is as per the growth guideline table 110 and is going well. be done. Furthermore, when the eruption start field g1 does not match the growth guideline table 110, if the eruption start code of the eruption start field g1 is "1", the teeth start to erupt is in the preceding state, and the eruption start field g1 indicates the eruption start state. When the code is not "1", it is determined that the beginning of teething is delayed. Furthermore, when the tooth number data in the number field g2 does not match the tooth number guideline data 110f in the number field gg2, and the tooth number data is larger than the tooth number guideline data 110f, the growth is in the preceding state, but this is not the case. It is determined that the condition is developmentally retarded.

As described above, the recommendation server 10 has a function as a tooth index data generation means that executes tooth index data generation processing so that the following tooth index data is generated. In the index data of the tooth, when the eruption start field g1 and the number field g2 match the growth guideline table 110, the tooth is developing smoothly, and the eruption start field g1 and the number field g2 match the growth guideline table 110. When it does not, it indicates early or delayed dental development.

(Body movement index data generation process: S36)
The body movement index data generation process is executed according to the flowchart shown in FIG. 17. In the body motion index data generation process, a progress determination process regarding growth specific motion is executed for each motion code "h1" to "h20". Body motion index data is generated according to the results.

The progress determination process regarding the growth specific motion is a process of determining whether each growth specific motion is smooth, leading, or delayed, using the motion availability data 103 kb, as viewed from the growth guideline table 110. In the progress determination process, the motion availability data 103kb of each motion code "h1" to "h20" is compared with the feasibility data 110e of the corresponding fields "hh1" to "hh20" of the body motion guideline data section 110d (in advance, In step 34, a record whose birth month Ma matches the birth month data field 110a is read from the growth guideline table 110). When the two match, it is determined that the growth related to the growth specific action corresponding to the action code is going well, and when they do not match, it is determined that the growth related to the growth specific action is advanced or delayed.

For the operation code "h1", steps 51, 52, 57, and 58 are executed. In step 51, regarding the growth status data, whether or not the motion availability data 103kb of the field corresponding to the motion code "h1" of the motion field 103ka matches the feasibility data 110e of the field "hh1" of the body movement guideline data section 110d. is determined. If the operability data 103kb matches the propriety data 110e, the process proceeds to step 53, but if the operability data 103kb does not match the propriety data 110e, the process proceeds to step 52. When the process proceeds to step 52, it is determined whether the operability data 103kb of the field corresponding to the operation code "h1" matches "1" (the determination in step 52 is the operability determination according to the present invention). ). When the operability data 103kb matches "1", the process proceeds to step 57, but when the operability data 103kb does not match "1", the process proceeds to step 58. When the process proceeds to steps 57 and 58, "8" and "9" are respectively set in the field corresponding to the growth index code "h1f" in the output record.

Similarly, steps 53, 54, 59, and 60 are executed for the operation code "h2," and steps 55, 56, 61, and 62 are executed for the operation code "h20."

In step 53, regarding the growth status data, it is determined whether the motion availability data 103kb of the field corresponding to the motion code "h2" of the motion field 103ka matches the feasibility data 110e of the field "hh2" of the body movement guideline data section 110d. is determined. When the operability data 103kb matches the propriety data 110e, the process proceeds to step 55, but when the operability data 103kb does not match the propriety data 110e, the process proceeds to step 54. When the process proceeds to step 54, it is determined whether the operation availability data 103kb in the field corresponding to the operation code "h2" matches "1". When the operability data 103kb matches "1", the process proceeds to step 59, but when the operability data 103kb does not match "1", the process proceeds to step 60. When the process proceeds to steps 59 and 60, "8" and "9" are respectively set in the field corresponding to the growth index code "h2f" in the output record.

Processing is similarly executed for operation codes "h3" to "h19" (not shown), and steps 55, 56, 61, and 62 are executed.

