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

Abstract

The system can recommend the customer service staff that the user of the online customer service service desires. [Solution] The information processing device includes: a reception unit that receives perspective information from a user indicating the criteria for matching a user with a customer service staff member desired by the user of an online customer service service, which is a service in which a user receives customer service from customer service staff online; an acquisition unit that acquires customer service staff information about the customer service staff member; a calculation unit that calculates a matching degree indicating the degree of matching based on the perspective information and the customer service staff information; and a provision unit that recommends customer service staff members whose matching degree exceeds a predetermined threshold to the user.

Description

Technical Field

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

Background Art

[0002] In recent years, technologies related to online customer service, which is a service where users receive customer service from customer service staff online, are known. For example, a technology where a pharmacist provides online customer service to those who wish to purchase prescribed medicines is known.

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 prior art, it is not always possible to recommend to the user the customer service staff desired by the user of the online customer service.

[0005] Therefore, an object of the present disclosure is to recommend to the user the customer service staff desired by the user of the online customer service.

Means for Solving the Problems

[0006] The information processing apparatus according to this embodiment includes: a reception unit that receives from a user perspective information indicating the criteria for matching the user with the customer service staff desired by the user in an online customer service service, which is a service in which the user receives customer service from customer service staff online; an acquisition unit that acquires customer service staff information relating to the customer service staff; a calculation unit that calculates a matching degree indicating the degree of matching based on the perspective information and the customer service staff information; and a provision unit that recommends to the user customer service staff whose matching degree exceeds a predetermined threshold. [Effects of the Invention]

[0007] According to the present invention, it is possible to recommend a customer service staff member to a user of an online customer service service who has a preference for that staff member. [Brief explanation of the drawing]

[0008] [Figure 1] Figure 1 shows an example of the configuration 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 shows an example of the results screen for the fashion style diagnosis. [Figure 4] Figure 4 shows an example of the profile screen. [Figure 5] Figure 5 shows an example of matching criteria added by a user. [Figure 6] Figure 6 shows an example of the profile screen after the user matching perspective has been added. [Figure 7] Figure 7 shows an example of matching criteria added by a user. [Figure 8] Figure 8 illustrates an example of the customer service staff profile recommended to users. [Figure 9] Figure 9 illustrates an example of the customer service staff profile recommended to users. [Figure 10] Figure 10 illustrates an example of the customer service staff profile recommended to users. [Figure 11] Figure 11 shows an example of a list screen for customer service staff. [Figure 12] Figure 12 shows an example of a detailed screen for customer service staff. [Figure 13] Figure 13 is a hardware configuration diagram showing an example of a computer that implements the functions of the information processing device according to the embodiment. [Modes for carrying out the invention]

[0009] The following describes in detail, with reference to the drawings, embodiments for implementing the information processing device, information processing method, and information processing program according to the present application (hereinafter referred to as "embodiments"). Note that these embodiments do not limit the information processing device, information processing method, and information processing program according to the present application. Furthermore, the same parts are denoted by the same reference numerals in each of the following embodiments, and redundant descriptions are omitted.

[0010] The one or more embodiments (including examples, modifications, and applications) described below can each be implemented independently. On the other hand, at least some of the embodiments described below may be implemented in appropriate combination with at least some of the other embodiments. These embodiments may contain novel features that differ from each other. Therefore, these embodiments may contribute to solving different objectives or problems and may produce different effects.

[0011] (Embodiment) [1. Introduction] [1.1. Overall Overview] Conventionally, when users of online customer service enjoy the recommendations of customer service staff, the perspective of matching between the customer service staff and the users has been limited to the perspective provided by the online customer service side. Also, the direction in which the matching perspective affects the recommendation results has been one-way, that is, it only gets stronger, and it has not been able to meet the needs of users who want to deliberately weaken or temporarily weaken the reflection of the matching perspective in the recommendation results.

[0012] In contrast, the information processing apparatus according to the embodiment enables, for example, in the scenario of online shopping for fashion items, the user himself / herself to freely create the perspective of matching between the customer service staff and the user when enjoying the recommendations of the customer service staff. Also, it provides a mechanism that allows the user himself / herself to control the direction and degree to which these matching perspectives affect the recommendation results.

