JP2012252420A - Information management device, information management program, and information management method - Google Patents

Abstract

PROBLEM TO BE SOLVED: To specify a conversation correspondent who is expected to appropriately find out the psychological condition of a target person from the person.SOLUTION: When receiving mood change information from a portable terminal 101-i operated by a target person, an information management device 100 refers to a conversation efficiency S between the target person and a care-receiver and selects a conversation correspondent who is to have conversation with the target person from among plural care-receivers. The conversation efficiency S is a value indicating how much amount of information of mood change conditions extracted from a target person in past conversations. The conversation efficiency S is a value produced by dividing an amount of characters N of text data of conversation contents transcribed from voice data by a reproducing period T of the voice data of the past conversation between the target person and an individual care-receiver. The information management device 100 transmits request information to the portable terminal of the conversation correspondent.

Description

  The present invention relates to an information management apparatus, an information management program, and an information management method for managing information.

  At sites that provide services such as nursing care, medical care, and childcare, grasp the psychological status of the target person by referring to the data recorded in the conversation between the target person and the conversation partner. As a result, the staff providing the service may facilitate the work. Examples of the target person include a cared person who is cared for at a care site, a medical person who is treated at a medical site (so-called patient), and a child-care worker who is raised at a child-care site (so-called childcare child). Can be mentioned. Examples of the conversation partner include a staff member and a target person.

  Therefore, when the subject requests a conversation, it is conceivable that one conversation partner is selected from a plurality of conversation partner candidates, and the selected conversation partner is conversed with the subject who desires the conversation. 2. Description of the Related Art Conventionally, a technique for selecting a staff to be dispatched to a target person based on a preset compatibility degree between the target person and the staff has been disclosed.

JP 2005-56188 A

  However, there is a problem that the psychological state of the subject cannot be sufficiently heard depending on the conversation ability of the selected conversation partner.

  The present invention eliminates the problems caused by the above-described prior art, so that an information management apparatus, an information management program, and an information management program that can identify a conversation partner who can be expected to sufficiently hear the psychological state of the subject from the subject, And an information management method.

  In order to solve the above-described problems and achieve the object, according to one aspect of the present invention, for each conversation partner who has a conversation with a target person, the text data of the conversation content and the conversation time are stored in association with each other, and the target Information on a conversation request from a person is obtained, and for each conversation partner, by dividing the conversation time associated with the text data from the amount of text data stored, the target person and the conversation partner An information management device, an information management program, and an information management method are proposed that output conversation efficiency for each conversation partner when the conversation efficiency is calculated and information related to the conversation request is acquired.

  Advantageous Effects of Invention According to one aspect of the present invention, there is an effect that it is possible to specify a conversation partner who is expected to sufficiently hear the subject's psychological situation from the subject.

FIG. 1 is an explanatory diagram of an example of the information management method according to the embodiment. FIG. 2 is an explanatory diagram of an example of the information management system according to the embodiment. FIG. 3 is a block diagram of a hardware configuration example of the computer according to the embodiment. FIG. 4 is an explanatory diagram showing an example of the contents stored in the face-to-face conversation information DB. FIG. 5 is an explanatory diagram showing an example of the contents stored in the mood change sheet DB. FIG. 6 is an explanatory diagram illustrating an example of the content stored in the fitness information DB. FIG. 7 is an explanatory diagram showing an example of the stored contents of the care receiver information DB. FIG. 8 is a block diagram illustrating an example of functions of the information management apparatus. FIG. 9 is a flowchart illustrating an example of a mobile terminal processing procedure of the mobile terminal according to the embodiment. FIG. 10A is a flowchart (part 1) illustrating an example of an information management processing procedure of the information management apparatus according to the embodiment. FIG. 10-2 is a flowchart (part 2) of the example of the information management processing procedure of the information management apparatus according to the embodiment. FIG. 10-3 is a flowchart (part 3) illustrating an example of an information management processing procedure of the information management apparatus according to the embodiment. FIG. 11 is a flowchart illustrating an example of a fitness calculation process procedure of the information management apparatus according to the embodiment. FIG. 12 is a flowchart illustrating an example of the fitness information DB update processing procedure of the information management apparatus according to the embodiment. FIG. 13 is a flowchart illustrating an example of a text input processing procedure of the staff terminal according to the embodiment.

  Exemplary embodiments of an information management device, an information management program, and an information management method according to the present invention will be explained below in detail with reference to the accompanying drawings.

<Embodiment>
In the embodiment, the target person is any one of the n (n> 1) cared persons, and in a past conversation between the cared person and the target person different from the target person. The conversation efficiency S indicating how much mood change information can be obtained per predetermined time from the subject is calculated. By selecting a conversation partner based on the calculated conversation efficiency S, a conversation partner who is expected to be able to sufficiently hear the psychological state of the target person from the target person can be conversed with the target person. Thereby, the data of the content of the substantial conversation between the target person and the conversation partner are created, and the staff can sufficiently grasp the psychological situation of the target person. Therefore, the staff can be provided with a smooth service in consideration of the psychological situation of the subject.

(An example of information management method)
FIG. 1 is an explanatory diagram of an example of the information management method according to the embodiment. In FIG. 1, among the mobile terminals 101-1 to 101-n owned by the care recipients P1 to Pn, a request to request a conversation with the target person from the mobile terminal of the conversation partner selected by the information management device 100. An information management method when information is transmitted will be described. In the following description, an arbitrary mobile terminal among the mobile terminals 101-1 to 101-n is referred to as “mobile terminal 101-i” (i = 1, 2,..., N). Further, in FIG. 1, description will be made assuming that n = 3.

  The information management apparatus 100 is a computer connected to the mobile terminals 101-1 to 101-3 and the staff terminal 102. The portable terminals 101-1 to 101-n are terminals operated by the care recipients P1 to Pn. The mobile terminals 101-1 to 101-n are, for example, mobile phones, PDAs (Personal Digital Assistants), and notebook PCs (Personal Computers). The staff terminal 102 is a computer operated by a staff caring for the care recipients P1 to Pn. Here, an example of information management in the case where the care receiver P1 is a target person will be described.

(1) The information management apparatus 100 receives mood change information including identification information of the subject from the mobile terminal 101-i operated by the subject. The mood change information includes information indicating that the subject requests a conversation. Here, for example, the information management apparatus 100 receives mood change information from the mobile terminal 101-1 of the care receiver P1.

(2) The information management apparatus 100 refers to the conversation efficiency S calculated for each care recipient and selects a conversation partner to be talked to the subject from a plurality of care recipients. Specifically, for example, the conversation efficiency S is determined by the information management apparatus 100 at the reproduction time T of the voice data of the past conversation between the target person and the cared person and the content of the conversation written from the voice data. This is a value obtained by dividing the character amount N of the text data. This text data is, for example, data in which information effective for nursing care is transcribed among the contents of the voice data by a staff member who has listened to the contents of the voice data. Information effective for nursing care is, for example, characteristic information of the subject such as information about the subject's personality and information about the situation when the subject's mood changes. The reproduction time T is the time from the start of audio data reproduction to the end. The character amount N is the number of characters in the text data. Hereinafter, the conversation efficiency S of the conversation partner with respect to the subject when the subject is the care recipient α and the conversation partner is the care recipient β will be referred to as “conversation efficiency Sαβ”.

  Here, a case where the cared person P1 is the target person and one of the cared persons P2 and P3 is selected as the conversation partner will be described. The voice data of the past conversation between the cared person P1 and the cared person P2 is voice data V1, and the voice data of the past conversation between the cared person P1 and the cared person P3 is voice data V2. Further, the reproduction time T of the audio data V1 is assumed to be reproduction time T1, the text data of the contents of the audio data V1 is assumed to be text data Y1, and the character amount N of the text data Y1 is assumed to be character amount N1. Further, the reproduction time T of the audio data V2 is set as the reproduction time T2, the text data of the content of the audio data V2 is set as the text data Y2, and the character amount N of the text data Y2 is set as the character amount N2.

In this case, the conversation efficiency S _P1P2 is a value obtained by dividing the reproduction amount T1 from the character amount N1 and is N1 / T1. The conversation efficiency S _P1P3 is a value obtained by dividing the reproduction amount T2 from the character amount N2 and is N2 / T2. For example, as shown in FIG. 1, when T1 <T2 and N1> N2, S _P1P2 > S _P1P3 . Here, the information management apparatus 100 selects the cared person P2 as the conversation partner, and in the past conversation, the cared person who was able to hear more information about the mood change situation from the target person per predetermined time. Can be selected.

(3) The information management apparatus 100 transmits request information to the mobile terminal 101-i of the conversation partner. The request information includes information indicating that the conversation partner is requested to have a conversation with the target person. For example, the information management apparatus 100 transmits the request information to the portable terminal 101-2 of the care receiver P2 selected as the conversation partner. When the portable terminal 101-2 displays the request information on the display, the cared person P2 who is the conversation partner visits the person of the cared person P1 who is the target person and has a conversation.

(4) The conversation partner mobile terminal 101-i records the conversation between the conversation partner and the target person. For example, the portable terminal 101-2 that has received the request information records a conversation between the care receiver P1 who is the subject and the care receiver P2 who is the conversation partner. That is, the voice data V3 of the conversation between the cared person P1 and the cared person P2 is created by the portable terminal 101-2.