In step 55, regarding the growth status data, it is determined whether the motion availability data 103kb of the field corresponding to the motion code "h20" of the motion field 103ka matches the feasibility data 110e of the field hh20 of the body motion guideline data section 110d. be done. When the actionability data 103kb matches the actionability data 110e, the body motion index data generation process ends, but when the actionability data 103kb does not match the actionability data 110e, the process proceeds to step 56. When the process proceeds to step 56, it is determined whether the operation availability data 103kb of the field corresponding to the operation code "h20" matches "1". When the operation availability data 103kb matches "1", the process proceeds to step 61, but when the operation availability data 103kb does not match "1", the process proceeds to step 62. When the process proceeds to steps 61 and 62, fields corresponding to the growth index code "h20f" in the output record are set to "8" and "9", respectively.

When the tooth index data generation process and the body movement index data generation process in steps 35 and 36 are completed, the process proceeds to step 37 in FIG. 15, and a growth pattern determination process to be described later is executed. Thereafter, the process proceeds to step 38, and the tooth index data, body movement index data, and growth pattern generated in steps 35, 36, and 37 are set in the output record. When step 38 is executed, the feature extraction process ends. Then, in FIG. 14, the process proceeds to step 24. As described above, when step 24 is executed, the feature data generation process ends. When the characteristic data generation process is completed, the process proceeds to step 12 in FIG. 13, and a recommended product determination process, which will be described later, is started.

(Development pattern determination process: S37)
In the growth pattern determination process, the CPU 11 operates as a growth data reading section, an analysis processing section, and a growth pattern determination section. When the CPU 11 operates as a growth data reading section, it executes a process of reading the physical data stored in the physical data storage section 103d of the growth status data storage DB 103. Further, when the CPU 11 executes the operation as an analysis processing section, it accesses the growth pattern registration DB 111 and reads registered growth pattern data. The CPU 11 performs an analysis process regarding the physical data using each of the read growth pattern data, and outputs analysis data indicating the result. Furthermore, when the CPU 11 executes the operation as the growth pattern determining section, it selects the growth pattern data that is most similar to the physical data read by the growth data reading section from among the growth pattern data according to the output analysis data, This is determined as the optimal pattern. Data indicating the determined optimum pattern is set in a field corresponding to the growth pattern section 104k of the output record.

(Recommended product determination process: S12)
The recommended product determination process is executed by the determination processing unit 91 of the recommendation processing unit 90. When the determination processing unit 91 operates according to the instructions from the CPU 11, the determination processing unit 91 reads the characteristic data from the characteristic data storage DB 104 and determines the recommended product by referring to the recommended product determination table 112. The determination processing section 91 has a function as a recommended product determination means according to the present invention.

The recommended product determination table 112 is recommended product determination data storage means according to the present invention, and has a data structure as shown in FIG. The recommended product determination table 112 has a tooth index section 112b1 and a body motion index section 112b2. An index correspondence section 112fa and a progress code area 112fb are provided in the tooth index section 112b1 and the body movement index section 112b2. The index correspondence unit 112fa has individual areas corresponding to each of the growth start index field g1f, the number index field g2f, and each growth index code ("h1f" to "h20f"), and each of the individual areas has a growth progress code ( A progress code area 112fb corresponding to the progress code ("0", "8", "9") is allocated. Appropriately recommended products are associated with each progress code area 112fb, and recommendability data indicating whether or not the product can be recommended is set.

Here, the recommended products are childcare products that the recommendation server 10 according to the present invention encourages the user to purchase and use. In this embodiment, a plurality of types of childcare products are targeted as recommended products. Appropriate recommended products are recommended products that are suitable for each of a plurality of growth-specific movements. For example, the "sitting practice chair" (h32 in Figure 18) is a recommended product and is suitable for practicing the invention-specific motion of sitting (motion code "h3"), so motion code "h3" is appropriate. This is a recommended product. However, the "sitting practice chair" (h32 in FIG. 18) is not suitable for practicing the invention-specific action of grasping a toy (action code "h2"), and therefore is not an appropriate recommended product for action code "h2". In this way, in the recommended product determination table 112, the childcare products that the recommendation server 10 recommends to the user for purchase and use are registered (as appropriate recommended products) in consideration of their relevance to the invention specifying operation.