[0013] As a result, since the information processing apparatus allows the user to freely add matching perspectives, it enables the user to encounter an ideal customer service staff who is highly likely to solve the user's personal needs and concerns. Also, by allowing the user to change the direction and degree to which the matching perspective affects the recommendation results, the information processing apparatus enables, for example, the user to be served by a staff member who is proficient in a style different from the user's usual fashion style.

[0014] 〔1.2. Overview of Matching〕 First, the information processing device causes both the user and the customer service staff to perform a diagnosis (for example, a fashion style diagnosis), and generates a diagnosis result (for example, a graph representing a ratio (see Figure 3)). Also, the information processing device calculates the matching degree between the user and the customer service staff from the perspective of matching based on the diagnosis result. Further, the information processing device recommends a customer service staff to the user based on the matching degree (for example, displays them ranked on a customer service staff list screen). In addition, the information processing device provides a function for the user to freely add (for example, add a graph representing a ratio (see Figure 5) such as "Hokkaido: 80%, Okinawa: 20%"), delete, turn on or off the perspective of matching. Moreover, the information processing device provides a function to adjust the direction and degree to which the user affects the recommendation result from the perspective of matching (for example, set to 75% in the positive direction (= 25% in the negative direction) (see Figure 4)).

[0015] [2. Configuration of the information processing system] FIG. 1 is a diagram showing a configuration example of an information processing system 1 according to an embodiment. As shown in FIG. 1, the information processing system 1 according to the embodiment includes a user terminal 10 and an information processing device 100. The user terminal 10 and the information processing device 100 are communicably connected by wire or wirelessly via a predetermined communication network (network N).

[0016] The user terminal 10 is an information processing device used by a user of an online customer service, which is a service in which the user receives customer service from the customer service staff online. For example, the user terminal 10 is an information processing device such as a desktop PC (Personal Computer) or a notebook PC. Also, the user terminal 10 may be a smart device such as a smartphone or a tablet. Further, the user terminal 10 displays the information received from the information processing device 100 or the like on a web browser or an application.

[0017] Furthermore, the user terminal 10 accepts information input from the user in response to the user's actions. When the user terminal 10 accepts information input, it transmits the input information to the information processing device 100 in response to the user's actions.

[0018] The information processing device 100 is an information processing device that performs information processing according to the embodiment. The information processing device 100 is implemented by a server device, a cloud system, or the like. For example, the information processing device 100 may perform information processing according to the embodiment in accordance with the information processing method implemented by the information processing program according to the embodiment.

[0019] [3. Configuration of the Information Processing Device] Figure 2 shows an example of the configuration of an information processing device 100 according to the embodiment. The information processing device 100 according to the embodiment includes a communication unit 110, a storage unit 120, and a control unit 130.

[0020] (Communications Department 110) The communication unit 110 is connected to the network N by wire or wireless connection and transmits and receives information with the user terminal 10. For example, the communication unit 110 can be implemented using a NIC (Network Interface Card) or an antenna.

[0021] (Storage 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. For example, the storage unit 120 stores an information processing program according to the embodiment. The storage unit 120 also has a user information storage unit 121 and a customer service staff information storage unit 122.

[0022] (User information storage unit 121) The user information storage unit 121 stores various information about users of the online customer service. For example, the user information storage unit 121 stores user identification information that identifies the user and information about the user in association. Information about the user includes, for example, perspective information that indicates the criteria for matching the customer service staff with the user, as received from the user.

[0023] (Customer service staff information memory unit 122) The customer service staff information storage unit 122 stores various information about the customer service staff of the online customer service service. For example, it stores customer service staff identification information, which identifies the customer service staff, in association with information about the customer service staff. Information about the customer service staff includes, for example, the customer service staff's self-introduction.

[0024] (Control unit 130) The control unit 130 is a controller, and is realized, for example, by executing various programs stored in the memory device inside the information processing device 100 using RAM as the working area, using a CPU (Central Processing Unit) or MPU (Micro Processing Unit), etc. Alternatively, the control unit 130 is a controller and can be realized, for example, by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or FPGA (Field Programmable Gate Array).

[0025] The control unit 130 has a reception unit 131, an acquisition unit 132, a calculation unit 133, and a provision unit 134 as functional units, and may realize or execute the information processing 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 acceptable as long as they perform the information processing described later. Furthermore, each functional unit represents the function of the control unit 130 and does not necessarily have to be physically separated.

