Information processing device, information processing method, and information processing program

Abstract

To provide an information processing device, an information processing method and an information processing program for properly optimizing a feedback for reflections by a user.SOLUTION: In an information processing system in which an inputter device, a viewer device, and an information processing device are communicably connected, an information processing device 100 comprises a communication unit 110, a storage unit 120, and a control unit 130. A collection unit 131 collects dialog history information that includes reflection information, and feedback information which is responded to reflections by a viewer. A detection unit 132 detects a dialog pattern on the basis of the result of evaluation of the feedback having been evaluated by an inputter, and the dialog history information. When a reflection is newly inputted, a selection unit 134 selects, on the basis of the newly inputted new reflection and the dialog pattern detected by the detection unit, a recommended feedback which is recommended as a response by the viewer who has viewed the new reflection.SELECTED DRAWING: Figure 2

Description

Technical Field

[0003]

[0001] The present invention relates to an information processing apparatus, an information processing method, and an information processing program.

Background Art

[0002] Conventionally, a mechanism for supporting experiential learning that converts experience into learning has been proposed.

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the above conventional technology, it is not always possible to optimize the feedback so as to appropriately feedback on the reflection by the user.

[0005] For example, in the above conventional technology, based on the history of indicators in the retrospective evaluation of the emotional aspect and the ability display aspect of the experiencer for the experienced event, by analyzing the history of the emotional aspect and the ability display aspect of the experiencer, it only controls so that the experiencer can view the analysis result.

[0006] From this, it is considered that the above conventional technology has room for improvement in optimizing the feedback so as to appropriately feedback on the reflection by the user. ​​​​​​​​ An information processing device according to one aspect of the present invention is an information processing device that supports a dialogue between an inputter who inputs a reflection, which is a reflection on an activity, and a viewer who views the reflection, and is characterized by comprising: a collection unit that collects dialogue history information including reflection information indicating the reflection and feedback information indicating the feedback in which the viewer responded to the reflection; a detection unit that detects a dialogue pattern based on the evaluation result in which the feedback was evaluated by the inputter and the history information; and a selection unit that, when a new reflection is input, selects a recommended feedback that is recommended as a response by the viewer who viewed the new reflection, based on the newly input new reflection and the dialogue pattern detected by the detection unit.

[0009] An information processing method according to one aspect of the present invention is an information processing method performed by an information processing device that supports a dialogue between an inputter who inputs a reflection, which is a reflection on an activity, and a viewer who views the reflection, and is characterized by including a collection step of collecting dialogue history information including reflection information indicating the reflection and feedback information indicating the feedback in which the viewer responded to the reflection; a detection step of detecting a dialogue pattern based on the evaluation result in which the feedback was evaluated by the inputter and the history information; and a selection step of selecting a recommended feedback that is recommended as a response by the viewer who viewed the new reflection, based on the newly input new reflection and the dialogue pattern detected by the detection step when a new reflection is input.

[0010] An information processing program according to one aspect of the present invention is an information processing program executed by an information processing device that supports a dialogue between an inputter who inputs a reflection, which is a reflection on an activity, and a viewer who views the reflection, and is an information processing program that causes the information processing device to execute a collection procedure for collecting dialogue history information including reflection information indicating the reflection and feedback information indicating the feedback in which the viewer responded to the reflection; a detection procedure for detecting a dialogue pattern based on the evaluation result in which the feedback was evaluated by the inputter and the history information; and a selection procedure for selecting a recommended feedback that is recommended as a response by the viewer who viewed the new reflection, based on the newly input reflection and the dialogue pattern detected by the detection procedure, when a new reflection is input. [Effects of the Invention]

[0011] According to the present invention, for example, feedback can be optimized to provide appropriate feedback to user reflections. [Brief explanation of the drawing]

[0012] [Figure 1] Figure 1 shows an example of an information processing system according to an embodiment. [Figure 2] Figure 2 shows an example of the configuration of an information processing device according to the embodiment. [Figure 3] Figure 3 is an explanatory diagram illustrating a specific example of information processing according to the embodiment. [Figure 4] Figure 4 shows an example of the components that make up reflection. [Figure 5] Figure 5 is a flowchart showing the information processing procedure according to the embodiment. [Figure 6] Figure 6 is a block diagram showing an example of the hardware configuration of the information processing device 100 according to the embodiment. [Modes for carrying out the invention]

[0013] Below, an example of an embodiment for implementing an information processing device, an information processing method, and an information processing program (hereinafter referred to as "embodiment") will be described in detail with reference to the drawings. Note that this embodiment does not limit the information processing device, information processing method, and information processing program. Furthermore, the same parts will be denoted by the same reference numerals in the following embodiments, and redundant explanations will be omitted.

[0014] [Embodiment] [1. Introduction] In organizational management, it is considered important to cultivate employee autonomy (for example, employees' autonomous thinking and actions) and utilize it to create new value. For instance, it is considered particularly important in organizational development for employees to gain experience by autonomously gaining insights and taking action, and then to transform that experience into learning, thereby turning that learning into organizational knowledge.

[0015] This invention was made in view of the above circumstances, and its purpose is to provide a service that connects human resource development and organizational development and supports the activation of organizational learning. For example, this invention utilizes a "dialogue" framework that starts with "reflection," which is a review / introspection of daily activities, to provide a service that supports individual updates and team or organizational updates.

[0016] In the following, the service in question (autonomous human resource development service) will be referred to as "Service SA," and the information processing required to realize Service SA (information processing according to the embodiment) will be described in detail.

[0017] [2. System Configuration] First, the configuration of the system for realizing the information processing according to the embodiment will be explained using Figure 1. Figure 1 is a diagram showing an example of an information processing system according to the embodiment. Figure 1 shows information processing system 1 as an example of an information processing system according to the embodiment.

[0018] In the example of FIG. 1, the information processing system 1 includes an input device 10, a viewer device 20, and an information processing device 100. Also, the input device 10, the viewer device 20, and the information processing device 100 are communicably connected by wire or wirelessly via a predetermined network N.

[0019] The input device 10 is an information processing terminal used by an input person when inputting a reflection, which is a retrospective on activities. The input device 10 is realized by, for example, a smartphone, a tablet terminal, a notebook PC (Personal Computer), a desktop PC, a mobile phone, a PDA (Personal Digital Assistant), or the like.

[0020] Also, an application for realizing the transmission and reception of information between the input device 10 and the information processing device 100 may be introduced into the input device 10. Such an application may be implemented as a dedicated application for accessing the information processing device 100, or may be a general-purpose application such as a browser. For example, an input person can input reflection information indicating a reflection via a predetermined screen corresponding to such an application.

[0021] Also, activities corresponding to the reflection include activities within a predetermined organization. Activities within a predetermined organization include, for example, daily operations in a company organization, project operations for carrying out a specific project in a company organization, and the like. Of course, the activities corresponding to the reflection are not limited to such examples.