Recommendability data is data indicating whether recommendation is possible, and in this embodiment, "7" indicates that recommendation is possible, and a space (blank in FIG. 18) indicates that recommendation is not possible. . When "7" is set for each appropriate recommended product, it is determined as a recommended product. For example, for the h21 building blocks, the growth index code "h2f" has a growth progress code of "0" and the progress code area 112fb of "8" is set to "7" indicating that it is recommended. Therefore, when the progress of the growth specific action ("grasping a toy") corresponding to the growth index code "h2f" is smooth or ahead, it is determined as a recommended product. However, since "7" is not set in the progress code area 112fb for the growth progress code "9", if the progress status is delayed, it will not be determined as a recommended product. This means that ``building blocks'' are determined as the recommended product when the invention-specific action ``grasping a toy'' is going well or ahead of time, but when ``grasping a toy'' is delayed, ``building blocks'' are recommended. This indicates that it cannot be determined as a product.

Then, when the decision processing unit 91 starts the recommended product decision process, the decision processing unit 91 reads the feature data generated in the above-described feature data generation process (S11) from the feature data storage DB 104. Further, the determination processing unit 91 reads out all the growth progress codes 104mb stored in the tooth index section 104j and the body movement index section 104h of the growth index data storage section 104g of the characteristic data. The eruption start index field g1f, number index field g2f of the tooth index section 104j, and the plurality of growth index fields 104ma (h1f, h2f...h20f) of the body movement index section 104h have "0" and "8", respectively. , a growth progress code of "9" 104mb is set. Therefore, when all the developmental progress codes 104mb are read out at once, a total of 22 digits (2 digits + 20 digits) of data (for example, 00009800000... ..., also referred to as "readout index data") are read out. The reading index data corresponds to g1f, g2f, h1f, h2f...h20f in order from the beginning, so which one of g1f, g2f, h1f, h2f...h20f corresponds to the number of digits from the beginning. It is determined whether the data corresponds to the field.

When the readout index data is used sequentially from the beginning, an individual area (search area) to which the recommended product determination table 112 is referred is specified. At this time, an individual area in the index correspondence section 112fa that corresponds to the number of digits from the beginning of the read index data is specified as the search area. For example, when the fifth digit of the read index data is used, the index corresponding section 112fa stores "g1f", "g2f", "h1f", "h2f", "h3f", "h4f", etc. ... is set, and the fifth one is "h3f", so the individual area with the growth index code "h3f" is specified as the search area. Further, the progress code area 112fb corresponding to the corresponding number of digits of the read index data is referred to, and recommended products to which "7" is set are extracted. For example, when the fifth digit of the read index data is "9", the record whose progress code area 112fb is "9" in the individual area "h3f" of the index correspondence section 112fa is referred to. At this time, according to FIG. 18, since "7" is set for the cushion "h31" and the practice chair "h32", this cushion and the practice chair are determined to be recommended products.

Recommended products are determined by performing similar processing on all digits of read index data. Further, the determination processing unit 91 accesses the recommended product master 113 and obtains product descriptions (product name, manufacturer, price, usage method, and images showing them) regarding the determined recommended product from the recommended product master 113. The related data (recommended product list data) is read out, and the recommended product list data is stored in the recommended product data file 116. After that, the recommended product determination process ends. As shown in FIG. 13, when step 12 is completed, the process proceeds to step 13.