[0026] (Reception desk 131) The reception unit 131 has both the user and the customer service staff perform a diagnosis and generates the diagnosis results. For example, the reception unit 131 has the user perform a fashion style diagnosis to assess the match between the user's "likes" and the customer service staff's "strengths" regarding fashion, and generates the diagnosis results. Alternatively, the reception unit 131 may have the user perform a communication style diagnosis to assess the match between the user's "preferences" and the customer service staff's "strengths" regarding customer service approaches, and generates the diagnosis results. For example, the reception unit 131 provides information related to the diagnosis to the terminal devices of both the user and the customer service staff, and receives the information entered by each of them. The reception unit 131 also generates the diagnosis results based on the information entered by each of the user and the customer service staff.

[0027] Figure 3 shows an example of the screen displaying the results of a fashion style diagnosis. The reception unit 131 generates content C1, as shown in Figure 3, as the diagnosis result, and provides content C1 to the user (or customer service staff). Specifically, the reception unit 131 transmits content C1 to the user terminal 10. For example, the reception unit 131 generates content C1 that includes the text ST1 "Simple in a sense" which indicates the diagnosis result of the fashion style diagnosis. The style of the diagnosis result (for example, "Simple in a sense") is composed of multiple styles (for example, "Simple," "Clean," and "Natural," etc.). The reception unit 131 generates content that includes a pie chart G1 which displays the correspondence between strings indicating each of the multiple styles that make up the style of the diagnosis result and percentage information indicating the proportion of each of the multiple styles. In Figure 3, the reception unit 131 generates a pie chart G1 that displays percentage information R11 showing that the proportion of the string T11 representing the style "simple" is 55%, percentage information R12 showing that the proportion of the string T12 representing the style "neat" is 25%, and percentage information R13 showing that the proportion of the string 13 representing the style "natural" is 20%. The reception unit 131 also generates content C1 which includes the pie chart G1. When the reception unit 131 generates a diagnosis result for a user, it stores the user identification information and the information related to the diagnosis result in the user information storage unit 121. When the reception unit 131 generates a diagnosis result for a customer service staff member, it stores the customer service staff identification information and the information related to the diagnosis result in the customer service staff information storage unit 122.

[0028] (Acquisition part 132) The acquisition unit 132 acquires customer service staff information. For example, the acquisition unit 132 acquires customer service staff information by referring to the customer service staff information storage unit 122.

[0029] (Calculation section 133) The calculation unit 133 calculates a matching degree, which indicates the degree of matching between the customer service staff and the user, based on the user's diagnostic results and the customer service staff's diagnostic results. For example, the calculation unit 133 converts each of the pie chart information included in the user's diagnostic results and the pie chart information included in the customer service staff's diagnostic results into vectors. For example, the calculation unit 133 converts each of the multiple strings included in the pie chart into a vector using known natural language processing techniques. Subsequently, the calculation unit 133 generates multiple weighted vectors by weighting the vectors corresponding to each of the multiple strings according to the proportion each of the multiple strings occupies. Subsequently, the calculation unit 133 sums the multiple weighted vectors to generate an integrated vector. Subsequently, the calculation unit 133 calculates the similarity between the user's pie chart vector and the customer service staff's pie chart vector as the matching degree. For example, the calculation unit 133 may calculate the cosine similarity or Euclidean distance between the user's vector representation and the customer service staff's vector as the matching degree.

[0030] Figure 4 shows an example of a profile screen. The reception unit 131 generates a slider bar SB1 that displays the degree to which the recommendation results recommended by the provision unit 134 reflect the degree of matching, based on the position of the slider SL1, and provides the slider bar SB1 to the user. For example, the reception unit 131 generates content C2 which includes content C21 which includes slider bar SB1, and sends the generated content C2 to the user terminal 10. Here, content C2 is the content corresponding to the profile screen. Here, the user can choose whether to be served by a sales staff member who suggests a style that suits their own style, or a sales staff member who suggests a new style. The reception unit 131 generates content C2, which includes content C21 containing a slider bar SB1. The positive direction of the slider bar SB1 (right in Figure 6) represents the "My Style Emphasis" mode, where the user desires a sales staff member who suggests a style that suits their own style, and the negative direction of the slider bar SB1 (left in Figure 6) represents the "New Style Challenge" mode, where the user desires a sales staff member who suggests a new style. The user terminal 10 displays content C2 on its screen. The user terminal 10 receives an operation from the user to change the position of the slider SL1 displayed on the screen. When the user terminal 10 receives an operation to change the position of the slider SL1, it transmits information indicating the position of the slider SL1 changed by the user to the information processing device 100. In this way, the reception unit 131 receives degree information from the user that indicates the degree to which the recommendation results recommended by the provision unit 134 reflect the degree of matching. For example, the reception unit 131 receives information indicating the position of the slider SL1 as degree information.