[0022] The viewer device 20 is an information processing terminal used by a viewer when viewing a reflection input by an input person. The viewer device 20 is realized by, for example, a smartphone, a tablet terminal, a notebook PC, a desktop PC, a mobile phone, a PDA, or the like.

[0023] Furthermore, the viewer device 20 may also have an application installed to enable the sending and receiving of information with the information processing device 100. This application may be implemented as a dedicated application for accessing the information processing device 100, or it may be a general-purpose application such as a browser. For example, the viewer can view the reflection information through a predetermined screen corresponding to this application.

[0024] In the following, this application for accessing the information processing device 100 will be referred to as "App AP".

[0025] The information processing device 100 is a central device for providing service SA and realizing information processing according to the embodiment. For example, the information processing device 100 is an information processing device that supports dialogue between an inputter who inputs a reflection, which is a review of an activity, and a viewer who views the reflection.

[0026] Furthermore, if the input device 10 and the viewer device 20 are edge computers that perform edge processing near the users using the service SA, then the information processing device 100 may be, for example, a cloud computer that performs processing on the cloud side. In other words, the information processing device 100 may be a server device.

[0027] Here, the term "users of Service SA" refers to both those who input reflections and those who view reflections. For example, users may input reflections by reflecting on their own activities, or they may view reflections input by others. Therefore, users can be both inputters and viewers.

[0028] Furthermore, an example of an inputter could be an individual employee belonging to a company organization, and an example of a viewer could be a representative person within the company organization (for example, the team leader of the inputter's team, the department head of the inputter's department, etc.). In this case, a relationship such as subordinate and superior may exist between the inputter and the viewer. Of course, the relationship between the inputter and the viewer is not limited to the examples given. For example, if the inputter is a specific employee within a company organization, the viewer may be another employee within that company organization.

[0029] Furthermore, for the reasons shown in Figure 1, the information processing system 1 may be divided by company organization. For example, in the example in Figure 1, the information processing system 1 includes a system 1n corresponding to each company organization Xn that is a member of the service SA. In this example, system 1n includes an input device 10-n corresponding to company organization Xn and a viewer device 20-n corresponding to company organization Xn.

[0030] Here, taking company organization X1 as an example of an arbitrary company organization Xn, the information processing system 1 may include a system 11 corresponding to company organization X1, as shown in Figure 1. Furthermore, according to the example in Figure 1, system 11 includes an input device 10-1 used for inputting reflections by one employee belonging to company organization X1 (for example, a regular employee without a managerial position), and a viewer device 20-1 used for viewing reflections by another employee belonging to company organization X1 (for example, a representative employee with a managerial position).

[0031] [3. Configuration of the Information Processing Device] From here, the information processing device 100 according to the embodiment will be described using Figure 2. Figure 2 is a diagram showing an example of the configuration of the information processing device 100 according to the embodiment. As shown in Figure 2, the information processing device 100 has a communication unit 110, a storage unit 120, and a control unit 130.

[0032] (Regarding Communications Unit 110) The communication unit 110 is implemented, for example, by a NIC (Network Interface Card). The communication unit 110 is connected to the network N by wire or wireless connection and transmits and receives information between, for example, the input device 10 and the viewer device 20.

[0033] (Regarding memory unit 120) The storage unit 120 is implemented by, for example, semiconductor memory elements such as RAM (Random Access Memory) and flash memory, or storage devices such as hard disks and optical discs. The storage unit 120 has a history information database 121 and an interaction pattern database 122.

[0034] (Regarding the historical information database 121) The history information database 121 stores dialogue history information, which includes reflection information indicating the reflections entered by the inputter and feedback information indicating the feedback the viewer gave in response to the reflections.

[0035] For example, if the user's response to a set of questions designed to prompt reflection on an activity (i.e., reflection) marks the beginning of the dialogue, the dialogue then progresses as others provide feedback on the reflection, and the user who entered the reflection ultimately evaluates this feedback.

[0036] In this way, a series of interactions between the inputter and the viewer, involving reflection and feedback, are considered a single dialogue. In this case, the history information database 121 may manage the reflections (reflection information) entered within the dialogue identified by the dialogue ID, and the feedback (feedback information) given in response to the reflections.

[0037] For example, in the history information database 121, for each dialogue ID, reflection information and feedback information may be stored as associated information for that dialogue ID.

[0038] As will be explained later in Figure 3, the reflection information may include the inputter's opinion on a given question, the inputter's experience that forms the basis of that opinion, the inputter's emotions that arose from that experience, and the inputter's values ​​that form the basis of those emotions.

[0039] Furthermore, the feedback information includes text information indicating the content of the feedback. The text information indicating the content of the feedback is the feedback comment, which is a comment made by the viewer in response to the reflection. The feedback information may also include type information indicating the type of comment the feedback comment is.

[0040] (Regarding Dialogue Pattern Database 122) The dialogue pattern database 122 stores information about dialogue patterns detected by the detection unit 132, which will be described later.

[0041] For example, in the dialogue pattern database 122, for each pattern ID that identifies a dialogue pattern, pattern information indicating the dialogue pattern may be stored as associated information.

[0042] (Regarding the control unit 130) The control unit 130 is implemented by a CPU (Central Processing Unit) or MPU (Micro Processing Unit), etc., which executes various programs (for example, information processing programs according to the embodiment) stored in the memory device inside the information processing device 100 using RAM as the working area. Alternatively, the control unit 130 can be implemented by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

[0043] As shown in Figure 3, the control unit 130 includes a collection unit 131, a detection unit 132, an acquisition unit 133, a selection unit 134, and a provision unit 135, and realizes or executes the information processing functions and operations described below. Note that the internal configuration of the control unit 130 is not limited to the configuration shown in Figure 2, and other configurations are also possible as long as they perform the information processing described later. Also, the connection relationships of the various processing units in the control unit 130 are not limited to the connection relationships shown in Figure 2, and other connection relationships are also possible.

[0044] (Regarding Collection Unit 131) The collection unit 131 collects reflection information in response to input of reflection as a reflective evaluation (or introspection) of an activity. The collection unit 131 also collects feedback information in which the viewer responds to the reflection. Specifically, the collection unit 131 collects dialogue history information, which is a series of interactions between the inputter and the viewer through reflection and feedback. In other words, the collection unit 131 collects dialogue history information, which includes reflection information and feedback information.

[0045] Furthermore, the collection unit 131 stores the history information of the conversation in the history information database 121. For example, for each conversation, the collection unit 131 issues a conversation ID to identify that conversation, and uses the issued conversation ID to manage the history information of the conversation in the history information database 121.

[0046] The reflection information may include any of the following components that constitute the reflection: the inputter's opinion on a given question, the inputter's experience that forms the basis of the opinion, the inputter's feelings that arose from the experience, or the inputter's values ​​that form the basis of the feelings.

[0047] Feedback information may include either text information describing the content of the feedback, or type information indicating the category of the feedback.