When the process proceeds to step 13, the list creation section 92 is activated in response to an instruction from the CPU 11. The list creation unit 92 executes recommended product list creation processing. As shown in FIG. 19, by executing steps 13 to 17, the list creation section 92, pre-persona image generation processing section 93, post-persona image generation processing section 94, and presentation processing section 95 operate in sequence.

When the list creation unit 92 executes the recommended product list creation process, a recommended product list L1 is created. The recommended product list L1 is a list showing the recommended products determined in step 12. At this time, the list creation unit 92 reads recommended product list data from the recommended product data file 116, edits the recommended product list data as appropriate, and creates a recommended product list L1.

Next, when the process proceeds to step 14, the pre-persona image generation processing unit 93 operates according to instructions from the CPU 11. The preliminary persona image generation processing unit 93 generates a preliminary persona image using the feature data in the characteristic data storage DB 104, and preliminary image data corresponding to the generated preliminary persona image is stored in the preliminary image data storage unit 117. . In the recommendation server 10, a plurality of image data (also referred to as persona basic data) representing typical children according to their age and gender are prepared and stored in the persona basic data storage unit 121. The advance persona image generation processing unit 93 uses the persona basic data to select image data according to the child's age and gender based on the feature data in the feature data storage DB 104, and converts the child's facial expression into a developmental progress code 104mb. Generate a preliminary persona image by changing it according to the information.

The pre-persona image is a persona corresponding to the feature data generated using the feature data, and is a persona before the child uses the above-mentioned appropriately recommended product (appropriately recommended product listed in the recommended product list L1). This is an image showing a persona before the appropriate recommended product is used (also referred to as a preliminary persona). The advance persona is a persona that corresponds to characteristic data, so it is a persona that corresponds to the child's developmental status. Note that a persona generally refers to a typical user of a product or service. The persona image is an image in which the persona can be visually recognized. The image generated in step 14 is an image corresponding to the child's state before using the appropriate recommended product. For example, with respect to motion code h3, in the case of a child in a delayed state, an image of the child with a sad expression due to difficulty in sitting down corresponds to the preliminary persona image. Furthermore, when a preliminary persona image is generated, the number of developmental progress codes indicating that the child's development is delayed is measured using feature data, and the facial expression can be changed according to the number. In more detail, the number of "9"s (also referred to as the number of delays) indicating a delay state included in the data (the "readout index code" described above) in which the developmental progress code 104mb is read out at once is measured, and the delay is calculated. The larger the number, the sadder the expression can be made (the smaller the number of delayed expressions, the less sad the expression).

Next, when the process proceeds to step 15, the comment handling section 96 operates to execute comment handling processing. In the comment handling process, the comment handling unit 96 accesses the recommended comment storage unit 114, which will be described later, and stores the recommended comments stored in the recommended comment field 114c (recommendations corresponding to the index code field 114a and the developmental progress code field 114b). comments) and create a comment-corresponding file 119.

Here, the recommended comment storage unit 114 has an index code field 114a, a growth progress code field 114b, and a recommended comment field 114c, as shown in FIG. The index code field 114a is formed to correspond to the growth index field g1f, the number index field g2f, and the growth index field 104ma. The growth progress code field 114b is formed to correspond to a growth progress code. A recommended comment is written in the recommended comment field 114c. For example, comments regarding the recommended recommended product include the types of toys recommended, how to practice specific developmental movements, and the effects on children who use the recommended recommended product. Additionally, comments from mothers who have experience raising children, comments from doctors, etc. are also written in the recommended comment field 114c.

The comment correspondence file 119 stores, together with recommended comments, data (developmental change data) indicating changes that may occur in the child's development due to execution of processing in accordance with the recommended comments. For example, the following image data regarding child C who is delayed in grasping a toy may be considered. As a result of child C's practice using the recommended products, image data can be considered that shows that he is now able to grasp toys with his hands, has become interested in eating with his hands, and as a result has progressed in weaning food.