[0031] Furthermore, the reception unit 131 generates a slider bar SB2 that displays the weight of the diagnostic results as described in Figure 3, based on the position of the slider SL2, and provides the slider bar SB2 to the user. For example, the reception unit 131 generates content C2, which includes content C22 containing the pie chart G1 and slider bar SB2 as described in Figure 3, and transmits the generated content C2 to the user terminal 10. The user terminal 10 displays content C2 on its screen. The user terminal 10 receives an operation from the user to change the position of the slider SL2 displayed on the screen. When the user terminal 10 receives an operation to change the position of the slider SL2, it transmits information indicating the position of the slider SL2 changed by the user to the information processing device 100. In this way, the reception unit 131 receives diagnostic result weight information from the user, which indicates the weight of the diagnostic results. For example, the reception unit 131 receives information indicating the position of the slider SL2 as diagnostic result weight information.

[0032] Furthermore, the reception unit 131 receives perspective information from users that indicates the criteria for matching users with customer service staff they desire, in addition to the online customer service service where users receive customer service from customer service staff online. Specifically, the reception unit 131 accepts strings as perspective information. Figure 5 shows an example of matching criteria added by a user. In Figure 5, the reception unit 131 accepts the string "Hokkaido" T21 and the string "Okinawa" T22 as perspective information. In this way, the reception unit 131 accepts combinations of words or phrases of the same category as perspective information. For example, in addition to the combination of place names "Hokkaido" and "Okinawa," the reception unit 131 may also accept combinations of words such as "indoor" and "outdoor" as perspective information. The reception unit 131 also accepts multiple strings and percentage information indicating the proportion that each of the multiple strings occupies within the multiple strings as perspective information. In Figure 5, the reception unit 131 receives the strings "Hokkaido" T21 and "Okinawa" T22 as viewpoint information, as well as percentage information R21 indicating that the proportion of the string "Hokkaido" T21 is 80% and percentage information R22 indicating that the proportion of the string "Okinawa" T22 is 20%. The reception unit 131 also generates a pie chart G2 that displays the percentage information R21 indicating that the proportion of the string "Hokkaido" T21 is 80% and the percentage information R22 indicating that the proportion of the string "Okinawa" T22 is 20%. The reception unit 131 also generates content C23 that includes the pie chart G2. In this way, the reception unit 131 generates content including a graph that displays the correspondence between multiple strings and percentage information, and provides the content including the graph to the user. If the reception unit 131 receives only one string from the user, it generates a pie chart that displays percentage information indicating that the proportion of the received string is 100%.

[0033] Furthermore, instead of accepting text entered by the user as perspective information, the reception unit 131 may accept text selected by the user from a list of input candidates presented to the user in advance. Also, the reception unit 131 may accept perspective information in the form of voice input by the user or input through dialogue between the chatbot and the user.

[0034] Furthermore, the reception unit 131 generates a slider bar SB3 that displays the weight of the viewpoint information described in Figure 5 according to the position of the slider SL3, and provides the slider bar SB3 to the user. In this way, the reception unit 131 generates a slider bar that displays the weight of the viewpoint information according to the position of the slider, and provides the slider bar to the user. For example, the reception unit 131 generates content C2' (see Figure 6) which includes content C23 containing a pie chart G2 and slider bar SB3, and transmits the generated content C2' to the user terminal 10. Figure 6 is a diagram showing an example of the profile screen after a matching viewpoint has been added by the user. Content C2' is the content that corresponds to the profile screen after a matching viewpoint has been added by the user. As shown in Figure 6, when a new matching viewpoint is added by the user, content corresponding to the new matching viewpoint is added to the profile screen. The user terminal 10 displays content C2' on the screen. The user terminal 10 accepts an operation from the user to change the position of the slider SL3 displayed on the screen. When the user terminal 10 receives an operation to change the position of slider SL3, it transmits information indicating the position of slider SL3 changed by the user to the information processing device 100. In this way, the reception unit 131 receives viewpoint weight information from the user, which indicates the weight of viewpoint information. For example, the reception unit 131 receives information indicating the position of slider SL3 as viewpoint weight information. In this way, the reception unit 131 receives weight information indicating the weight of viewpoint information. The reception unit 131 may generate content C23, which includes a button B1 for deleting viewpoint information, by selecting a button.