[0048] (Regarding the detection unit 132) The detection unit 132 detects a dialogue pattern based on the evaluation result of the feedback evaluated by the inputter and the dialogue history information.

[0049] For example, the detection unit 132 uses a set of feedback data consisting of feedback information indicating a target feedback to which a predetermined evaluation result has been given, and reflection information indicating a reflection corresponding to the target feedback, as learning data. Based on the learning result, in which the relationship between information about the component items and the feedback information indicating the target feedback has been learned, the detection unit detects a dialogue pattern.

[0050] For example, the detection unit 132 may detect dialogue patterns corresponding to the relationship between the inputter's attributes and the viewer's attributes. The detection unit 132 may also detect dialogue patterns corresponding to the relationship between reflection and feedback. For example, the detection unit 132 may detect dialogue patterns corresponding to the relationship between reflection and feedback, which is based on the relationship between the inputter's attributes and the viewer's attributes.

[0051] Furthermore, the detection unit 132 stores the detected pattern in the dialogue pattern database 122.

[0052] (Regarding acquisition section 133) The acquisition unit 133 acquires an ideal model in which state transitions are defined, representing ideal changes in the state of the inputter, and which are estimated from the constituent items corresponding to the dialogue pattern. Specifically, the acquisition unit 133 acquires an ideal model in which state transitions are estimated from the emotions and values ​​among the constituent items, and which represent state transitions in which pairs of emotions and values ​​are classified in stages according to the relationship between the state of the inputter and the state of the viewer. Details of the ideal model are explained in Figure 3.

[0053] (Regarding selection section 134) When a new reflection is input, the selection unit 134 selects a recommended feedback that is suggested as a response by the viewer who viewed the new reflection, based on the newly input reflection and the dialogue pattern detected by the detection unit 132.

[0054] For example, the selection unit 134 selects recommended feedback based on reflection information indicating a new reflection, an ideal model, and a dialogue pattern. For example, by comparing the reflection information indicating a new reflection with the ideal model, the selection unit 134 identifies which stage of the state transition in the ideal model the relationship between the state of the target inputter, who input the new reflection, and the state of the target viewer, who views the new reflection, is at. Then, based on the identified stage and the dialogue pattern, the selection unit 134 selects recommended feedback that is recommended as a response by the target viewer. As an example, the selection unit 134 may select a dialogue pattern that corresponds to the identified stage and includes a pair of emotions and values ​​as constituent items as recommended feedback.

[0055] (Regarding Section 135) The providing unit 135 provides the target viewer with the recommended feedback selected by the selection unit 134. For example, the providing unit 135 may provide the target viewer with recommended feedback that is controlled to be selectable.

[0056] [4. Specific Examples of Information Processing] Next, a specific example of the information processing implemented in the embodiment described in Figure 2 will be explained using Figure 3.

[0057] Figure 3 is an explanatory diagram illustrating a specific example of information processing according to the embodiment. In Figure 3, information processing is explained using system 11, which corresponds to company organization X1, as an example, among the systems 1n for each company organization Xn included in the information processing system 1 shown in Figure 1.

[0058] In other words, the example in Figure 3 illustrates information processing in response to a dialogue between users belonging to company organization X1. More specifically, the information processing according to the embodiment will be explained using a dialogue DLz between any general employee Rx belonging to company organization X1 and any representative employee Fy who has a role in managing general employee Rx (e.g., team leader or supervisor).

[0059] Furthermore, the dialogue DLz proceeds with general employee Rx inputting reflections in response to predetermined questions designed to prompt reflection on work within company organization X1, and representative employee Fy providing feedback comments. The dialogue ends when general employee Rx evaluates these comments. In the example shown in Figure 3, general employee Rx corresponds to the inputter, and representative employee Fy corresponds to the viewer.

[0060] In the example in Figure 3, when distinguishing any general employee Rx from a specific general employee, a predetermined numerical value is applied to "x". For example, Figure 3 shows general employees R11, U12, U13, etc., as examples of general employee Rx.

[0061] Furthermore, in the example shown in Figure 3, just as "x" is used to distinguish general employee Rx, attribute Ax, reflection information RLx, etc., may also be distinguished accordingly. For example, Figure 3 shows attribute A11, which corresponds to general employee R11, as an example of attribute Ax, and reflection information RL11, which corresponds to general employee R11, as an example of reflection information RLx.

[0062] Furthermore, in the example in Figure 3, when distinguishing any representative member Fy from a specific representative member, a predetermined numerical value is applied to "y". For example, Figure 3 shows representative members F21, F22, F23, etc., as examples of representative members Fy.

[0063] Furthermore, in accordance with the above example, if "y" is used to distinguish the representative employee Fy, then attributes Ay, feedback information FBy, etc., may also be distinguished accordingly. For example, Figure 3 shows attribute A21 corresponding to representative employee F21 as an example of attribute Ay, and feedback information FB21 corresponding to representative employee F21 as an example of feedback information FBy.

[0064] Figure 3 shows examples of how to distinguish and represent various types of information by applying predetermined values ​​to "x" and "y," but since these can be explained by following the examples above, the details will be omitted.

[0065] Furthermore, in the example shown in Figure 3, a predetermined numerical value may be applied to the "z" in the dialogue DLz to distinguish it as a specific dialogue.

[0066] First, let's explain step S1 in Figure 3. In step S1, the collection unit 131 collects the history information of the dialogue DLz.

[0067] Figure 3 shows an example of a dialogue DLz conducted between a regular employee Rx and a representative employee Fy.

[0068] For example, suppose a regular employee Rx reviews a set of questions via the application AP to reflect on their work within company organization X1. In this case, Rx reflects on their work and inputs their self-assessment of that work into a designated screen within the application AP. Based on this input, a dialogue DLz is initiated.

[0069] According to the example in Figure 3, the reflection information RLx, which is the information actually entered as reflection, may include the following components that make up the reflection: opinion OPx, experience EXx, emotion EMx, and values ​​VAx. In other words, a regular employee Rx may input opinion OPx, experience EXx, emotion EMx, and values ​​VAx as reflection information.

[0070] As shown in Figure 3, the application AP may employ a method that allows general employees Rx to freely input opinions OPx and experiences EXx. On the other hand, the application AP may employ a method that allows emotion EMx and values ​​VAx to be entered in a selection format.

[0071] Here, we will explain a specific example of the constituent items using Figure 4. Figure 4 is a diagram showing an example of the constituent items that make up reflection.

[0072] First, Opinion OPx may be equivalent to answers to predetermined questions designed to prompt reflection on work. These questions may be unique to each company organization Xn, or they may be common to all company organizations Xn.

[0073] Experience (EXx) can be the real-life experiences that form the background to Opinion (OPx), or the knowledge gained from those experiences.

[0074] Emotions (EMx) can be emotions linked to experiences (EXx), such as real-life experiences or knowledge.

[0075] Values ​​(VAx) can be things you cherish, like, or dislike, which are the triggers for generating emotions (EMx).