(5) The mobile terminal 101-i of the conversation partner transmits the recorded voice data of the conversation between the conversation partner and the target person to the information management apparatus 100. For example, the portable terminal 101-2 transmits the created voice data V3 to the information management apparatus 100. The audio data V3 is stored in the information management apparatus 100.

(6) The staff terminal 102 creates text data of the contents of the voice data of the conversation between the recorded conversation partner and the target person in response to an input from the staff, and transmits the text data to the information management apparatus 100. At that time, for example, the staff terminal 102 acquires and reproduces the audio data V3. Then, the staff listens to the reproduced voice data V3, and creates text data Y3 by writing up information useful for care among the contents of the voice data V3. The created text data Y3 is stored in the information management apparatus 100.

(7) The staff terminal 102 acquires the text data Y3 from the information management apparatus 100, and displays the acquired text data Y3 on the display. With reference to the contents of the text data Y3 displayed on the display, the staff provides care for the care recipient P1.

  As described above, by selecting a conversation partner based on the conversation efficiency Sαβ, a conversation partner who can expect to efficiently hear the subject's psychological situation from the subject is selected. Then, from the content of the voice data of the conversation between the conversation partner and the target person, information effective for nursing care is extracted by the staff and text data is created. That is, it can be expected that the text data includes more information effective for care. Therefore, the staff can provide the subject with smooth care that grasps the psychological situation by providing the subject with care that refers to the text data. Each conversation efficiency Sαβ may be calculated at the timing (2), or may be calculated when each text data is stored in the information management apparatus 100.

(Example of information management system)
Next, an information management system according to an embodiment will be described.

  FIG. 2 is an explanatory diagram of an example of the information management system according to the embodiment. In the information management system 200 shown in FIG. 2, the information management apparatus 100, the mobile terminals 101-1 to 101-n, and the staff terminal 102 include the Internet, a LAN (Local Area Network), a WAN (Wide Area Network), and the like. The network 202 is connected.

  The information management apparatus 100 stores a face-to-face conversation information DB 210, a mood change sheet DB 220, a fitness information DB 230, and a care receiver information DB 240. In the face-to-face conversation information DB 210, information related to voice data is stored for each voice ID. The voice ID is identification information for identifying voice data. Details of the face-to-face conversation information DB 210 will be described later with reference to FIG. The mood change sheet DB 220 stores information such as text data in association with each voice ID. Details of the mood change sheet DB 220 will be described later with reference to FIG.

  The fitness information DB 230 stores values of the compatibility Lαβ and the normal conversation efficiency Cαβ for each subject and conversation partner. The degree of compatibility Lαβ is a value indicating how compatible the target person and the conversation partner are when the target person is the care receiver α and the conversation partner is the care receiver β. The normal conversation efficiency Cαβ is a value obtained by normalizing the conversation efficiency Sαβ. Details of the fitness information DB 230 will be described later with reference to FIG. In the care receiver information DB 240, information of a care receiver is stored for each care receiver ID. The care receiver ID is information for identifying a care receiver and is P1 to Pn. Details of the care receiver information DB 240 will be described later with reference to FIG.

  The portable terminal 101-i receives an input of mood change from the subject. At that time, the mobile terminal 101-i receives an input of any one of the plurality of types of mood changes from the subject. Examples of the mood change include “joy”, “anger”, “sorrow”, and “easy”. “Joy” is a type of mood change that expresses joy. “Anger” is a type of mood change that represents anger. “Sorrow” is a type of mood change that represents sadness. “Raku” is a type of mood change that expresses enjoyment. When receiving an input of mood change from the subject, the mobile terminal 101-i transmits mood change information including the type of mood change to the information management apparatus 100. Thereby, the processing described above with reference to FIG. 1 is performed.

(Example of computer hardware)
FIG. 3 is a block diagram of a hardware configuration example of the computer according to the embodiment. The computer may be any of the information management apparatus 100, the portable terminal 101-i, and the staff terminal 102. In FIG. 3, the computer includes a CPU (Central Processing Unit) 301, a ROM (Read-Only Memory) 302, a RAM (Random Access Memory) 303, a magnetic disk drive 304, a magnetic disk 305, an optical disk drive 306, and the like. And an optical disk 307 and an I / F (Interface) 308. Each unit is connected by a bus 300.

  Here, the CPU 301 governs overall control of the information management apparatus 100. The ROM 302 stores a program such as a boot program. The RAM 303 is used as a work area for the CPU 301. The magnetic disk drive 304 controls the reading / writing of the data with respect to the magnetic disk 305 according to control of CPU301. The magnetic disk 305 stores data written under the control of the magnetic disk drive 304.

  The optical disk drive 306 controls the reading / writing of the data with respect to the optical disk 307 according to control of CPU301. The optical disk 307 stores data written under the control of the optical disk drive 306, and causes the computer to read data stored on the optical disk 307.

  The I / F 308 is connected to the network 202 through a communication line, and is connected to another computer via the network 202. The I / F 308 controls an internal interface with the network 202 and controls data input / output from an external computer. For example, a modem or a LAN adapter can be adopted as the I / F 308.

  Next, the contents stored in the face-to-face conversation information DB 210 will be described. The face-to-face conversation information DB 210 is realized by a storage device such as the RAM 303, the magnetic disk 305, and the optical disk 307 of the information management apparatus 100, for example.

(Storage contents of face-to-face conversation information DB 210)
FIG. 4 is an explanatory diagram showing an example of the contents stored in the face-to-face conversation information DB 210. In FIG. 4, the face-to-face conversation information DB 210 has fields for a subject ID, conversation time, mood change type, voice data, voice ID, playback time T, conversation partner ID, conversation input history, and context record flag. By setting information in each field, the face-to-face conversation characteristic data 400-1 to 400-m are stored as records. In the following description, arbitrary face-to-face conversation characteristic data among the face-to-face conversation characteristic data 400-1 to 400-m is expressed as “face-to-face conversation characteristic data 400-j” (j = 1, 2,..., M). .

  Here, the type of mood change, voice data, voice ID, and playback time T are as described above. The target person ID is a care receiver ID of a cared person who is the target person, and is any one of P1 to Pn. The conversation time is the time when the subject person requested the conversation, and specifically, the request time when the portable terminal 101-i accepted the input of the conversation request from the subject person.

  The conversation partner ID is identification information of the cared person who is the conversation partner, and is any one of P1 to Pn. The input history during conversation is a history of the type of mood change that has occurred in the subject during the conversation with the conversation partner, and is input from the subject to the mobile terminal 101-i during recording of voice data, and is input to the information management apparatus 100. Sent. The context recording flag is a flag indicating whether or not text data of the content of audio data has been created. When the text data is not created, the context record flag is “not yet”, and when the text data is created, the context record flag is “completed”.

  As an example, when the face-to-face conversation characteristic data 400-1 is taken as an example, the subject ID “P1”, the conversation time “10:20”, the mood change type “joy”, the voice data “log1.wav”, the voice ID “ # 1 "is recorded. Also, the face-to-face conversation characteristic data 400-1 stores a reproduction time T “120 (seconds)”, a conversation partner ID “P4”, a conversation input history “joy, easy, easy”, and a context record flag “completed”. ing.

  Next, the contents stored in the mood change sheet DB 220 will be described. The mood change sheet DB 220 is realized by a storage device such as the RAM 303, the magnetic disk 305, and the optical disk 307 of the information management apparatus 100, for example.

(Contents stored in the mood change sheet DB 220)
FIG. 5 is an explanatory diagram showing an example of the contents stored in the mood change sheet DB 220. In FIG. 5, the mood change sheet DB 220 includes fields for a subject ID, a conversation time, a mood change type, text data, and a voice ID. By setting information in each field, mood change characteristic data 500-1 to 500-m are stored as records. In the following description, any mood change characteristic data among the mood change characteristic data 500-1 to 500-m is expressed as “mood change characteristic data 500-j”.

  Here, the subject person ID, conversation time, mood change type, text data, and voice ID are as described above. As an example, if the mood change characteristic data 500-1 is given as an example, the subject ID “P1”, the conversation time “10:20”, the mood change type “joy”, the text data “you can sing your favorite song today. , Very comfortable ... "and voice ID" # 1 "are recorded.

  Next, the contents stored in the fitness information DB 230 will be described. The fitness information DB 230 is realized by a storage device such as the RAM 303, the magnetic disk 305, and the optical disk 307 of the information management apparatus 100, for example.

(Contents stored in the fitness information DB 230)
FIG. 6 is an explanatory diagram showing an example of the contents stored in the fitness level information DB 230. In FIG. 6, the fitness level information DB 230 has fields of compatibility Lαβ and normal conversation efficiency Cαβ with each conversation partner for each subject ID. By setting information in each field, the fitness characteristic data 600-1 to 600-n are stored as records.

As an example, taking the fitness characteristic data 600-1 as an example, L ₁₂ = 0.5, C ₁₂ = 0.7, L ₁₃ = 0.8, C ₁₃ = 0.2,... L _1n = 0.2 and C _1n = 0.3 are recorded.

  Next, the stored contents of the care receiver information DB 240 will be described. The care receiver information DB 240 is realized by a storage device such as the ROM 302, the RAM 303, the magnetic disk 305, and the optical disk 307 of the information management apparatus 100, for example.