[0035] The calculation unit 133 calculates a matching degree, which indicates the degree of matching, based on the viewpoint information and the customer service staff information. Specifically, the calculation unit 133 converts the pie chart corresponding to the viewpoint information into a vector. More specifically, the calculation unit 133 uses known natural language processing techniques to convert each of the multiple strings received as viewpoint information into a vector. Subsequently, the calculation unit 133 generates multiple weighted vectors by weighting each vector corresponding to each of the multiple strings according to the proportion each of the multiple strings occupies. Subsequently, the calculation unit 133 sums the multiple weighted vectors to generate a first integrated vector.

[0036] Furthermore, the acquisition unit 132 refers to the customer service staff information storage unit 122 to acquire the string displayed on the customer service staff details screen. The string displayed on the customer service staff details screen is, for example, a self-introduction of the customer service staff or a problem that the customer service staff is confident they can solve, freely written in text format. The string displayed on the customer service staff details screen may be the text that the customer service staff registered as their profile. Furthermore, the calculation unit 133 vectorizes the string acquired by the acquisition unit 132 using known natural language processing techniques. For example, the calculation unit 133 inputs the string acquired by the acquisition unit 132 into a text embedding model such as BERT to vectorize the string acquired by the acquisition unit 132. For example, if the string acquired by the acquisition unit 132 is a sentence, the calculation unit 133 converts the words and phrases extracted from the sentence into multiple vectors that take into account the surrounding context. Subsequently, the calculation unit 133 sums the multiple vectors to generate a second integrated vector. The second integrated vector represents the meaning of the entire text displayed on the customer service staff details screen. Furthermore, the calculation unit 133 only needs to generate an integrated vector that represents the meaning of the entire text displayed on the customer service staff details screen, and the means for generating the integrated vector are not limited to any particular method.

[0037] Furthermore, the calculation unit 133 calculates the degree of similarity between the first unified vector and the second unified vector as the degree of matching. For example, the calculation unit 133 may calculate the cosine similarity or Euclidean distance between the first unified vector and the second unified vector as the degree of matching.

[0038] Furthermore, the reception unit 131 generates content that is displayed in a predetermined direction according to the order in which the multiple viewpoint information was input, and provides the content to the user. In Figure 6, the reception unit 131 generates content C2' in which content C22 related to the diagnostic results and content C23 related to viewpoint information added by the user are displayed vertically. When the reception unit 131 generates content C2', it provides content C2' to the user terminal 10. The user terminal 10 displays content C2' on its screen. The user can change the order of the viewpoint information by performing predetermined operations on the content C2' displayed on the screen. The calculation unit 133 calculates the degree of matching based on the weights corresponding to the order of the multiple viewpoint information. Specifically, the calculation unit 133 multiplies the weight for each viewpoint received from the user by a correction value (an example of a weight) corresponding to the order of the multiple viewpoint information. For example, when multiple viewpoint information is arranged vertically, the calculation unit 133 determines that the correction value corresponding to the viewpoint information displayed at the top is "1.0", the correction value corresponding to the viewpoint information displayed second from the top is "0.8", the correction value corresponding to the viewpoint information displayed third from the top is "0.6", and so on. In this way, when multiple viewpoint information is arranged vertically, the calculation unit 133 determines the correction values ​​so that the correction value of the viewpoint information displayed higher up becomes larger. For example, in Figure 6, suppose the diagnostic result weight information contained in content C22 is "1.0" and the viewpoint weight information contained in content C23 is "1.0". In this case, the calculation unit 133 multiplies the diagnostic result weight information "1.0" by the correction value "1.0" corresponding to the viewpoint information displayed at the top to calculate the corrected diagnostic result weight as "1.0". Furthermore, the calculation unit 133 multiplies the viewpoint weight information, "1.0," by the correction value "0.8," which corresponds to the viewpoint information displayed second from the top, to calculate the weight of the corrected viewpoint information as "0.8."