[0076] Figure 4 also shows examples of content that is actually freely entered as opinion OPx, as well as as content that is actually freely entered as experience EXx, as well as as content selected as emotion EMx, and as content selected as values ​​VAx.

[0077] Furthermore, as shown in the example in Figure 4, in response to the question, an opinion OPx such as "I want to create a situation where sales members can take initiative and have a positive impact on the company and customers" may be entered. In addition, an experience EXx behind the opinion OPx may be entered such as "Because being the first person that comes to mind for colleagues and customers has increased the range of work options and challenges I can take on."

[0078] Furthermore, as shown in the example in Figure 4, emotions such as "enjoyment," "satisfaction," and "excitement" may be selected as Emotions (EMx) linked to Experiences (EXx) (real-world experiences and knowledge). In addition, values ​​such as "decisiveness," "growth," and "responsibility" may be selected as Values ​​(VAx) related to things that are important to you, things you like, and things you dislike, which may have triggered the generation of Emotions (EMx).

[0079] Let's return to the explanation of Figure 3. Up to this point, we have shown an example where a regular employee Rx inputs reflection information RLx in response to a question. However, a regular employee Rx may also input attribute information that indicates their own attributes Ax. Attributes Ax corresponding to a regular employee Rx may include, for example, the employee Rx's age, gender, hobbies, department, job title, etc.

[0080] Based on previous examples, a regular employee Rx may input a reflection that includes reflection information RLx and attribute Ax.

[0081] Next, when Representative Employee Fy views the reflection information RLx entered by General Employee Rx, it provides predetermined information as feedback to General Employee Rx's reflection. For example, Representative Employee Fy provides feedback including a comment CMy indicating its opinion on the reflection information RLx, and information indicating the type KDy of the comment CMy. In the following, the information provided as feedback to General Employee Rx will be defined as feedback information FBy, which includes text information indicating the comment CMy and type information indicating the type KDy of the comment CMy.

[0082] Feedback information FBy represents the feedback that representative employee Fy, who is the viewer, has given in response to the reflection information RLx.

[0083] Furthermore, Representative Employee Fy may not only provide feedback but also input attribute information that indicates their own attributes Ay. Attributes Ay corresponding to Representative Employee Fy may include, for example, Representative Employee Fy's age, gender, hobbies, department, position, etc.

[0084] Next, when feedback information FBy is entered by representative employee Fy, general employee Rx evaluates the feedback from representative employee Fy. For example, general employee Rx evaluates comment CMy, which is included in the feedback information FBy, using terms such as "good" or "bad" from the perspective of whether or not the content of the comment CMy was useful to them. Note that the method of evaluation is not limited to the example given.

[0085] Thus, the series of dialogues DLz may be terminated once the general employee Rx has made its evaluation. In this case, the collection unit 131 acquires the information exchanged between the general employee Rx and the representative employee Fy from the start to the end of the dialogue DLz. Specifically, the collection unit 131 acquires a pair of attribute Ax and reflection information RLx as information regarding the general employee Rx's reflection, and a pair of attribute Ay and feedback information FBy as information regarding the representative employee Fy's feedback. The collection unit 131 also acquires an evaluation EVx indicating the evaluation result by the general employee Rx (for example, "good" or "bad").

[0086] Furthermore, the collection unit 131 associates reflection information and feedback information with the dialogue ID that identifies the dialogue DLz. The collection unit 131 then stores the associated information as history information of the dialogue DLz in the history information database 121.

[0087] For example, suppose a dialogue DL1 takes place between general employee R11 and representative employee F21. In this case, the collection unit 131 acquires a set of attribute A11 and reflection information RL11-1 as information regarding the reflection from general employee R11's side, and a set of attribute A21 and feedback information FB21-1 as information regarding the feedback from representative employee F21's side.

[0088] The collection unit 131 then associates attribute A11 with reflection information RL11-1 for the dialogue ID "DL1" which identifies dialogue DL1. The collection unit 131 also associates attribute A21 with feedback information FB21-1 for the dialogue ID "DL1".

[0089] Furthermore, suppose that a dialogue DL2 takes place between general employee R12 and representative employee F22. In this case, the collection unit 131 acquires a set of attribute A12 and reflection information RL12-2 as information regarding the reflection from general employee R12's side, and acquires a set of attribute A22 and feedback information FB22-2 as information regarding the feedback from representative employee F22's side.

[0090] The collection unit 131 then associates attribute A12 with reflection information RL12-2 to the dialogue ID "DL2" which identifies dialogue DL2. The collection unit 131 also associates attribute A22 with feedback information FB22-2 to the dialogue ID "DL2".

[0091] Furthermore, suppose a separate dialogue DL3 takes place between general employee R12 and representative employee F22, distinct from dialogue DL2. In this case, the collection unit 131 acquires a set of attribute A12 and reflection information RL12-3 as information regarding general employee R12's reflection, and a set of attribute A22 and feedback information FB22-3 as information regarding representative employee F22's feedback.

[0092] The collection unit 131 then associates attribute A12 with reflection information RL12-3 for the dialogue ID "DL3" which identifies dialogue DL3. The collection unit 131 also associates attribute A22 with feedback information FB22-3 for dialogue ID "DL3".

[0093] Furthermore, there are cases where multiple representative employees Fx provide feedback on a reflection input by one general employee Rx. In other words, multiple representative employees Fx may participate in a single dialogue DLz corresponding to one general employee Rx. As an example of such a case, suppose a dialogue DL4 takes place between general employee R13 and representative employees F23 and F24. In this case, the collection unit 131 acquires the set of attribute A13 and reflection information RL13-4 as information on general employee R13's reflection, and the set of attribute A23 and feedback information FB23-4 as information on representative employee F23's feedback. The collection unit 131 also acquires the set of attribute A24 and feedback information FB24-4 as information on representative employee F24's feedback.

[0094] The collection unit 131 then associates attribute A13 with reflection information RL13-4 for the dialogue ID "DL4" which identifies dialogue DL4. The collection unit 131 also associates attribute A23 with feedback information FB23-4 for dialogue ID "DL4". The collection unit 131 also associates attribute A24 with feedback information FB24-4 for dialogue ID "DL4".

[0095] In this way, the collection unit 131 collects historical information of the dialogue DLz each time a dialogue DLz is performed, and stores the collected historical information in the history information database 121. An example of the historical information corresponding to each of the dialogue DL1, DL2, DL3, and DL4 described above is shown in step S2, which will be explained next in Figure 3.

[0096] In step S2, the detection unit 132 detects a pattern in the dialogue DLz based on the evaluation EVx (e.g., "good" or "bad") by the general employee Rx for the feedbacked comment CMy and the history information of the dialogue DLz. For example, the detection unit 132 may perform the process of detecting a dialogue pattern when sufficient history information of the dialogue DLz has been accumulated.

[0097] For example, the detection unit 132 extracts feedback information FBy, which includes the target comment CMy (target feedback) that received a good evaluation from the comments CMy, and reflection information RLx, which is included in the dialogue DLz corresponding to this feedback information FBy, from the history information of the dialogue DLz. Here, the extracted reflection information RLx may indicate the reflection that was the source of the feedback of the target comment CMy.