Subsequently, when the process proceeds to step 16, the post-persona image generation processing section 94 is activated. The post-persona image generation processing unit 94 generates a post-persona image, and post-image data corresponding to the generated post-persona image is stored in the post-image data storage unit 118. Similar to the pre-persona image generation processing section 93, the post persona image generation processing section 94 uses the feature data in the feature data storage DB 104 and the persona basic data in the persona basic data storage section 121, and further uses recommended products in the recommended product data file 116. A post-persona image is generated using the recommended comments in the recommended comment storage unit 114 and the developmental change data in the comment-corresponding file 119 along with the list data. The post-persona image generation processing unit 94 generates a post-persona image by changing the facial expression of the child according to the feature data and the persona basic data according to the recommended product list data, recommended comments, and developmental change data. The post-persona image is an image that shows the persona after the child has used the appropriately recommended product listed in the recommended product list L1 and/or after the comment response has been executed. For example, an image of a child with a happy expression because he or she has become able to sit well after practicing using appropriate recommended products corresponds to the post-persona image.

In addition, as mentioned above, when a preliminary persona image is generated by changing the child's facial expression according to the number of delays, the number of delays is modified according to the number of improvements after the progress data below. You can change the child's facial expressions. More specifically, the number of delayed items is set to a negative (minus) integer, and the progress data of a positive (plus) integer is set to each of the recommended comments, growth change data, and recommended product list data (for each recommended product). Then, the number of improvements is calculated by the sum of the number of delays and each piece of progress data. The larger the number of improvements, the happier the expression can be.

Subsequently, when the process proceeds to step 17, the presentation processing unit 95 is activated according to an instruction from the CPU 11. The presentation processing unit 95 executes list/image presentation processing. Then, the communication control unit 15 and the communication processing unit 16 are activated to perform data communication with the user terminal device 30. Subsequently, the presentation processing unit 95 presents the recommended product list L1 to the user terminal device 30. As shown in FIG. 19, in the user terminal device 30, a list acquisition unit 401 and a list display control unit 402 operate according to instructions from the CPU 31 to acquire a recommended product list L1 presented from the recommendation server 10, and The product list L1 is displayed on the liquid crystal display section 35.

Further, the presentation processing unit 95 serving as an image presentation unit reads the preliminary image data stored in the preliminary image data storage unit 117 and transmits the preliminary image data to the user terminal device 30, thereby presenting the preliminary persona image. . As shown in FIG. 19, in the user terminal device 30, a preliminary image acquisition unit 403 operates according to instructions from the CPU 31 to acquire preliminary image data transmitted from the recommendation server 10.

Further, the presentation processing unit 95 reads out the post-image data stored in the post-image data storage unit 118 and transmits the post-image data to the user terminal device 30, thereby presenting the post-persona image. Then, as shown in FIG. 19, in the user terminal device 30, the post-image acquisition unit 404 operates according to instructions from the CPU 31, and obtains post-image data presented from the recommendation server 10. Thereafter, in the user terminal device 30, the image display control unit 405 operates according to instructions from the CPU 31. Then, the pre-persona image and the post-persona image are displayed on the liquid crystal display section 35 using the pre-image data and post-image data presented from the recommendation server 10.

As described above, when the list/image presentation process is executed, the CPU 11 operates as a presentation control means and controls so that the pre-persona image and the post-persona image are presented together with the recommended product list L1. is preferred.

Then, for example, a mixed image LX as shown in FIG. 23 is displayed on the user terminal device 30. The mixed image LX includes a recommended product list L1, a pre-persona image display section L2, a post-persona image display section L3, and a recommended comment display section L5. In the mixed image LX, the display section L2 and the display section L3 are arranged side by side on the left and right, and an arrow L4 directed from the display section L2 to the display section L3 is also written. When step 17 ends, the list/image presentation process ends, and the childcare products recommendation process ends.