(Memory contents of care receiver information DB 240)
FIG. 7 is an explanatory diagram showing an example of the contents stored in the care receiver information DB 240. In FIG. 7, the care receiver information DB 240 includes fields of a care receiver ID, a mail address, a name, and a room number. By setting information in each field, terminal characteristic data 700-1 to 700-n are stored as records.

  The e-mail address is destination information necessary for transmitting information to the portable terminal 101-i owned by the care recipient. The full name is the surname of the care recipient. The room number is information for identifying the room of the care facility where the care recipient is in.

  As an example, taking the terminal characteristic data 700-1 as an example, the care receiver ID “P1”, the email address “XXX @ XXX”, the name “Tokyo Taro”, and the room number “202” are recorded. Has been.

(Example of functions of information management apparatus 100)
Next, an example of functions of the information management apparatus 100 will be described. FIG. 8 is a block diagram illustrating an example of functions of the information management apparatus 100. The information management apparatus 100 includes a storage unit 801, an acquisition unit 802, a specification unit 803, a conversation efficiency calculation unit 804, a fitness calculation unit 805, a selection unit 806, and an output unit 807. Specifically, the functions (storage unit 801 to output unit 807) serving as the control unit are, for example, a program stored in a storage device such as the ROM 302, RAM 303, magnetic disk 305, and optical disk 307 shown in FIG. The function is realized by executing the function or by the I / F 308.

  The storage unit 801 stores the text data of the conversation contents and the conversation time in association with each conversation partner who has a conversation with the target person. The target person is the person who requested the conversation among the cared persons as described above, but is not limited to the cared person, and may be a person such as a medical person or a childcare person. The conversation partner is a person who has a conversation with the target person among the cared persons as described above, but is not limited to the cared person, and may be a person such as a medical person or a childcare person, Moreover, the staff who provides a service may be sufficient.

  The conversation time is the time from the start to the end of the conversation. For example, the conversation time is the above-described reproduction time T or the time manually measured from the start to the end of the conversation. The storage unit 801 stores text data of conversation contents and conversation time in association with each conversation partner ID. Specifically, for example, the storage unit 801 stores the text data and the reproduction time T in association with each conversation partner ID by using the face-to-face conversation information DB 210 and the mood change sheet DB 220 associated with the voice ID. .

  In addition, the storage unit 801 further stores, for each conversation partner, information indicating the type of the subject's mood during the conversation with the conversation partner in association with each other. The information that indicates the subject's mood during the conversation with the conversation partner is whether the subject's mood changed during the conversation, or what kind of mood the subject's mood changed during the conversation. It is information indicating whether or not it has changed. The information indicating the type of the subject's mood during the conversation with the conversation partner is, for example, an input history during conversation in the face-to-face conversation information DB 210. Specifically, for example, the storage unit 801 stores the text data, the reproduction time T, and the input history during conversation in association with each other by the face-to-face conversation information DB 210 and the mood change sheet DB 220.

  Further, the storage unit 801 further stores a conversation time in association with each conversation partner. Specifically, for example, the storage unit 801 stores the text data, the reproduction time T, the input history during conversation, and the conversation time in association with each other by the face-to-face conversation information DB 210 and the mood change sheet DB 220. Yes.

  In addition, the storage unit 801 further stores information indicating the type of mood of the subject person before the conversation with the conversation partner for each conversation partner. The information indicating the mood type of the subject before the conversation with the conversation partner is information selected from the plurality of mood types by the subject before the conversation. For example, the mood change of the face-to-face conversation information DB 210 described above. It is a kind. Specifically, for example, the storage unit 801 stores the text data, the reproduction time T, and the type of mood change in association with each other with the face-to-face conversation information DB 210 and the mood change sheet DB 220 for each conversation partner ID.

  The acquisition unit 802 acquires information related to a conversation request from the target person. The information related to the conversation request is information indicating that the subject requests a conversation, and is, for example, the mood change information described above. Specifically, for example, the acquisition unit 802 acquires information related to the conversation request by receiving mood change information from the mobile terminal 101-i operated by the subject. The information related to the conversation request may include information indicating the type of mood of the target person at the time of the conversation request. The information indicating the mood of the subject at the time of the conversation request is information indicating what the subject is feeling, for example, the type of mood change described above. Further, the information related to the conversation request from the subject may include the request time when the subject requested the conversation.

  The identifying unit 803 identifies a conversation partner who has a conversation during the same time period from a plurality of conversation partners based on the conversation time and the acquisition time of information related to the conversation request. The acquisition time is the time when the information related to the conversation request is acquired by the acquisition unit 802, and may be the above-described request time. When the information related to the conversation request is acquired by the acquisition unit 802, the information management apparatus 100 It may be the measured time.

  A conversation partner who has a conversation in the same time zone is a conversation partner whose conversation time stored in the storage unit 801 is in the same time zone as the acquisition time acquired by the acquisition unit 802. The time zone is a predetermined time width, for example, 30 minutes or 1 hour. To identify the conversation partner is specifically to identify the conversation partner ID.

  Specifically, for example, for each face-to-face conversation characteristic data 400-j in the face-to-face conversation information DB 210, the specifying unit 803 determines the difference between the request time included in the mood change information and the conversation time of the face-to-face conversation characteristic data 400-j. Is determined within 30 minutes. Then, the identification unit 803 identifies the conversation partner ID of the face-to-face conversation characteristic data 400-j including the conversation time determined that the difference from the request time included in the mood change information is within 30 minutes. Identify the conversation partner with whom you have a conversation during the time.

  The identifying unit 803 also includes information indicating the type of the subject's mood at the time of the conversation request included in the information related to the conversation request from the plurality of conversation partners and the mood of the subject before the conversation with the conversation partner. Identify the conversation partner whose type information matches.

  Specifically, for example, first, the identifying unit 803 includes, for each face-to-face conversation characteristic data 400-j in the face-to-face conversation information DB 210, the type of mood change included in the mood change information and the face-to-face conversation characteristic data 400-j. It is determined whether the types of mood changes to be made are the same. Then, the identifying unit 803 determines the type of mood change included in the mood change information and the conversation partner of the face-to-face conversation characteristic data 400-j determined to be the same as the type of mood change included in the face-to-face conversation characteristic data 400-j. Specify the ID.

  The conversation efficiency calculation unit 804 divides, for each conversation partner, the conversation time associated with the text data from the character amount N of the text data stored in the storage unit 801, so that the conversation between the target person and the conversation partner is performed. The efficiency Sαβ is calculated.

  Specifically, for example, the conversation efficiency calculation unit 804 first measures the character amount N of the text data, and obtains the face-to-face conversation characteristic data 400-j associated with the text data by the voice ID from the face-to-face conversation information DB 210. Search for. Then, the conversation efficiency calculation unit 804 specifies the reproduction time T included in the searched face-to-face conversation characteristic data 400-j, and calculates the conversation efficiency Sαβ by dividing the specified reproduction time T from the measured character amount N. To do. For example, when the reproduction time T is 120 seconds and the character amount N is 150 characters, the conversation efficiency Sαβ is calculated as conversation efficiency Sαβ = 150/120 = 1.25.

  Note that the conversation efficiency calculation unit 804 may calculate the conversation efficiency Sαβ when the text data is registered or when the acquisition unit 802 acquires information related to the conversation request from the target person. May be.

  The suitability calculation unit 805 is adapted to a conversation with the target person based on the conversation efficiency Sαβ for each conversation partner and the information indicating the type of mood of the target person during the conversation for each conversation partner. Is calculated for each conversation partner. The fitness M is a value indicating that the higher the fitness is for the subject, the lower the fitness M is, the lower the fitness for the subject. Hereinafter, when the target person is the cared person α and the conversation partner is the cared person β, the degree of fitness M of the conversation partner with respect to the target person is referred to as “fit degree Mαβ”. For example, the fitness level calculation unit 805 calculates the fitness level Mαβ based on the normal conversation efficiency Cαβ obtained by normalizing the conversation efficiency Sαβ and the compatibility level Lαβ based on information indicating the type of mood of the target person for each conversation partner. To do.

  The normal conversation efficiency Cαβ is a standard character amount Ns which is a character amount of standard text data, a standard reproduction time Ts which is a reproduction time of standard voice data, and a standard normal conversation efficiency which is a standard normal conversation efficiency. Calculated using Cs. Here, the standard character amount Ns, the standard reproduction time Ts, and the standard normal conversation efficiency Cs are predetermined values.

  Specifically, for example, the normal conversation efficiency Cαβ is calculated as follows: normal conversation efficiency Cαβ = conversation efficiency Sαβ × standard reproduction time Ts / standard character amount Ns × standard normal conversation efficiency Cs. For example, when the conversation efficiency Sαβ = 1.25, the standard reproduction time Ts = 60 seconds, the standard character amount Ns = 50 characters, and the standard normal conversation efficiency Cs = 0.5, the normal conversation efficiency Cαβ is the normal conversation efficiency Cαβ = It is calculated as 1.25 × 60/50 × 0.5 = 0.75. When the calculated normal conversation efficiency Cαβ is greater than “1”, the normal conversation efficiency Cαβ is corrected to normal conversation efficiency Cαβ = 1.0. The calculated normal conversation efficiency Cαβ is stored in the care receiver information DB 240 in association with the target person ID and the conversation partner ID.