[0098] Here, let's assume that in dialogue DL1, employee R11 gave a positive evaluation to comment CM21 contained in feedback information FB21-1. In this case, the detection unit 132 extracts information associated with dialogue ID "DL1". For example, the detection unit 132 extracts the pair of attribute A11 and reflection information RL11-1, and the pair of attribute A21 and feedback information FB21-1.

[0099] Furthermore, suppose that in dialogue DL2, employee R12 gave a positive evaluation to comment CM22 included in feedback information FB22-2. In this case, the detection unit 132 extracts information associated with dialogue ID "DL2". For example, the detection unit 132 extracts the pair of attribute A12 and reflection information RL12-2, and the pair of attribute A22 and feedback information FB22-2.

[0100] Furthermore, suppose that in dialogue DL3, employee R12 gave a positive evaluation to comment CM22 included in feedback information FB22-3. In this case, the detection unit 132 extracts information associated with dialogue ID "DL3". For example, the detection unit 132 extracts the pair of attribute A12 and reflection information RL12-3, and the pair of attribute A22 and feedback information FB22-3.

[0101] On the other hand, suppose in dialogue DL4, employee R13 gave a negative rating to comment CM23 included in feedback information FB23-4. Also suppose that employee R13 gave a negative rating to comment CM24 included in feedback information FB24-4. In such cases, the detection unit 132 does not extract information associated with dialogue ID "DL4".

[0102] According to the example above, the detection unit 132 uses the information extracted for each of the dialogues DL1, DL2, and DL3 as training data to detect patterns in dialogue DLz. Specifically, the detection unit 132 uses the sets extracted for dialogue DL1 as one training dataset. The detection unit 132 also uses the sets extracted for dialogue DL2 as one training dataset. The detection unit 132 also uses the sets extracted for dialogue DL3 as one training dataset. Based on the training datasets, the detection unit 132 learns the relationship between information about the constituent items and the target comment CMy. For example, based on the training datasets, the detection unit 132 can learn the relationship between information about the constituent items and the target comment CMy, specifically the relationship based on the attribute Ax of general employee Rx and the attribute Ay of representative employee Fy.

[0103] For example, the detection unit 132 may learn which attribute Ax general employee Rx and which attribute Ay representative employee Fy provide feedback that tends to result in a good evaluation. Alternatively, the detection unit 132 may learn which attribute CMy provides feedback that tends to result in a good evaluation for which component reflection information RLx from general employee Rx.

[0104] In other words, the detection unit 132 may learn what kind of comments CMy from representative employee Fy with attribute Ay tend to be given as feedback to what kind of reflection information RLx of what kind of component items by general employee Rx with attribute Ax, and what kind of comments CMy from representative employee Fy with attribute Ay, tend to result in a good evaluation.

[0105] Furthermore, the detection unit 132 may learn which comment CMy comments containing important keywords tend to receive good ratings when provided as feedback, by inferring important keywords as keywords that are likely to receive good ratings based on the training data. As another example, the detection unit 132 may learn which related keywords among the related keywords related to important keywords tend to receive good ratings when comment CMy comments contain them as feedback.

[0106] The detection unit 132 may then detect the trends obtained from the learning results as dialogue DLz patterns. Figure 3 shows an example in which the detection unit 132 has detected six dialogue DLz patterns. Specifically, it shows an example in which the detection unit 132 has detected dialogue DLz patterns PT1, PT2, ... PT6.

[0107] The learning process may be performed by a unit other than the detection unit 132. For example, the information processing device 100 may have a generation unit that generates a model that outputs information about the patterns of the dialogue DLz by having the model learn relationships based on learning data. In this case, the detection unit 132 may use the model generated by the generation unit to detect the patterns of the dialogue DLz. As another example, the information processing system 1 may include a dedicated learner that performs the learning process, in which case the detection unit 132 may use the model generated by the learner to detect the patterns of the dialogue DLz.

[0108] Next, step S3 will be explained. If the interactive DLz has been patterned in step S2, step S3 may be performed. In step S3, the acquisition unit 133 acquires the ideal model. Figure 3 shows an example in which the acquisition unit 133 acquires the ideal model MD.

[0109] Here, we will explain the ideal model MD in more detail using the example in Figure 3. The ideal model MD is a model in which state transitions are estimated from the constituent items corresponding to the patterns of the dialogue DLz, and state transitions that show the ideal change in the state of the general employee Rx (inputter) are defined. More specifically, the ideal model MD is a model in which state transitions are estimated from the emotions and values ​​among the constituent items, and the pairs of emotions and values ​​are classified stepwise according to the relationship between the state of the general employee Rx (inputter) and the state of the representative employee Fy (viewer).

[0110] As shown in the example in Figure 3, the ideal MD model is classified into five phases: Phase 1 PH1, Phase 2 PH2, Phase 3 PH3, Phase 4 PH4, and Phase 5 PH5. This indicates that as the phases progress from Phase 1 to Phase 5 PH5, the relationship between the state of general employee Rx and the state of representative employee Fy approaches an ideal state.

[0111] In Phase 1, PH1, the pair of emotion EX#1 and value VA#1 correlates the state of the company organization (representative employee Fy) as "acceptance" with the state of the input person (general employee Rx) as "self-disclosure." This example means that when the company organization is in a state of "acceptance" of the input person, it can be inferred from the pair of emotion EX#1 and value VA#1 that the input person is in a state of "self-disclosure."

[0112] In Phase 2, PH2, the state of the company organization, "trust," and the state of the inputter, "self-affirmation," are associated through the pairing of emotion EX#2 and value VA#2. In this example, it can be inferred from the pairing of emotion EX#2 and value VA#2 that when the company organization "trusts" the inputter, the inputter is in a state of "self-affirmation."

[0113] In Phase 3, PH3, the combination of emotion EX#3 and values ​​VA#3 correlates the state of the company organization ("recognition") with the state of the inputter ("self-analysis"). In this example, it can be inferred from the combination of emotion EX#3 and values ​​VA#3 that when the company organization is in a state of "recognition" of the inputter, the inputter is in a state of "self-analysis."

[0114] In Phase 4, PH4, the combination of emotion EX#4 and values ​​VA#4 correlates the state of the company organization ("expectation") with the state of the inputter ("independence"). This example means that when the company organization has "expectations" of the inputter, the combination of emotion EX#4 and values ​​VA#4 suggests that the inputter is in a state of "independence."

[0115] In Phase 5, PH5, the combination of emotion EX#5 and values ​​VA#5 correlates the state of the company organization ("co-creation") with the state of the inputter ("autonomy and contribution"). This example means that when the company organization is in a state of "co-creation" with the inputter, the inputter is in a state of "autonomy and contribution," which can be inferred from the combination of emotion EX#3 and values ​​VA#3.