As described above, in the childcare product recommendation system 1 having the recommendation server 10 according to the embodiment of the present invention, the user (member) uses the user terminal device 30 to collect data regarding the child's growth status (at least weight, preferably By inputting the progress status of the growth specific movement (weight, height, head circumference), the recommendation server 10 determines recommended products according to the progress of the growth specific movement, and creates a recommended product list L1 containing the recommended products. present. The recommended products presented through the recommended product list L1 are adapted to the characteristics of the child's physical movements. For example, if you have a 6-month-old child (C1, not shown) who can sit up and a 6-month-old child (C2, not shown) who cannot sit up, an exercise chair is recommended for child C1. Although not presented, the same practice chair is presented as a recommendation to child C2. The product recommendations presented will reflect differences in each child's developmental progress. In addition, by presenting recommended products that match the characteristics of body movements, it is thought that the possibility of purchasing the recommended products increases. It is also very effective for business operators.

In the recommendation server 10, recommended products are determined using the results of the growth status determination using the acceptability data 110e of the growth guideline table 110, so objectivity is ensured in the growth status determination. Further, by determining the growth status, it is determined whether each growth specifying operation is normal, leading, or delayed, and recommended products are determined according to the results. Therefore, recommended products are determined in a manner that more accurately matches the progress of the growth specific operation. Since the progress status is determined to be one of three patterns: smooth, ahead, and delayed, no complicated processing is required for the determination.

Furthermore, since a preliminary persona image is presented, the child's current developmental progress can be visualized from the facial expressions shown in the preliminary persona image. Users can understand whether their child is on track, ahead of schedule, or behind schedule. Since the progress, lead, and delay are determined by determining the growth status using a growth guideline table, the user can objectively perceive the growth status. By displaying the post-persona image together with the pre-persona image, the effects of using recommended products can also be visualized. From the change in facial expression from the pre-persona image to the post-persona image, the user can more reliably realize the effects of using the recommended product.

By referring to the recommended comments by the user, in addition to the time and effort required to purchase childcare products, the time and effort required to collect information regarding childcare is eliminated, leading to a reduction in the burden of childcare. In particular, when a pre-persona image and a post-persona image are displayed in contrast with the recommended product list L1 as in the mixed image LX, the two can be easily compared, and the user can You can feel the effects more reliably.

For parents raising children, it may not be clear whether or not their child's development is on track. Children acquire a variety of movements as they grow, and the types of movements are wide-ranging. Therefore, it is very time-consuming to check and understand whether children are on track to acquire each movement, are ahead of the curve, or are behind the curve. In this regard, the childcare product recommendation server 10 according to the present invention not only presents recommended products but also presents recommended comments. Therefore, by referring to the recommended comments, parents who are raising children can understand whether their child's development is going well or not for each developmental specific movement. Additionally, in addition to knowing whether the child's development is on track, parents raising children will also have the opportunity to access medical services if necessary.

(Modified example)
Furthermore, the user terminal device may be a high-performance mobile phone instead of a notebook computer. The childcare products recommendation program executed by the CPU 11 can be recorded on various recording media such as a magnetic recording medium, CD-ROM, and DVD, or can be downloaded from a server (not shown) via a network. The recommended server 10 is not only configured by a server device, but can also be configured by a virtual server built on a cloud computing service.

An electronic maternal and child notebook can also be created by utilizing data stored in the member master 101, child master 102, and growth status data storage DB 103. In particular, the operation availability data storage section 103h of the growth status data storage DB 103 stores information as to whether or not there has been a change in the growth specific operation. Therefore, by storing these data in association with video data showing the child's behavior at that time, a growth record that accurately reflects the child's growth status is stored in the recommendation server 10.