  The degree of compatibility Lαβ is calculated based on the degree of compatibility Lαβ before update, the specified value QL, the mood change amount ΔF, and the maximum mood change amount Rmax. Here, the prescribed value QL is a predetermined value. The mood change amount ΔF is a value obtained by quantifying how much the subject's mood has changed during the conversation, and is calculated based on information indicating the type of the subject's mood during the conversation. The larger the value of the mood change amount ΔF is, the larger the value is to indicate that the subject feels better during the conversation. The smaller the value of the mood change amount ΔF, the worse the subject feels during the conversation. It is a value indicating that

  Specifically, for example, the mood change amount ΔF is calculated by adding mood change points determined in advance for each type of mood of the subject during the conversation. For example, the mood change amount ΔF is “+1” for “joy”, −2 points for “anger”, −1 point for “sorrow”, and “+2” for “easy” in the conversation history input history of the face-to-face conversation characteristic data 400-j. It is calculated by adding the points as points. Here, when the input history during conversation is “joy, comfort, comfort”, the mood change amount ΔF is calculated as the mood change amount ΔF = + 1 + 2 + 2 = + 5.

  The maximum mood change amount Rmax is a maximum value that the mood change amount ΔF can take, for example, the maximum number of points assigned to the type of mood change in the number of types of mood change stored as the input history during conversation. The value multiplied by the value. For example, when three types of mood change are stored as the input history during conversation, and the maximum value of the points assigned to the type of mood change is +2 points, the maximum mood change amount Rmax is Rmax = 3. X (+2) = + 6 is calculated.

  Specifically, the degree of compatibility Lαβ is calculated as, for example, the degree of compatibility Lαβ = the degree of compatibility Lαβ before update + the specified value QL × the mood change amount ΔF / the maximum mood change amount Rmax. For example, when the compatibility level Lαβ before update is 0.8, the specified value QL = 0.2, the mood change amount ΔF = + 5, and the maximum mood change amount Rmax = + 6, the new compatibility level Lαβ is the compatibility level Lαβ = It is calculated as 0.8 + 0.2 × (+ 5 / + 6) = 0.97.

  The goodness-of-fit calculation unit 805, for example, based on the normal conversation efficiency Cαβ, the compatibility Lαβ, the conversation efficiency coefficient WC, and the compatibility coefficient WL, the fitness Mαβ = conversation efficiency coefficient WC × normal conversation efficiency Cαβ + compatibility The fitness Mαβ is calculated as coefficient WL × compatibility Lαβ. The conversation efficiency coefficient WC is a coefficient relating to the normal conversation efficiency Cαβ, and the compatibility degree coefficient WL is a coefficient relating to the affinity degree Lαβ. For example, when the normal conversation efficiency Cαβ = 0.75, the compatibility Lαβ = 0.97, the conversation efficiency coefficient WC = 0.1, and the compatibility coefficient WL = 0.9, the fitness calculation unit 805 determines the fitness Mαβ. = 0.1 * 0.75 + 0.9 * 0.97 = 0.948.

  In addition, the fitness level calculation unit 805 may calculate the fitness level Mαβ for each conversation partner by weighting the conversation efficiency Sαβ more as the character amount N of the text data is smaller. The calculation of the fitness Mαβ by weighting the conversation efficiency Sαβ with a large weight means that the ratio of the conversation efficiency Sαβ to the information indicating the type of mood of the target person during the conversation for each conversation partner is increased. It is to be. Specifically, for example, the fitness calculation unit 805 changes the weighting by changing the compatibility coefficient WL and the conversation efficiency coefficient WC according to the character amount N of the text data.

  For example, the suitability calculation unit 805 calculates the compatibility coefficient WL = character amount N / (prescribed character amount Nt × 2) using the character amount N and a predetermined character amount Nt, and the conversation efficiency. The coefficient WC is calculated as 1−the compatibility coefficient WL. For example, when the character amount N = 360 and the prescribed character amount Nt = 200, the fitness calculation unit 805 calculates the compatibility coefficient WL = 360 / (200 × 2) = 0.9. At that time, the fitness level calculation unit 805 calculates the conversation efficiency coefficient WC = 1−0.9 = 0.1. Thereby, the smaller the value of the character amount N, the smaller the value of the compatibility coefficient WL and the larger the value of the conversation efficiency coefficient WC. Accordingly, the weighting of the normal conversation efficiency Cαβ is increased. That is, the smaller the character amount N, the greater the weighting of the conversation efficiency Sαβ. When the calculated compatibility coefficient WL is larger than “1”, the fitness calculation unit 805 corrects the compatibility coefficient WL = 1.0.

  In addition, the fitness level calculation unit 805 is adapted to the degree to which the conversation with the target person is based on the conversation efficiency S for each specific conversation partner and the information indicating the type of mood of the target person for each specific conversation partner. The degree of fitness Mαβ indicating whether or not the user is doing may be calculated for each specific conversation partner. The specific conversation partner is a conversation partner identified by the identifying unit 803. For example, the fitness level calculation unit 805 may calculate only the fitness level Mαβ of the conversation partner specified by the specification unit 803.

  Further, the fitness level calculation unit 805 may calculate the fitness level Mαβ for each specific conversation partner by weighting the conversation efficiency S as the character amount N of the text data is smaller. For example, the goodness-of-fit calculation unit 805 calculates the goodness-of-fit Mαβ by using the conversation efficiency coefficient WC and the compatibility coefficient WL based on the character amount N of text data only for the goodness of match Mαβ of the conversation partner specified by the specifying unit 803. It is good to do.

  When information about a conversation request is acquired, the selection unit 806 selects a conversation partner to be talked to the target person from a plurality of conversation partners based on the conversation efficiency Sαβ for each conversation partner. The conversation partner to be talked to the target person from among a plurality of conversation partners is identification information of the conversation partner most suitable for the conversation with the target person.

  For example, when information related to a conversation request is acquired, the selection unit 806 selects a conversation partner to be talked to the target person from a plurality of conversation partners based on the matching degree Mαβ for each conversation partner. Specifically, for example, the selection unit 806 compares the respective fitness levels Mαβ calculated by the fitness level calculation unit 805, and specifies the conversation partner ID associated with the highest fitness level Mαβ, so that the target person Select a conversation partner to talk to.

  Note that the selection unit 806 compares any of conversation efficiency Sαβ, normal conversation efficiency Cαβ, and fitness Mαβ as long as it selects a conversation partner to be talked to the target person based on the conversation efficiency Sαβ for each conversation partner. Accordingly, a conversation partner to be talked with the target person may be selected. For example, the selection unit 806 may select a conversation partner having the highest conversation efficiency Sαβ as a conversation partner to be talked to the target person, or cause a conversation partner having the highest regular conversation efficiency Cαβ to talk to the target person. It is good also as selecting as a conversation partner who should be.

  In addition, the selection unit 806 selects a conversation partner to be conversed with the target person from a plurality of conversation partners based on the conversation efficiency Sαβ for each specific conversation partner when information about the conversation request is acquired. It is good. In addition, the selection unit 806 selects a conversation partner to be talked to the target person from a plurality of conversation partners based on the fitness Mαβ for each specific conversation partner when information about the conversation request is acquired. It is good.

  When the acquisition unit 802 acquires information related to the conversation request, the output unit 807 outputs the conversation efficiency Sαβ for each conversation partner calculated by the conversation efficiency calculation unit 804. Here, the output of the conversation efficiency Sαβ is selected based on the normal conversation efficiency Cαβ and the fitness Mαβ calculated based on the conversation efficiency Sαβ, or the conversation efficiency Sαβ, the normal conversation efficiency Cαβ, and the fitness Mαβ. Including outputting information about the conversation partner who has been sent.

  Specifically, for example, the output unit 807 may output data listing the conversation efficiency Sαβ, the normal conversation efficiency Cαβ, and the matching degree Mαβ for each conversation partner. For example, data listing the conversation efficiency Sαβ for each conversation partner may be transmitted to the staff terminal 102. Thereby, the information management apparatus 100 can make the staff select a conversation partner to be talked to the target person based on the conversation efficiency Sαβ for each conversation partner.

  Further, for example, data that lists the fitness Mαβ for each conversation partner may be output to the staff terminal 102. As a result, the information management apparatus 100 can cause the staff to select a conversation partner to be talked to the target person based on the fitness Mαβ of each conversation partner.

  Further, the output unit 807 may output the conversation efficiency Sαβ or the matching degree Mαβ for each specific conversation partner specified by the specification unit 803. Thereby, the staff is made to select a conversation partner to be talked to the target person from the conversation target person who had a conversation in the same time zone as the requested time based on the conversation efficiency Sαβ or the matching degree Mαβ for each conversation partner. be able to.

  The output unit 807 may output the selection result selected by the selection unit 806. For example, the output unit 807 may transmit a conversation partner ID that is a selection result to the staff terminal 102. Thereby, the staff can be made to recognize the conversation partner who should have a conversation with the target person, and can ask the conversation partner to have a conversation with the target person.

  Further, the output unit 807 may transmit the selection result to a conversation partner who should have a conversation with the target person. Specifically, the transmission to the conversation partner is, for example, transmission to a terminal device owned by the conversation partner who should have a conversation with the target person. The terminal device may be a computer that can receive information transmitted from the output unit 807, and may be the above-described portable terminal 101-i or a fixed terminal device such as a PC.