[0116] The acquisition unit 133 may acquire the ideal model MD by generating it based on emotions and values. For example, the acquisition unit 133 may generate the ideal model MD by estimation based on opinions OPx and values ​​VAx corresponding to the dialogue DLz patterns (patterns PT1 to PT6) detected in step S2.

[0117] On the other hand, the ideal model MD may be generated, for example, by human effort.

[0118] Next, step S4 will be explained. Step S4 may be performed when the dialogue DLz has been patterned in step S2 and the ideal model MD has been obtained in step S3. In step S4, the selection unit 134 selects recommended feedback that is recommended as a response from the viewer, and the provision unit 135 provides the selected recommended feedback to the viewer.

[0119] Figure 3 shows a scene in which a new dialogue DL5 is about to take place between a regular employee R15 (the person inputting the data) and a representative employee F25 (the person viewing the data).

[0120] For example, suppose employee R15 checks a set of questions via application AP to reflect on their work in company organization X1. In this case, employee R15 reflects on their work and inputs their self-assessment of that work into a designated screen within application AP. When a new dialogue DL5 is started due to the input of this new reflection, the selection unit 134 acquires reflection information RL15-5, which indicates the new reflection input by employee R15, and attribute information A15, which indicates employee R15's attribute.

[0121] As shown in Figure 3, the reflection information RL15-5 includes the following components: opinions OP15 from general employee R15, experiences EX15, emotions EM15, and values ​​VA15. Furthermore, the attributes A15 of general employee R15 may include, for example, the age, gender, hobbies, department, and position of general employee Rx.

[0122] In this state, in step S4, the selection unit 134 selects a recommended feedback that is recommended as a response by the representative employee F25, based on the reflection information RL15- indicating a new reflection, the ideal model MD, and the dialogue DLz patterns PT1 to PT6.

[0123] Step S4 will be explained in more detail by dividing it into steps S4-1 and S4-2. In step S4-1, the selection unit 134 identifies which phase (i.e., phase 1 PH1 to phase 5 PH5) the relationship between the state of general employee R15 and the state of representative employee F25 is in, based on the state transitions defined in the ideal model MD. In the following explanation, we will assume that the selection unit 134 has identified phase 3 PH3.

[0124] In step S4-2, the selection unit 134 selects recommended feedback that is recommended as a response from the target viewer, representative employee F25, to the target inputter, general employee R15, based on the third phase PH3 identified in step S4-1 and the dialogue DLz patterns PT1 to PT6. Specifically, the selection unit 134 identifies a pattern from the dialogue DLz patterns PT1 to PT6 that corresponds to the third phase PH3 and in which the set of emotion #3 and value #3 is treated as constituent items. The selection unit 134 then selects the identified pattern as recommended feedback. For example, the selection unit 134 may select the feedback comment shown in the identified pattern as recommended feedback.

[0125] For example, suppose the selection unit 134 selects a feedback comment CM(PT1) corresponding to pattern PT1, a feedback comment CM(PT2) corresponding to pattern PT2, and a feedback comment CM(PT3) corresponding to pattern PT3. In this case, the provision unit 135 provides the feedback comments CM(PT1), CM(PT2), and CM(PT3) to the representative employee F25 as recommended feedback.

[0126] For example, the providing unit 135 may provide feedback comments via the application AP while controlling the system to allow the user to select one of the following: feedback comment CM(PT1), feedback comment CM(PT2), or feedback comment CM(PT3).

[0127] Furthermore, the selection unit 134 may select the most optimal of the feedback comments CM(PT1), CM(PT2), and CM(PT3), and the providing unit 135 may respond with this optimal feedback comment on behalf of the representative employee F25. In other words, the information processing device 100 may dynamically provide feedback on behalf of the target viewer.

[0128] Here, according to the example in Figure 3, let's assume that Representative Employee F25 selects feedback comment CM(PT2) and inputs feedback information FB25-5 which includes the selected feedback comment CM(PT2). Note that the feedback information FB25-5 may also include attribute information indicating Representative Employee F25's attribute A25.

[0129] Furthermore, when representative employee F25 inputs feedback information FB25-5, general employee R15 evaluates the comment CM(PT2) contained in the feedback information FB25-5.

[0130] Thus, the series of dialogues DL5 may be terminated once the general employee R15 has made its evaluation. In this case, the collection unit 131 acquires the information exchanged between the general employee R15 and the representative employee F25 from the start to the end of the dialogue DL5. Specifically, the collection unit 131 acquires the set of attribute A15 and reflection information RL15-5 as information regarding the general employee R15's reflection, and the set of attribute A25 and feedback information FB25-5 as information regarding the representative employee F25's feedback. The collection unit 131 also acquires the evaluation EV15, which indicates the evaluation result by the general employee R15 (for example, "good" or "bad"). In this way, the collection unit 131 may also acquire the history information of newly performed dialogues DL5, and control the system so that the acquired history information is used for future pattern detection.

[0131] [5. Processing Procedure] Next, the information processing procedure according to the embodiment will be explained using Figure 5. Figure 5 is a flowchart of the information processing procedure according to the embodiment. In Figure 5, the example in Figure 3 will be used as appropriate to explain the flow of information processing.

[0132] First, the collection unit 131 collects history information of the dialogue DLz (step S501). For example, the collection unit 131 acquires history information of the dialogue DLz when a dialogue DLz is conducted between a general employee Rx and a representative employee Fy. The collection unit 131 then collects history information of the dialogue DLz by storing the acquired dialogue DLz history information in the history information database 121.

[0133] In the history information of a dialogue DLz, the dialogue ID that identifies a single dialogue DLz may manage the pair of attribute Ax and reflection information RLx of a general employee Rx, and the pair of attribute Ay and feedback information FBy of a representative employee Fy. In addition, the evaluation EVx of general employee Rx for the feedback comment CMy included in the feedback information FBy may also be managed by the dialogue ID.

[0134] Next, the detection unit 132 determines whether a sufficient amount of historical information of the dialogue DLz has been collected for the purpose of performing a detection process to detect the pattern of the dialogue DLz (step S502). For example, the detection unit 132 may perform this determination periodically, and if there is insufficient historical information of the dialogue DLz (step S502; No), it waits until a sufficient amount of historical information has been collected for the purpose of performing the detection process.

[0135] On the other hand, if a sufficient amount of historical information has been collected for the detection process (step S502; Yes), the detection unit 132 detects a pattern in the dialogue DLz based on the evaluation EVx by the general employee Rx and the historical information of the dialogue DLz (step S503). For example, the detection unit 132 extracts feedback information FBy, which includes the target comment CMy (target feedback) that has been given a good evaluation, and reflection information RLx, which is included in the dialogue DLz corresponding to this feedback information FBy, from the historical information of the dialogue DLz. The detection unit 132 then uses the extracted information as training data to learn the relationship between the attribute Ax of the general employee Rx and the attribute Ay of the representative employee Fy, and the relationship between information about constituent items (e.g., opinion OPx, experience EXx, emotion EMx, values ​​VAx, important keywords, or related keywords, etc.) and the target comment CMy. The detection unit 132 then detects a pattern in the dialogue DLz based on the learning results.