Further, in the above embodiment, the growth status data storage DB 103 is provided with the operation permission data storage section 103h, and the permission/inhibition of the child's growth specific movement is stored. In addition, a field (constitutional data field) for storing data regarding the child's constitution is provided in the growth status data storage DB 103, and data regarding the child's constitution (for example, data indicating whether there is dermatitis or not, and whether there is asthma) is provided in the growth status data storage DB 103. It is possible to store data (also referred to as "physical constitution data") as growth status data, such as data indicating whether the child has or does not have a diet, data indicating whether the child has a thin or fat diet, and whether he or she cries at night. Then, using the physical constitution data, a growth status judgment is made to determine whether growth is going well or not, characteristic data is generated to include the results, and childcare products that match the characteristic data are presented as recommended products. You can make it happen.

The above description is an explanation of the embodiments of the present invention, and does not limit the apparatus and method of the present invention, and various modifications can be easily implemented. Furthermore, the present invention also includes devices or methods configured by appropriately combining components, functions, features, or method steps in each embodiment.

By applying the present invention, it is possible to present recommended childcare products that are suitable for the child's physical movement characteristics and constitution so that differences in developmental progress are reflected. INDUSTRIAL APPLICATION This invention can be utilized in the field of a childcare product recommendation device and a childcare product recommendation program.

DESCRIPTION OF SYMBOLS 1...Childcare products recommendation system, 10...Childcare products recommendation server, 11, 31...CPU, 30...User terminal device, 80...Feature data extraction part, 90...Recommendation processing part, 91...Decision processing part, 92...List creation part , 93... Pre-persona image generation processing section, 94... Post-persona image generation processing section, 95... Presentation processing section, 103... Growth situation data storage DB, 104... Characteristic data storage DB, 110... Growth guideline table, 112... Recommended products Decision table, 114... Recommended comment storage unit.

Claims (11)