  For example, the output unit 807 first uses the conversation partner ID selected by the selection unit 806 to obtain the e-mail address that is the destination information of the mobile terminal 101-i owned by the conversation partner who should have a conversation with the target person. Based on ID, it extracts from care receiver information DB240. Then, the output unit 807 may transmit the above-described request information to the extracted mail address. Thereby, it is possible to automatically have a conversation with the subject with respect to a conversation partner who should have a conversation with the subject. Here, the output unit 807 transmits information to the mobile terminal 101-i using a mail address, but is not limited thereto. For example, the output unit 807 may transmit information to the mobile terminal 101-i using an IP (Internet Protocol) address.

(Mobile terminal processing procedure of the mobile terminal 101-i)
FIG. 9 is a flowchart illustrating an example of a mobile terminal processing procedure of the mobile terminal 101-i according to the embodiment. The mobile terminal process is a process executed by the CPU 301 of the mobile terminal 101-i. In the mobile terminal process, the mobile terminal 101-i first determines whether or not an input of mood change has been received (step S901).

  When the input of mood change is received (step S901: Yes), the portable terminal 101-i transmits mood change information to the information management apparatus 100 (step S902). As described above, the mood change information includes the target person ID, the request time, and the mood change type “joy”, “anger”, “sorrow”, or “easy” information. .

  After step S902, the mobile terminal 101-i determines whether conversation start timing information has been received from the information management apparatus 100 (step S903). As for the conversation start timing information, recording of conversation between a conversation partner who operates another portable terminal and a target person who operates the portable terminal 101-i is started on another portable terminal different from the portable terminal 101-i. This is information indicating the effect. When conversation start timing information is not received from the information management apparatus 100 (step S903: No), the mobile terminal 101-i waits until it is received.

  When the conversation start timing information is received from the information management apparatus 100 (step S903: Yes), the mobile terminal 101-i determines whether or not an input of mood change has been received (step S904). When the input of the mood change is received (step S904: Yes), the mobile terminal 101-i stores the input type of mood change as history information (step S905).

  After step S905, the portable terminal 101-i determines whether or not a conversation end notification has been received from the information management apparatus 100 (step S906). If not received (step S906: No), step S904 is performed. Migrate to The conversation end notification indicates that the recording of the conversation between the conversation partner who operates the other mobile terminal and the target person who operates the mobile terminal 101-i is ended on another mobile terminal different from the mobile terminal 101-i. It is information which shows. In step S904, when the input of mood change is not received (step S904: No), portable terminal 101-i transfers to step S906.

  In step S906, when the conversation end notification is received from the information management apparatus 100 (step S906: Yes), the mobile terminal 101-i transmits the history information stored in step S905 to the information management apparatus 100 (step S907). Then, after step S907, the mobile terminal 101-i ends the series of processes in this flowchart. The history information transmitted in step S907 is received by the information management apparatus 100 and registered as an in-conversation input history in the face-to-face conversation information DB 210. By performing Steps S901 to S907, the mobile terminal 101-i functions as the mobile terminal of the subject person.

  In step S901, when the input of mood change is not received (step S901: No), the portable terminal 101-i determines whether the request information is received from the information management apparatus 100 (step S908). If the request information has not been received (step S908: No), the mobile terminal 101-i proceeds to step S901.

  When request information is received in step S908 (step S908: Yes), the mobile terminal 101-i displays the request content included in the received request information on the display of the mobile terminal 101-i (step S909). Here, it is assumed that the name and room number of the target person are included as the target person information included in the request information. For example, the portable terminal 101-i displays character information such as “Talk to Mr. Taro Tokyo (room number: 202) to hear and record the situation when the mood changes”.

  After step S909, the portable terminal 101-i determines whether or not an input for starting a conversation with the subject has been accepted (step S910). If not accepted (step S910: No), the portable terminal 101-i stands by until accepted. When the input of the start of the conversation is received (step S910: Yes), the mobile terminal 101-i transmits to the information management apparatus 100 conversation start information indicating that recording of the conversation between the target person and the conversation partner is started. Transmit (step S911).

  After step S911, the portable terminal 101-i starts recording a conversation between the target person and the conversation partner (step S912), and determines whether or not an input for ending the conversation has been received (step S913). When the input of the conversation end is not accepted (step S913: No), the portable terminal 101-i waits until it is accepted. When the input of the conversation end is accepted (step S913: Yes), the mobile terminal 101-i transmits the conversation completion information to the information management apparatus 100 (step S914), and the series of processes in this flowchart is terminated. The conversation completion information includes recorded voice data and a conversation partner ID. By performing Steps S908 to S914, the mobile terminal 101-i functions as a mobile terminal of the conversation partner.

  By executing Steps S904 to S907 of the above-described mobile terminal processing, the mobile terminal 101-i transmits the history information of the mood change of the subject during the conversation between the subject and the conversation partner to the information management apparatus 100. can do. Further, by executing steps S908 to S914 of the above-described portable terminal processing, the portable terminal 101-i can create voice data of conversation between the target person and the conversation partner and transmit it to the information management apparatus 100. it can.

(Information management processing procedure of the information management apparatus 100)
10A to 10C are flowcharts illustrating an example of an information management processing procedure of the information management apparatus 100 according to the embodiment. The information management process is a process executed by the CPU 301 of the information management apparatus 100. In the information management process, the information management apparatus 100 first determines whether or not mood change information has been received from the mobile terminal 101-i (step S1001). The mood change information is information transmitted from the portable terminal 101-i in step S902 of FIG.

  When the mood change information is received (step S1001: Yes), the information management apparatus 100 registers information included in the mood change information in the face-to-face conversation information DB 210 and the mood change sheet DB 220 (step S1002). At that time, the information management apparatus 100 creates new face-to-face conversation characteristic data, registers the request time included in the mood change information as the conversation time, and registers the type of mood change and the subject ID. In addition, the information management apparatus 100 creates new mood change data, registers the request time included in the mood change information as the conversation time, and registers the type of mood change and the subject ID.

  After step S1002, the information management apparatus 100 executes a fitness calculation process (step S1003). The fitness level calculation process is a process of calculating the fitness level Mαβ using the fitness level information DB 230, and details thereof will be described later with reference to FIG. After step S1003, the information management apparatus 100 selects the care recipient having the highest fitness Mαβ calculated in step S1003 as the conversation partner (step S1004).

  Then, the information management apparatus 100 transmits the request information to the care receiver's portable terminal 101-i selected as the conversation partner (step S1005). In step S <b> 1005, the information management apparatus 100 specifies a mail address corresponding to the determined care receiver ID of the conversation partner from the care receiver information DB 240, and transmits request information with the specified mail address as a destination.

  After step S1005, the information management apparatus 100 determines whether or not conversation start information has been received from the mobile terminal 101-i of the cared person selected as the conversation partner (step S1006), and if not received (step S1006: No), wait until receiving. The conversation start information is information transmitted from the portable terminal 101-i in step S911 in FIG.

  When the conversation start information is received from the mobile terminal 101-i of the cared person selected as the conversation partner (step S1006: Yes), the information management apparatus 100 uses the mobile terminal of the cared person who is the target person for the conversation start timing information. 101-i is transmitted (step S1007). The conversation start timing information is information received by the mobile terminal 101-i in step S903 in FIG. In step S <b> 1007, the information management apparatus 100 identifies an email address corresponding to the care receiver ID of the care recipient who is the subject from the care receiver information DB 240, and sets the conversation start timing information with the identified email address as the destination. Send.

  After step S1007, the information management apparatus 100 determines whether or not conversation completion information has been received from the mobile terminal 101-i of the cared person selected as the conversation partner (step S1008), and if not received (step S1008: No), wait until receiving. The conversation completion information is information transmitted from the portable terminal 101-i in step S914 in FIG.

  In step S1008, when the conversation completion information is received (step S1008: Yes), the information management apparatus 100 transmits a conversation end notification to the mobile terminal 101-i of the care receiver who is the subject (step S1009). The conversation end notification is information received by the mobile terminal 101-i in step S906 in FIG. In step S <b> 1009, the information management apparatus 100 identifies an email address corresponding to the care receiver ID of the care recipient who is the subject from the care receiver information DB 240, and sends a conversation end notification with the identified email address as the destination. To do.

  After step S1009, the information management apparatus 100 registers the voice data and the conversation partner ID included in the conversation completion information received in step S1008, the reproduction time T of the voice data, and the voice ID in the face-to-face conversation information DB 210. (Step S1010). At this time, the registered face-to-face conversation characteristic data 400-j is the face-to-face conversation characteristic data in which information is registered in step S1002. The reproduction time T is measured and registered by the information management apparatus 100 from the audio data included in the conversation completion information. The voice ID is generated and registered by the information management apparatus 100.

  Then, the information management apparatus 100 registers the voice ID registered in the face-to-face conversation information DB 210 in step S1010 in the mood change sheet DB 220 (step S1011). At this time, the mood change characteristic data 500-j to be registered is the face-to-face conversation characteristic data in which information is registered in step S1002. Thereafter, the information management apparatus 100 determines whether or not history information has been received from the mobile terminal 101-i of the care recipient who is the subject (step S1012), and if not received (step S1012: No), receives the history information. Wait until. The history information is information transmitted from the portable terminal 101-i in step S907 in FIG.