[0136] Next, the acquisition unit 133 acquires the ideal model MD generated based on the pattern of the interactive DLz (step S504).

[0137] In this state, the selection unit 134 determines whether or not a new reflection, which is a reflection for a new dialogue DLz, has been input (step S505). If the selection unit 134 determines that no new reflection has been input (step S505; No), it waits until a new reflection is input.

[0138] On the other hand, if the selection unit 134 determines that a new reflection has been input (step S505; Yes), it waits until a person who views the new reflection appears, and if the target viewer is detected by the appearance of a person who views the new reflection, it proceeds to step S506.

[0139] For example, the selection unit 134 selects a feedback comment that the target viewer should respond to in response to the new reflection, based on the reflection information RLx indicating the new reflection, the ideal model MD, and the pattern of the dialogue DLz (step S506).

[0140] Then, the providing unit 135 presents the feedback comments selected by the selection unit 134 as recommended feedback to the target viewer (step S507).

[0141] [6. Summary] Based on the above explanation, the information processing device 100 can optimize feedback so that viewers can provide appropriate feedback to the inputter's reflections. As a result, the inputter will be motivated to autonomously gain insights and take action, thereby gaining more experience and transforming that experience into learning. Furthermore, the organization to which the inputter belongs can develop its organization by using the inputter's learning as knowledge and applying that knowledge to its operations.

[0142] [7. Hardware Configuration] Next, an example of the hardware configuration of the information processing device 100 according to the embodiment will be described. Figure 6 is a block diagram showing an example of the hardware configuration of the information processing device 100 according to the embodiment. Referring to Figure 6, the information processing device 100 includes, for example, a processor 801, a ROM 802, a RAM 803, a host bus 804, a bridge 805, an external bus 806, an interface 807, an input device 808, an output device 809, a storage device 810, a drive 811, a connection port 812, and a communication device 813. Note that the hardware configuration shown here is just an example, and some of the components may be omitted. Furthermore, it may also include components other than those shown here.

[0143] (Processor 801) The processor 801 functions, for example, as an arithmetic processing unit or a control unit, and controls the overall operation or part of the operation of each component based on various programs recorded in the ROM 802, RAM 803, storage 810, or removable recording medium 901.

[0144] (ROM802, RAM803) ROM 802 is a means of storing programs loaded into the processor 801 and data used for calculations. RAM 803 temporarily or permanently stores, for example, programs loaded into the processor 801 and various parameters that change as needed when executing those programs.

[0145] (Host bus 804, bridge 805, external bus 806, interface 807) The processor 801, ROM 802, and RAM 803 are interconnected, for example, via a host bus 804 capable of high-speed data transmission. On the other hand, the host bus 804 is connected to an external bus 806, which has a relatively low data transmission speed, via a bridge 805. The external bus 806 is also connected to various components via an interface 807.

[0146] (Input device 808) Input devices 808 may include, for example, a mouse, keyboard, touch panel, buttons, switches, and levers. Furthermore, a remote controller (hereinafter referred to as a remote control) capable of transmitting control signals using infrared or other radio waves may also be used as an input device 808. Additionally, input devices 808 may include audio input devices such as microphones.

[0147] (Output device 809) The output device 809 is a device capable of visually or audibly notifying the user of acquired information, such as a display device like a CRT (Cathode Ray Tube), LCD, or organic EL; an audio output device like a speaker or headphones; a printer, a mobile phone, or a facsimile. Furthermore, the output device 809 according to this embodiment includes various vibration devices capable of outputting tactile stimuli.

[0148] (Storage 810) Storage 810 is a device for storing various types of data. Examples of storage devices that can be used for storage 810 include magnetic storage devices such as hard disk drives (HDDs), semiconductor storage devices, optical storage devices, or magneto-optical storage devices.

[0149] (Drive 811) The drive 811 is a device that reads information recorded on a removable recording medium 901, such as a magnetic disk, optical disk, magneto-optical disk, or semiconductor memory, or writes information to the removable recording medium 901.

[0150] (Connection port 812) Connection port 812 is a port for connecting external devices 902, such as a USB (Universal Serial Bus) port, IEEE1394 port, SCSI (Small Computer System Interface), RS-232C port, or optical audio terminal.

[0151] (Communication device 813) The communication device 813 is a communication device for connecting to a network, and may include, for example, a communication card for wired or wireless LAN, Bluetooth®, or WUSB (Wireless USB), a router for optical communication, a router for ADSL (Asymmetric Digital Subscriber Line), or a modem for various types of communication.

[0152] (Removable recording medium 901) The removable recording medium 901 may be, for example, DVD media, Blu-ray® media, HD DVD media, or various semiconductor storage media. Of course, the removable recording medium 901 may also be, for example, an IC card equipped with a contactless IC chip, or an electronic device.

[0153] (External connection device 902) External connected devices 902 include, for example, a printer, a portable music player, a digital camera, a digital video camera, or an IC recorder.

[0154] In this embodiment, the storage unit 120 is implemented by ROM 802, RAM 803, and storage 810. Furthermore, the control unit 130 implemented by the processor 801 reads and executes control programs (for example, information processing programs according to this embodiment) that implement the collection unit 131, detection unit 132, acquisition unit 133, selection unit 134, and provision unit 135 from ROM 802, RAM 803, etc.

[0155] [8. Other] Of the processes described above as being performed automatically, all or part of them may be performed manually. Furthermore, all or part of the processes described as being performed manually may be performed automatically using known methods. In addition, the processing procedures, specific names, and various data and parameters shown in the above documents and drawings may be changed at will unless otherwise specified. For example, the various information shown in each drawing is not limited to the information illustrated.

[0156] Furthermore, each component of the illustrated device is a functional concept and does not necessarily have to be physically configured as shown. In other words, the specific forms of distribution and integration of each device are not limited to those shown. Moreover, each component may be configured by functionally or physically distributing and integrating all or part of it in any unit, depending on various loads and usage conditions. In addition, the processes described above may be combined and executed as appropriate, within a non-contradictory range.