Data indicating the child's developmental status, including multiple developmental specific movements such as crawling, rolling over, etc., which are useful for identifying the child's developmental progress, among physical movements that use the child's body. Developmental status data is stored, which includes operation availability data indicating whether each is possible or not, for each operation code assigned to each of the growth specific operations, and includes date of birth data indicating the child's date of birth. A means for storing developmental status data,
It is used as an index to grasp the characteristics related to the child's development, and indicates whether the child's development is normal, ahead, or delayed for each growth index code that is set to correspond to each of the behavior codes. characteristic data storage means in which characteristic data including a developmental progress code and having the date of birth data is stored;
Persona basic data storage means in which a plurality of persona basic data, which is image data representing the general child according to the age of the child, is stored;
Selecting the image data corresponding to the age of the child calculated using the date of birth data included in the characteristic data of the persona basic data stored in the persona basic data storage means, Pre-persona image generation means for generating a pre-persona image by changing the facial expression of the child indicated by the data according to the developmental progress code included in the characteristic data;
image presentation means for presenting the preliminary persona image generated by the preliminary persona image generation means;
and a recommended product presenting means for presenting childcare products that match the characteristic data stored in the characteristic data storage means as recommended products. The preliminary persona image generation means measures the number of delays, which is the number of data indicating that the child's development is delayed, among the developmental progress codes included in the characteristic data, and The childcare product recommendation device according to claim 1, wherein the childcare product recommendation device generates the preliminary persona image by changing the facial expression of the child depending on the number of childcare products. The characteristic data storage means further includes a tooth index data section in which the developmental progress code is stored as data indicating whether the child's dental development is normal, advanced, or delayed; 2. The child care system according to claim 1, wherein the index data section includes a start-of-eruption index field in which the developmental progress code is stored as data indicating whether the child's teeth start to erupt smoothly, ahead of time, or delayed. Supplies recommended equipment. It has individual areas corresponding to each of the growth index codes, a progress code area corresponding to the growth progress code is assigned to each of the individual areas, and a progress code area is presented to each of the progress code areas by the recommended product presentation means. Recommended product determination data storage means in which the recommended product, which is the recommended product and is suitable for each of the growth specific actions, is associated with recommendability data indicating whether it is recommendable or not recommended;
further comprising a recommended product determining means for determining the recommended product according to the recommendability data stored in the recommended product determining data storage means;
3. The childcare product recommendation device according to claim 2 , wherein the recommended product presenting means presents the recommended product determined by the recommended product determining means. progress determination processing means for determining whether the child's growth is normal, ahead, or delayed for each of the operation codes, using the operation availability data of the growth status data stored in the growth status data storage unit; and,
2. The child care product recommendation device according to claim 1, further comprising feature data generation means for generating the feature data so that data corresponding to the result determined by the progress determination processing means is included as the growth progress code. Growth in which a guideline data section storing data indicating a guideline for when the child's growth is normal is associated with a number-of-months-after-birth data section storing data indicating the number of months since the child's birth. further comprising a guideline data storage means,
The guideline data section has fields corresponding to each of the movement codes, each field is associated with the number of months after birth data section, and the possibility data indicating whether the physical movement is possible or not is included. Each field is set for each number of months after birth, and in each field, the minimum number of months that is the minimum value of the number of months after birth is less than the initial possible number of months corresponding to the time when the body movement becomes possible for the first time. Disapproval data indicating that the physical movement is not possible in the feasibility data is set by the number of months after birth, and the physical movement in the feasibility data is set in the number of months after birth that is equal to or greater than the initial possible number of months. 6. The childcare product recommendation device according to claim 5, wherein possibility data indicating that the childcare products are possible is set. The progress determination processing means calculates all the operation codes from the growth target data storage means using the date of birth data included in the growth status data stored in the growth status data storage means. The development of the child is determined by reading out the availability data set to the number of months after birth corresponding to the age of the child, and comparing the read availability data with the operation availability data included in the growth status data. 7. The childcare product recommendation device according to claim 6, which determines whether the childcare products are on track, ahead of schedule, or delayed. Recommended comment storage means in which a recommended comment regarding the appropriate recommended product stored in the recommended product determination data storage means is stored in association with the growth index code;
5. The childcare product recommendation device according to claim 4, further comprising post-persona image generation means for generating a post-persona image by changing the pre-persona image according to the recommendation comments stored in the recommendation comment storage means. 9. The apparatus further comprises a presentation control means for controlling the pre-persona image and the post-persona image to be presented side by side together with the recommended product when the recommended product is presented by the recommended product presentation means. Recommended equipment for childcare products. 9. The childcare product recommendation device according to claim 8, wherein the advance persona image generation means changes the facial expression of the child according to the number of improvements after the number of delayed items is corrected by a value set in the recommendation comment. A childcare product recommendation program for making a computer function as a childcare product recommendation device, which uses the computer to collect data indicating the developmental status of a child, including physical movements that use the child's body. Operation availability data indicating whether each of multiple developmental specific movements such as crawling, rolling over, etc., which is useful for identifying the progress of a child's development, is possible or not is provided for each movement code assigned to each of the developmental specific movements. and growth status data storage control means for storing growth status data in a growth status data storage means in which growth status data including date of birth data indicating the date of birth of the child is stored;
It is used as an index to grasp the characteristics related to the child's development, and indicates whether the child's development is normal, ahead, or delayed for each growth index code that is set to correspond to each of the behavior codes. Feature data storage control means for storing feature data in a feature data storage means in which feature data including a developmental progress code and having the date of birth data is stored;
The date of birth included in the characteristic data of the persona basic data stored in a persona basic data storage means in which a plurality of persona basic data, which is image data representing the general child according to the age of the child, is stored. The image data corresponding to the child's age calculated using the day data is selected, and the child's expression indicated by the image data is changed according to the developmental progress code included in the feature data to create a preliminary persona image. a pre-persona image generation means for generating;
image presentation means for presenting the preliminary persona image generated by the preliminary persona image generation means;
A childcare products recommendation program that functions as a recommended product presenting means for presenting childcare products that match the characteristic data stored in the characteristic data storage means as recommended products.

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