  In step S1012, when history information is received (step S1012: Yes), the information management apparatus 100 registers the received history information in the face-to-face conversation information DB 210 as an input history during conversation (step S1013). The process ends.

  If the mood change information is not received in step S1001 (step S1001: No), the information management apparatus 100 determines whether list request information is received from the staff terminal 102 (step S1014). The list request information is information for requesting a list of audio data for which text data has not been created. When the list request information is not received (step S1014: No), the information management apparatus 100 proceeds to step S1001.

  When the list request information is received from the staff terminal 102 (step S1014: Yes), the information management apparatus 100 specifies the face-to-face conversation characteristic data 400-j whose context record flag is “not yet” from the face-to-face conversation information DB 210 ( Step S1015). Then, the information management apparatus 100 transmits list information in which the specified face-to-face conversation characteristic data 400-j is listed to the staff terminal 102 (step S1016). The staff terminal 102 that has received the list information displays the list information on the display, and allows the user to select which face-to-face conversation characteristic data 400-j to input the text data.

  After step S1016, the information management apparatus 100 determines whether or not a selection result indicating whether to input text data for which face-to-face conversation characteristic data 400-j is received from the staff terminal 102 (step S1017). If not received (step S1017: No), the information management apparatus 100 stands by until it is received. When the information is received (step S1017: Yes), the information management apparatus 100 transmits the voice data of the face-to-face conversation characteristic data 400-j corresponding to the selection result to the staff terminal 102 (step S1018).

  Thereafter, the information management apparatus 100 determines whether or not text data has been received from the staff terminal 102 (step S1019). If not received (step S1019: No), the information management apparatus 100 waits until it is received. When the text data is received from the staff terminal 102 (step S1019: Yes), the received text data is registered in the mood change sheet DB 220 (step S1020). At this time, the received text data is registered in the mood change characteristic data 500-j corresponding to the received selection result. The text data received here is data in which the content of the voice data transmitted to the staff terminal 102 is input by the staff.

  Thereafter, the information management apparatus 100 executes a fitness information DB update process for updating the fitness information DB 230 (step S1021), and ends the series of processes in this flowchart. Details of the fitness information DB update processing will be described later with reference to FIG.

  By executing the information management process described above, the information management apparatus 100 can select the care receiver associated with the highest fitness Mαβ as the conversation partner when the subject's mood changes. . Thereby, the conversation partner and the target person who can expect the conversation with the highest time efficiency can be made to talk. Further, the information management apparatus 100 can register voice data of conversation between the selected conversation partner and the target person. Further, the information management apparatus 100 can register text data of the contents of the registered voice data.

(Fitness calculation processing procedure of information management apparatus 100)
FIG. 11 is a flowchart illustrating an example of a fitness calculation process procedure of the information management apparatus 100 according to the embodiment. The fitness calculation process is the process shown in step S1003 of FIG. 10A and is executed by the CPU 301 of the information management apparatus 100. In the fitness level calculation process, the information management apparatus 100 first sets j to “0” (step S1101). Then, a value obtained by adding “1” to j is set as a new j (step S1102).

  Then, the information management apparatus 100 specifies mood change characteristic data 500-j from the mood change sheet DB 220 (step S1103). Then, the information management apparatus 100 determines whether or not the target person ID in the identified mood change characteristic data 500-j is the same as the target person ID included in the mood change information received in step S1001 of FIG. Is determined (step S1104).

  In step S1104, when the target person ID in the specified mood change characteristic data 500-j is the same as the target person ID included in the mood change information (step S1104: Yes), the information management apparatus 100 performs step S1105. Execute. In step S1105, the information management apparatus 100 determines whether or not the type of mood change in the identified mood change characteristic data 500-j is the same as the type of mood change included in the received mood change information ( Step S1105).

  In step S1105, when the type of mood change in the identified mood change characteristic data 500-j is the same as the type of mood change included in the received mood change information (step S1105: Yes), the information management apparatus 100 Step S1106 is executed. In step S1106, the information management apparatus 100 determines whether or not the conversation time in the identified mood change characteristic data 500-j and the request time included in the received mood change information are in the same time zone (step S1106). S1106). Here, if the difference between the conversation time in the specified mood change characteristic data 500-j and the request time included in the received mood change information is within 30 minutes, it is determined that they are in the same time zone.

  When it is determined in step S1106 that the conversation time in the identified mood change characteristic data 500-j and the conversation time included in the mood change information are in the same time zone (step S1106: Yes), the information management apparatus 100 The process proceeds to step S1107. In step S1107, the information management apparatus 100 measures the character amount N of text data in the mood change characteristic data 500-j (step S1107).

  After step S1108, the information management apparatus 100 sets a weighting factor including the compatibility factor WL and the conversation efficiency factor WC (step S1108). As described above with reference to FIG. 8, the respective weighting coefficients are calculated as compatibility coefficient WL = character amount N / (2 × specified character amount Nt), conversation efficiency coefficient WC = 1−compatibility coefficient WL.

  Thereafter, the information management apparatus 100 calculates the fitness Mαβ (step S1109). At this time, the fitness Mαβ is calculated as the fitness Mαβ = compatibility coefficient WL × compatibility Lαβ + conversation efficiency coefficient WC × normal conversation efficiency Cαβ, as described above with reference to FIG.

  After step S1109, the information management apparatus 100 stores the calculated fitness Mαβ (step S1110), and determines whether j and m are the same value (step S1111). In step S1110, the fitness Mαβ is stored in a storage device such as the RAM 303, the magnetic disk 305, or the optical disk 307. In step S1111, if j and m are not the same value (step S1111: No), the information management apparatus 100 proceeds to step S1102. In step S1111, if j and m are the same value (step S1111: Yes), the information management apparatus 100 ends the series of processes in this flowchart.

  In step S1104, when the subject ID in the identified mood change characteristic data 500-j is different from the subject ID included in the received mood change information (step S1104: No), the information management apparatus 100 performs step The process proceeds to S1102. In step S1105, when the type of mood change in the identified mood change characteristic data 500-j is different from the type of mood change included in the received mood change information (step S1105: No), the information management apparatus 100 The process proceeds to step S1102. In step S1106, when the conversation time in the specified mood change characteristic data 500-j is different from the conversation time included in the received mood change information (step S1106: No), the information management apparatus 100 goes to step S1102. Transition.

  By executing the fitness level calculation process described above, the information management apparatus 100 can calculate the fitness level Mαβ based on the normal conversation efficiency Cαβ and the compatibility level Lαβ. That is, the fitness Mαβ can be calculated based on the conversation efficiency Sαβ and the input history during conversation. By selecting a conversation partner based on the degree of matching Mαβ calculated here, it is possible to select a conversation partner based on the normal conversation efficiency Cαβ and the compatibility Lαβ. That is, the conversation partner can be selected based on the conversation efficiency Sαβ and the conversation input history. As a result, it is possible to select a conversation partner who is expected to be able to hear the situation at the time of mood change with respect to the conversation time from the target person and has the lowest possibility of damaging the subject's mood. it can.

  Further, the information management apparatus 100 may calculate the fitness Mαβ by setting the conversation efficiency coefficient WC to be larger as the character amount N of the text data is smaller, and setting the conversation efficiency coefficient WC to be smaller as the character amount N of the text data is larger. it can. As a result, the conversation partner can be selected by decreasing the weight of the normal conversation efficiency Cαβ in the fitness Mαβ as the character amount N of the text data is smaller and decreasing as the character amount N of the text data is larger. Therefore, as the character amount N is insufficient, it is possible to select a conversation partner who can expect more conversation, and it is possible to create text data effective for smooth nursing care.

  In addition, the information management apparatus 100 can select a conversation partner with whom conversation is efficiently performed in the same time zone as the time when the subject requests conversation. In addition, the information management apparatus 100 can select a conversation partner who has efficiently talked with a subject of the same mood change type.

(Relevance information DB update processing procedure of the information management apparatus 100)
FIG. 12 is a flowchart illustrating an example of the fitness information DB update processing procedure of the information management apparatus 100 according to the embodiment. The fitness information DB update process is the process shown in step S1021 in FIG. 10C, and is executed by the CPU 301 of the information management apparatus 100. In the suitability calculation processing, the information management apparatus 100 first specifies the face-to-face conversation characteristic data 400-j corresponding to the voice ID of the text data registered in step S1020 from the face-to-face conversation information DB 210 (step S1201).

  Then, the information management apparatus 100 switches the context record flag of the specified face-to-face conversation characteristic data 400-j to “Done” (step S1202), and calculates a mood change amount ΔF (step S1203). The method of calculating the mood change amount ΔF is as described above with reference to FIG.

  Then, the information management apparatus 100 calculates a new compatibility level Lαβ (step S1204). As described above with reference to FIG. 8, the new compatibility level Lαβ is calculated as the new compatibility level Lαβ = the compatibility level Lαβ before update + the defined value QL × the mood change amount ΔF / the maximum mood change amount Rmax. After step S1204, the information management apparatus 100 registers the calculated compatibility Lαβ in the fitness information DB 230 in association with the subject ID and the conversation partner ID (step S1205).