[0157] Although embodiments of the present application have been described in detail above with reference to several drawings, these are illustrative examples, and the present invention can be implemented in various other forms with modifications and improvements based on the knowledge of those skilled in the art, starting with the embodiments described in the disclosure section of the invention. [Explanation of Symbols]

[0158] 1. Information Processing System 10 Input device 20 Viewer device 100 Information Processing Devices 120 Storage section 121 History Information Database 122 Dialogue Pattern Database 130 Control Unit 131 Collection Department 132 Detection unit 133 Acquisition Department 134 Selection Section 135 Provision Department

Claims

1. An information processing device that supports dialogue between an inputter who inputs reflection information showing a reflection on an activity and a viewer who views the said reflection, A collection unit that collects dialogue history information including the reflection information and feedback information indicating the feedback entered by the viewer in response to the reflection, A detection unit detects a dialogue pattern based on the evaluation result evaluated by the inputter and the history information, When a new reflection is input, a selection unit selects a recommended feedback that is recommended as a response by the viewer who viewed the new reflection, based on the newly input reflection and the dialogue pattern detected by the detection unit. It has, The aforementioned reflection is the act of the inputter reflecting on the aforementioned activity that has already been performed. An information processing device characterized by the following:

2. An information processing device that supports dialogue between an inputter who inputs reflection information showing a reflection on an activity and a viewer who views the reflection, A collection unit collects dialogue history information, which includes, as reflection information indicating the aforementioned reflection, information on the results of reflection by the input person who performed the activity, according to items prepared to allow the user to reflect on the activity, and feedback information indicating the feedback entered by the viewer regarding the reflection. A detection unit detects a dialogue pattern based on the evaluation result evaluated by the inputter and the history information, An acquisition unit that acquires an ideal model in which a state transition is defined that represents an ideal change in the state of the inputter, which is estimated from the items corresponding to the dialogue pattern, When a new reflection is input, a selection unit selects a recommended feedback that is recommended as a response by the viewer who viewed the new reflection, based on the newly input reflection, the dialogue pattern detected by the detection unit, and the ideal model. An information processing device characterized by having the following features.

3. The components constituting the reflection include the inputter's opinion on a predetermined question, the inputter's experience that forms the basis of the opinion, the inputter's feelings arising from the experience, and the inputter's values ​​that form the basis of the feelings, The aforementioned reflection information is information resulting from the reflection by the inputter, who is the person who performed the activity, according to the aforementioned configuration items. The feedback information includes text information indicating the content of the feedback and information indicating the type of the content of the feedback. The information processing apparatus according to claim 1 or 2.

4. The detection unit uses a set of feedback information, specifically feedback information indicating a target feedback to which a predetermined evaluation result has been given, and reflection information indicating a reflection corresponding to the target feedback, as training data. Based on the learning results, which have been learned regarding the relationship between the information about the component items and the feedback information indicating the target feedback, the detection unit detects the dialogue pattern. The information processing apparatus according to claim 3.

5. The detection unit detects the dialogue pattern according to the relationship based on the attributes of the inputter and the attributes of the viewer. The information processing apparatus according to feature 4.

6. The system further includes an acquisition unit that acquires an ideal model in which a state transition is defined, which is a state transition estimated from the component items corresponding to the dialogue pattern, and which shows an ideal change in the state of the inputter. The selection unit selects the recommended feedback based on the reflection information indicating the new reflection, the ideal model, and the dialogue pattern. The information processing apparatus according to any one of claims 3 to 5.

7. The acquisition unit acquires an ideal model that represents an ideal state transition estimated from the emotion and values ​​among the constituent items, wherein the pair of emotion and values ​​is classified stepwise according to the relationship between the state of the inputter and the state of the viewer. The selection unit, by comparing the reflection information indicating the new reflection with the ideal model, identifies which stage of the state transition in the ideal model the relationship between the state of the target inputter who input the new reflection and the state of the target viewer who views the new reflection represents. Based on the identified stage and the dialogue pattern, it selects a recommended feedback as the recommended response from the target viewer. The information processing apparatus according to feature 6.

8. The selection unit selects, from among the dialogue patterns, a set that corresponds to the identified stage and includes the set of emotion and value as constituent items, as the recommended feedback. The information processing apparatus according to feature 7.

9. The collection unit associates the reflection information entered by the inputter with the feedback information entered by the viewer in response to the reflection information as a single dialogue history, and collects the history information each time the dialogue takes place. The information processing apparatus according to claim 1 or 2.

10. An information processing method executed by an information processing device that supports dialogue between an inputter who inputs reflection information showing a reflection on an activity and a viewer who views the said reflection, A collection step of collecting dialogue history information including the reflection information and feedback information indicating the feedback entered by the viewer in response to the reflection, A detection step in which the feedback is evaluated by the inputter and the historical information is used to detect a dialogue pattern. When a new reflection is input, a selection step is performed to select a recommended feedback that is recommended as a response by the viewer who viewed the new reflection, based on the newly input reflection and the dialogue pattern detected by the detection step. Includes, The aforementioned reflection is the act of the inputter reflecting on the aforementioned activity that has already been performed. An information processing method characterized by the following:

11. An information processing method performed by an information processing device that supports a dialogue between an inputter who inputs reflection information indicating a reflection on an activity and a viewer who views the reflection, A collection step of collecting dialogue history information, which includes, as reflection information indicating the reflection, information of the results of the reflection by the input person who performed the activity, according to items prepared to allow the user to reflect on the activity, and feedback information indicating the feedback entered by the viewer in response to the reflection. A detection step in which the feedback is evaluated by the inputter and the historical information is used to detect a dialogue pattern. An acquisition step to acquire an ideal model in which a state transition is defined, which is a state transition estimated from the items corresponding to the dialogue pattern, and which shows an ideal change in the state of the inputter; When a new reflection is input, a selection step is performed to select a recommended feedback that is recommended as a response by the viewer who viewed the new reflection, based on the newly input reflection, the dialogue pattern detected by the detection step, and the ideal model. An information processing method characterized by including

12. An information processing program executed by an information processing device that supports dialogue between an inputter who inputs reflection information showing a reflection on an activity and a viewer who views the said reflection, A collection procedure for collecting dialogue history information, which includes the reflection information and feedback information indicating the feedback entered by the viewer in response to the reflection. A detection procedure for detecting a dialogue pattern based on the evaluation result of the feedback evaluated by the inputter and the historical information, A selection procedure that, when a new reflection is entered, selects a recommended feedback that is recommended as a response by a viewer who has viewed the new reflection, based on the newly entered reflection and the dialogue pattern detected by the detection procedure. The information processing device is made to execute this, The aforementioned reflection is the act of the inputter reflecting on the aforementioned activity that has already been performed. Information processing program.

13. An information processing program executed by an information processing device that supports a dialogue between an inputter who inputs reflection information indicating a reflection on an activity and a viewer who views the reflection, A collection procedure for collecting dialogue history information, which includes, as reflection information indicating the reflection, information on the results of the reflection by the input person who performed the activity, according to items prepared to allow the user to reflect on the activity, and feedback information indicating the feedback entered by the viewer in response to the reflection. A detection procedure for detecting a dialogue pattern based on the evaluation result of the feedback evaluated by the inputter and the historical information, An acquisition procedure for obtaining an ideal model in which a state transition is defined, which is a state transition estimated from the items corresponding to the dialogue pattern, and which shows an ideal change in the state of the inputter; A selection procedure that, when a new reflection is input, selects a recommended feedback that is recommended as a response by a viewer who has viewed the new reflection, based on the newly input reflection, the dialogue pattern detected by the detection procedure, and the ideal model. An information processing program that causes an information processing device to execute.

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