[0039] Furthermore, the calculation unit 133 converts each of the multiple viewpoint information into a vector. For example, the calculation unit 133 converts the pie chart corresponding to each of the multiple viewpoint information into a vector (hereinafter sometimes referred to as "viewpoint vector"). The calculation unit 133 also generates a weighted viewpoint vector by weighting the viewpoint vector with the corrected weights. The calculation unit 133 then generates a first unified vector by summing the multiple weighted viewpoint vectors. The calculation unit 133 also calculates the degree of similarity between the first unified vector and the second unified vector as the degree of matching. In this way, the calculation unit 133 calculates the degree of matching based on the weights of the viewpoint information.

[0040] Users can have their mood for the day (their emotions and psychological state on that day) reflected in the recommendation results. For example, the reception unit 131 receives the user's responses to a multiple-choice questionnaire about their mood for the day from the user terminal 10 as information about their mood for the day. The reception unit 131 also converts the information about their mood for the day received from the user into emotion tags and their scores. For example, the reception unit 131 pre-defines emotion tags and their scores and uses them to convert the information about their mood for the day received from the user into emotion tags and their scores. For example, emotion tags and their scores are pre-defined for each option in the multiple-choice questionnaire about their mood for the day (for example, if "A" is selected in question 1, "Cheerful" (an example emotion tag) will be increased by "30" (an example score). Emotion tags and their scores are entered according to the user's answers (for example, the total score for "Cheerful" is "140", the total score for "Regret" is "385", etc.). The reception unit 131 receives the emotion tags and their total scores from the user terminal 10. The reception unit 131 generates a pie chart showing matching perspectives based on emotion tags and their scores. Figure 7 shows an example of matching perspectives added by the user. In Figure 7, the reception unit 131 generates a pie chart G3 that displays percentage information R31 showing that the percentage of emotion tag T31 "regret" is 55%, percentage information R32 showing that the percentage of emotion tag T32 "calm" is 25%, and percentage information R33 showing that the percentage of emotion tag T33 "cheerful" is 20%. The reception unit 131 also generates content C24 that includes pie chart G3.

[0041] Furthermore, the reception unit 131 may receive conversation logs between the chatbot, which uses a generative AI, and the user from the user terminal 10 as information about the user's mood today. The reception unit 131 identifies the conversation content from the conversation logs between the chatbot and the user using known natural language processing techniques. The reception unit 131 also estimates the user's emotions from the conversation content. For example, the reception unit 131 uses a pre-trained emotion analysis model to estimate emotion tags and their scores corresponding to the user's emotions from the conversation content. The reception unit 131 also generates a pie chart showing matching perspectives based on the emotion tags and their scores estimated by the emotion analysis model.

[0042] (Provider 134) The provision unit 134 recommends customer service staff whose matching degree exceeds a predetermined threshold to the user. The provision unit 134 recommends a layer of customer service staff to the user according to the degree information. The provision unit 134 does not recommend customer service staff whose matching degree is below the threshold (they are always excluded). Figures 8 to 10 are diagrams illustrating an example of the layer of customer service staff recommended to the user. In Figure 8, the user sets the position of slider SL1 to the far right end of slider bar SB1 (the maximum in "Prioritize My Style" mode). In other words, the user sets the degree information to the highest degree. At this time, the provision unit 134 recommends a layer of customer service staff with a high matching degree calculated by the calculation unit 133 to the user. In Figure 9, the user sets the position of slider SL1 to the middle of slider bar SB1 (between "Prioritize My Style" mode and "Challenge a New Style" mode). At this time, the provision unit 134 recommends to the user a group of customer service staff whose matching score calculated by the calculation unit 133 is midway between 100 and the matching score threshold. In Figure 10, the user sets the position of slider SL1 to the left end of slider bar SB1 (the minimum position in "My Style Emphasis" mode). At this time, the provision unit 134 recommends to the user a group of customer service staff whose matching score calculated by the calculation unit 133 is between the matching score threshold and lower.