  After step S1205, the information management apparatus 100 measures the character amount N of the text data registered in step S1020 (step S1206), and calculates the conversation efficiency Sαβ (step S1207). As described above with reference to FIG. 8, the conversation efficiency Sαβ is calculated as conversation efficiency Sαβ = character amount N / reproduction time T. Thereafter, the information management apparatus 100 calculates the normal conversation efficiency Cαβ (step S1208). The normal conversation efficiency Cαβ is calculated as normal conversation efficiency Cαβ = conversation efficiency Sαβ × standard reproduction time Ts / standard character amount Ns × standard normal conversation efficiency Cs, as described above with reference to FIG.

  After step S1208, the information management apparatus 100 registers the calculated normal conversation efficiency Cαβ in association with the target person ID and the conversation partner ID in the fitness information DB 230 (step S1209), and ends the series of processes in this flowchart. To do.

  By executing the fitness information DB update process described above, the information management apparatus 100 can calculate the compatibility Lαβ and the normal conversation efficiency Cαβ when text data is created.

(Text input processing procedure of staff terminal 102)
FIG. 13 is a flowchart illustrating an example of a text input processing procedure of the staff terminal 102 according to the embodiment. The text input process is a process executed by the CPU 301 of the staff terminal 102. In the text input process, the staff terminal 102 first determines whether or not an input of a creation request indicating that text data is to be created is received from the staff (step S1301), and if not accepted (step S1301: No), Wait until it is accepted.

  In step S1301, when an input of a creation request is accepted (step S1301: Yes), the staff terminal 102 transmits list request information to the information management apparatus 100 (step S1302). The list request information is received by the information management apparatus 100 in step S1014 of FIG. After step S1302, the staff terminal 102 determines whether or not the list information has been received from the information management apparatus 100 (step S1303). If not received (step S1303: No), the staff terminal 102 waits until it is received. The list information is information transmitted from the information management apparatus 100 in step S1016 of FIG.

  In step S1303, when the list information is received from the information management apparatus 100 (step S1303: Yes), the staff terminal 102 displays a list of the face-to-face conversation characteristic data 400-j included in the list information on the display (step S1304). . Then, the staff terminal 102 determines whether or not the selection of any of the face-to-face conversation characteristic data 400-j in the list has been received from the staff (step S1305), and if not received (step S1305: No), until it is received. stand by.

  When the selection is accepted (step S1305: Yes), the staff terminal 102 transmits the selection result to the information management apparatus 100 (step S1306). Then, the staff terminal 102 determines whether or not voice data has been received from the information management apparatus 100 (step S1307). If not received (step S1307: No), the staff terminal 102 waits until it is received. When the voice data is received (step S1307: Yes), the staff terminal 102 receives input of text data from the staff (step S1308). After that, the staff terminal 102 transmits the text data that has received the input to the information management apparatus 100 (step S1309), and the series of processes in this flowchart ends.

  By executing the text input process described above, the staff terminal 102 can create text data of the content of the voice data and transmit it to the information management apparatus 100.

  As described above, according to the present embodiment, the information management apparatus 100 outputs the conversation efficiency Sαβ when the mood change information is acquired from the portable terminal 101-i of the subject. Thereby, a conversation partner based on the conversation efficiency Sαβ can be selected. Therefore, it is possible to select a conversation partner who can expect more conversations per hour, and it is possible to efficiently create conversation content data.

  By creating efficient conversation content data, the staff can provide care using the data. Thereby, it is possible to make the staff easily recognize the psychological state of the target person such as whether the care recipients are compatible or how the caregiver's mood changes. Therefore, the staff can provide a service that fully considers the psychological situation of the subject.

  At this time, the information management apparatus 100 selects the conversation partner. However, the present invention is not limited to this. For example, the staff may select the conversation partner by outputting to the staff terminal 102. Since the information management device 100 can select the conversation partner based on the conversation efficiency Sαβ, it is possible to save the staff from having to select the conversation partner, so that the content data of the conversation can be created efficiently. .

  In addition, the information management apparatus 100 outputs the fitness Mαβ when mood change information is acquired from the mobile terminal 101-i of the subject. Thereby, the conversation partner based on the fitness Mαβ can be selected. Therefore, it is possible to select a conversation partner who can expect more conversations per hour and has the lowest possibility of impairing the subject's mood. It is possible to select a conversation partner in consideration of the conversation efficiency in the past conversation and the compatibility of the target person, and it is possible to create conversation contents data more efficiently.

  At this time, the information management apparatus 100 selects the conversation partner. However, the present invention is not limited to this. For example, the staff may select the conversation partner by outputting to the staff terminal 102. Since the information management apparatus 100 selects a conversation partner based on the matching degree Mαβ, it is possible to save the staff from having to select the conversation partner, so that data of conversation contents can be efficiently created. .

  Further, in order to grasp the psychological situation of the subject, it is desirable to register text data with a larger character amount N. Therefore, the information management apparatus 100 generates text data that is more effective for grasping the psychological situation of the target person by outputting the fitness Mαβ that weights the conversation efficiency Sαβ as the character amount N is smaller. You can select a conversation partner that can expect.

  Further, the information management apparatus 100 outputs the conversation efficiency Sαβ of the conversation partner who had the conversation in the same time zone as the time when the subject requested the conversation. Accordingly, it is possible to select a conversation partner who has had more conversations per hour in the same time zone, and it is possible to select a conversation partner who can expect a conversation considering a change in temporal feelings.

  In addition, the information management apparatus 100 outputs the conversation efficiency Sαβ of the conversation partner who has a conversation when the subject's mood change type is the same as this time. As a result, it is possible to select a conversation partner who has had more conversations per hour when the type of mood change is the same. That is, it is possible to select a conversation partner who can talk efficiently in a situation where the subject's feelings are the same.

  In addition, the information management apparatus 100 outputs the adaptability Mαβ of the conversation partner who had the conversation in the same time zone as the time when the subject requested the conversation. As a result, a conversation partner who has had more conversations per hour in the same time zone and who is unlikely to damage the subject's mood can be judged and selected in a composite manner. it can.

  In addition, the information management apparatus 100 outputs the degree of fitness Mαβ of the conversation partner who had a conversation when the subject's mood change type is the same as this time. This makes it possible to collectively determine conversation partners who have had more conversations per hour at the same mood change type and are less likely to damage the subject's mood. Can be selected.

  In addition, the information management apparatus 100 transmits the request information to the mobile terminal 101-i of the selected conversation partner. As a result, it is possible to save labor for the staff to request a conversation with the target person from the selected conversation partner, and to create data on the contents of the conversation more efficiently.

  Further, the information management apparatus 100 receives mood change information from the subject's portable terminal 101-i. Accordingly, the conversation partner can be selected more quickly than when the target person requests a conversation from the staff and selects the conversation partner. As time passes after the subject requests a conversation, the mood may change further, making it impossible to conduct an efficient conversation. Therefore, the conversation partner can have the conversation with the conversation target person without taking time from the time when the target person requests the conversation, and the conversation can be performed more efficiently.

  In addition, as described above, the information management apparatus 100 specifies a conversation partner who can expect to hear more psychological situations from the target person, and records the conversation between the target person and the conversation partner to obtain voice data. It was decided to make. Then, text information is newly created by extracting information effective for nursing care from the contents of the voice data by the staff. Thereby, it is expected that the text data includes more information effective for nursing care. Therefore, when the staff provides care to the subject based on the text data, the subject-oriented care can be facilitated.

  The text data is created by extracting information effective for nursing care from the contents of the voice data by the staff. However, the present invention is not limited to this. For example, the text data may be created by automatically converting the speech data of a conversation in which a psychological situation is sufficiently heard from the subject into a text by a technique such as a voice recognition technique. In that case, a cared person having higher conversation efficiency Sαβ than other cared persons is a person who has had a larger amount of conversation with the subject in the past. Accordingly, by selecting a conversation partner based on the conversation efficiency Sαβ, it is possible to select, as a conversation partner, a cared person who has performed a larger amount of conversation with the target person in the past. Therefore, a conversation partner who can expect a larger amount of conversation can be talked to the target person.

  In the embodiment, the subject person is a care recipient, but the subject person is not limited thereto, and may be a medical person or a childcare person. In the embodiment, the conversation partner is the target of the service. However, the present invention is not limited to this, and a service providing staff may be used.

  The information management method described in this embodiment can be realized by executing a program prepared in advance on a computer such as a personal computer or a workstation. The information management program is recorded on a computer-readable recording medium such as a hard disk, a flexible disk, a CD-ROM, an MO, and a DVD, and is executed by being read from the recording medium by the computer. The information management program may be distributed via a network such as the Internet.

  The following additional notes are disclosed with respect to the embodiment described above.

(Additional remark 1) The memory | storage means which memorize | stores the text data of conversation content, and conversation time in association with each conversation partner who had conversation with the subject,
Obtaining means for obtaining information on a conversation request from the subject;
Conversation efficiency for calculating conversation efficiency between the target person and the conversation partner by dividing the conversation time associated with the text data from the amount of text data stored in the storage means for each conversation partner. A calculation means;
An output means for outputting the conversation efficiency for each conversation partner calculated by the conversation efficiency calculation means when information on the conversation request is acquired by the acquisition means;
An information management device comprising:

(Appendix 2) The storage means
Each conversation partner further stores information indicating the type of the subject's mood during the conversation with the conversation partner,
Based on the conversation efficiency for each conversation partner and the information indicating the type of mood of the target person during the conversation for each conversation partner, the degree of suitability indicating the degree of suitability for conversation with the target person Is provided with a fitness calculation means for calculating for each conversation partner,
The output means includes
The information management apparatus according to appendix 1, wherein the fitness level of each conversation partner calculated by the fitness level calculation unit is output.

(Supplementary Note 3)
3. The information management apparatus according to appendix 2, wherein the fitness is calculated for each conversation partner by weighting the conversation efficiency as the character amount of the text data is smaller.

(Appendix 4) The storage means
Each conversation partner further stores a conversation time associated with the conversation partner,
Based on the conversation time and the acquisition time of information related to the conversation request, comprising a specifying means for specifying a conversation partner having a conversation in the same time zone from the plurality of conversation partners,
The output means includes
The information management apparatus according to appendix 1, wherein conversation efficiency for each specific conversation partner identified by the identifying means is output.

(Appendix 5) The storage means
Each conversation partner further stores information indicating the type of the subject's mood before the conversation with the conversation partner,
Among the plurality of conversation partners, information indicating the type of the subject's mood at the time of the conversation request included in the information related to the conversation request and the type of the subject's mood before the conversation with the conversation partner Provided with a specifying means for specifying a conversation partner whose information shown matches,
The output means includes
The information management apparatus according to appendix 1, wherein conversation efficiency for each specific conversation partner identified by the identifying means is output.

(Appendix 6) Based on the conversation efficiency for each specific conversation partner and the information indicating the type of mood of the target person for each specific conversation partner, to what extent is it suitable for talking with the target person A fitness level calculating means for calculating a fitness level that indicates whether or not each specific conversation partner,
The output means includes
6. The information management apparatus according to appendix 4 or 5, wherein the fitness level for each specific conversation partner calculated by the fitness level calculation unit is output.

(Supplementary note 7)
The information management apparatus according to appendix 6, wherein the degree of matching is calculated for each of the specific conversation partners by weighting the conversation efficiency as the character amount of the text data is smaller.

(Additional remark 8) When the information regarding the said conversation request | requirement is acquired, based on the conversation efficiency for every said conversation partner, the selection means which selects the conversation partner who should be made to talk with the said subject from several conversation partners is provided. ,
The output means includes
The information management apparatus according to appendix 1, wherein a selection result selected by the selection unit is output.

(Additional remark 9) When the information regarding the said conversation request | requirement is acquired, the selection means which selects the conversation partner which should be made to talk with the said subject from several conversation partners based on the fitness for every said conversation partner is provided. ,
The output means includes
4. The information management apparatus according to appendix 2 or 3, wherein the selection result selected by the selection means is output.

(Additional remark 10) When the information regarding the said conversation request | requirement is acquired, based on the conversation efficiency for every said specific conversation partner, the selection means which selects the conversation partner who should be made to talk with the said subject from several conversation partners With
The output means includes
6. The information management apparatus according to appendix 4 or 5, wherein a selection result selected by the selection unit is output.

(Additional remark 11) When the information regarding the said conversation request | requirement is acquired, the selection means which selects the conversation partner who should be made to talk with the said subject from several conversation partners based on the suitability for every said specific conversation partner With
The output means includes
The information management apparatus according to appendix 6 or 7, wherein the selection result selected by the selection means is output.

(Supplementary Note 12) The output means includes:
The information management apparatus according to any one of appendices 8 to 11, wherein the selection result is transmitted to a conversation partner to be conversed with the target person.

(Supplementary note 13) The acquisition means includes:
13. The information management device according to any one of appendices 1 to 12, wherein information related to the conversation request is received from a terminal device operated by the subject.

(Supplementary note 14) The information according to any one of supplementary notes 1 to 13, wherein the text data is text data of feature information of the subject created based on voice data of the conversation content. Management device.

(Supplementary note 15) The information management apparatus according to any one of supplementary notes 1 to 13, wherein the text data is text data converted from the voice data of the conversation content.

(Supplementary note 16) For each conversation partner who has a conversation with the target person, a computer accessible to storage means for storing the text data of conversation contents and conversation time in association with each other,
Obtaining information about a conversation request from the subject,
For each conversation partner, the conversation efficiency between the target person and the conversation partner is calculated by dividing the conversation time associated with the text data from the amount of text data stored in the storage means,
When the information about the conversation request is acquired, the calculated conversation efficiency for each conversation partner is output.
An information management program characterized by causing processing to be executed.

(Additional remark 17) The computer which can access the memory | storage means which associates and memorize | stores the text data and conversation time of conversation content for every conversation partner who had conversation with the subject,
Obtaining information about a conversation request from the subject,
For each conversation partner, the conversation efficiency between the target person and the conversation partner is calculated by dividing the conversation time associated with the text data from the amount of text data stored in the storage means,
When the information about the conversation request is acquired, the calculated conversation efficiency for each conversation partner is output.
An information management method characterized by that.

DESCRIPTION OF SYMBOLS 100 Information management apparatus 101-i Portable terminal 102 Staff terminal 210 Face-to-face conversation information DB
220 Mood change sheet DB
230 Goodness-of-fit information DB
240 Caregiver information DB
801 Storage unit 802 Acquisition unit 803 Identification unit 804 Conversation efficiency calculation unit 805 Suitability calculation unit 806 Selection unit 807 Output unit

Claims (12)

A storage means for storing the text data of the conversation content and the conversation time in association with each conversation partner having a conversation with the target person,
Obtaining means for obtaining information on a conversation request from the subject;
Conversation efficiency for calculating conversation efficiency between the target person and the conversation partner by dividing the conversation time associated with the text data from the amount of text data stored in the storage means for each conversation partner. A calculation means;
An output means for outputting the conversation efficiency for each conversation partner calculated by the conversation efficiency calculation means when information on the conversation request is acquired by the acquisition means;
An information management device comprising: The storage means
Each conversation partner further stores information indicating the type of the subject's mood during the conversation with the conversation partner,
Based on the conversation efficiency for each conversation partner and the information indicating the type of mood of the target person during the conversation for each conversation partner, the degree of suitability indicating the degree of suitability for conversation with the target person Is provided with a fitness calculation means for calculating for each conversation partner,
The output means includes
The information management apparatus according to claim 1, wherein the fitness level of each conversation partner calculated by the fitness level calculation unit is output. The fitness calculation means is
The information management apparatus according to claim 2, wherein the degree of matching is calculated for each conversation partner by weighting the conversation efficiency as the character amount of the text data is smaller. The storage means
Each conversation partner further stores a conversation time associated with the conversation partner,
Based on the conversation time and the acquisition time of information related to the conversation request, comprising a specifying means for specifying a conversation partner having a conversation in the same time zone from the plurality of conversation partners,
The output means includes
The information management apparatus according to claim 1, wherein conversation efficiency for each specific conversation partner identified by the identifying unit is output. The storage means
Each conversation partner further stores information indicating the type of the subject's mood before the conversation with the conversation partner,
Among the plurality of conversation partners, information indicating the type of the subject's mood at the time of the conversation request included in the information related to the conversation request and the type of the subject's mood before the conversation with the conversation partner Provided with a specifying means for specifying a conversation partner whose information shown matches,
The output means includes
The information management apparatus according to claim 1, wherein conversation efficiency for each specific conversation partner identified by the identifying unit is output. Conformity that indicates how well it is suitable for a conversation with the target person based on the conversation efficiency for each specific conversation partner and information indicating the type of mood of the target person for each specific conversation partner A degree-of-fit calculation means for calculating the degree of each specific conversation partner;
The output means includes
6. The information management apparatus according to claim 4, wherein the fitness level for each specific conversation partner calculated by the fitness level calculation unit is output. The fitness calculation means is
The information management apparatus according to claim 6, wherein the degree of matching is calculated for each specific conversation partner by weighting the conversation efficiency as the character amount of the text data is smaller. When information related to the conversation request is acquired, a selection unit that selects a conversation partner to be talked to the target person from a plurality of conversation partners based on conversation efficiency for each conversation partner,
The output means includes
The information management apparatus according to claim 1, wherein the selection result selected by the selection unit is output. When information related to the conversation request is acquired, a selection unit that selects a conversation partner to be conversed with the target person from a plurality of conversation partners based on the fitness for each conversation partner,
The output means includes
4. The information management apparatus according to claim 2, wherein a selection result selected by the selection unit is output. When information related to the conversation request is acquired, a selection unit that selects a conversation partner to be talked to the target person from a plurality of conversation partners based on conversation efficiency for each specific conversation partner,
The output means includes
6. The information management apparatus according to claim 4, wherein the selection result selected by the selection means is output. For each conversation partner who has a conversation with the target person, a computer that can access the storage means for storing the text data of the conversation contents and the conversation time in association with each other,
Obtaining information about a conversation request from the subject,
For each conversation partner, the conversation efficiency between the target person and the conversation partner is calculated by dividing the conversation time associated with the text data from the amount of text data stored in the storage means,
When the information about the conversation request is acquired, the calculated conversation efficiency for each conversation partner is output.
An information management program characterized by causing processing to be executed. For each conversation partner who has a conversation with the target person, a computer that can access storage means for storing the text data of the conversation contents and the conversation time in association with each other,
Obtaining information about a conversation request from the subject,
For each conversation partner, the conversation efficiency between the target person and the conversation partner is calculated by dividing the conversation time associated with the text data from the amount of text data stored in the storage means,
When the information about the conversation request is acquired, the calculated conversation efficiency for each conversation partner is output.
An information management method characterized by that.

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