[0043] Figure 11 shows an example of a customer service staff list screen. The provisioning unit 134 generates content C3 corresponding to the list screen of recommended customer service staff. The provisioning unit 134 provides the generated content C3 to the user. In Figure 11, partial content C31 corresponding to a given customer service staff member is selected from the list screen. Figure 12 shows an example of a customer service staff details screen. The provisioning unit 134 generates content C4 that displays the details of the customer service staff member selected from the customer service staff list screen. The provisioning unit 134 provides the generated content C4 to the user. For example, the provisioning unit 134 generates content C4 that includes the customer service staff member's image G41, the customer service staff member's nickname, text T41 indicating age and gender, keywords T42 registered by the customer service staff member, and the customer service staff member's self-introduction T43.

[0044] [4. Effects] As described above, the information processing device 100 according to the embodiment comprises a reception unit 131, an acquisition unit 132, a calculation unit 133, and a provision unit 134. The reception unit 131 receives perspective information from a user, which indicates the criteria for matching the user with the customer service staff desired by the user of an online customer service service, a service in which the user receives customer service from customer service staff online. The acquisition unit 132 acquires customer service staff information about the customer service staff. The calculation unit 133 calculates a matching degree, which indicates the degree of matching, based on the perspective information and the customer service staff information. The provision unit 134 recommends customer service staff whose matching degree exceeds a predetermined threshold to the user.

[0045] As a result, the information processing device 100 can recommend customer service staff to users of the online customer service service based on matching criteria desired by the user.

[0046] Furthermore, the reception unit 131 accepts a string of characters as viewpoint information.

[0047] As a result, the information processing device 100 can recommend a customer service staff member to the user of the online customer service service based on the string of characters desired by the user.

[0048] Furthermore, the reception unit 131 receives as viewpoint information multiple strings and percentage information indicating the proportion that each of the multiple strings occupies within those multiple strings.

[0049] As a result, the information processing device 100 can recommend a customer service staff member to a user of an online customer service service, based on a set of strings desired by the user and the proportion of each string within that set of strings.

[0050] Furthermore, the reception unit 131 generates content including a graph that displays multiple strings in association with percentage information, and provides the content including the graph to the user.

[0051] As a result, the information processing device 100 can provide users with the desired viewpoint information in a visually easy-to-understand format.

[0052] Furthermore, the reception unit 131 receives weight information indicating the weight of the viewpoint information. The calculation unit 133 calculates the degree of matching based on the weights.

[0053] As a result, the information processing device 100 can recommend to the user the customer service staff desired by the user of the online customer service, based on the weight of the perspective information desired by the user.

[0054] Furthermore, the reception unit 131 generates a slider bar that displays the weight according to the position of the slider, and provides the slider bar to the user.

[0055] This allows the information processing device 100 to provide the user with the desired weight in a way that is easy for the user to visually grasp.

[0056] Furthermore, the reception unit 131 generates content that is displayed in a predetermined direction according to the order in which the multiple viewpoint information is input, and provides the content to the user. The calculation unit 133 calculates the degree of matching based on the weights corresponding to the order in which the multiple viewpoint information is arranged.

[0057] As a result, the information processing device 100 can recommend to the user the customer service staff desired by the user of the online customer service, based on weights corresponding to the order desired by the user.

[0058] Furthermore, the reception unit 131 receives degree information from the user, indicating the degree to which the recommendation results recommended by the service unit 134 reflect the degree of matching. The service unit 134 recommends a range of customer service staff to the user according to the degree information.

[0059] As a result, the information processing device 100 can recommend to the user the customer service staff desired by the user of the online customer service, based on the degree to which the user desires.

[0060] [5. Hardware Configuration] Furthermore, the information processing device 100 according to the above-described embodiment is realized by a computer 1000 having a configuration such as that shown in Figure 13. Figure 13 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device 100. The computer 1000 includes a CPU 1100, RAM 1200, ROM 1300, HDD 1400, communication interface (I / F) 1500, input / output interface (I / F) 1600, and media interface (I / F) 1700.

[0061] The CPU 1100 operates based on programs stored in the ROM 1300 or HDD 1400, controlling various components. The ROM 1300 stores boot programs executed by the CPU 1100 when the computer 1000 starts up, as well as programs that depend on the computer 1000's hardware.

[0062] The HDD1400 stores programs executed by the CPU1100, as well as data used by such programs. The communication interface1500 receives data from other devices via a predetermined communication network and sends it to the CPU1100, and transmits data generated by the CPU1100 to other devices via the predetermined communication network.

[0063] The CPU 1100 controls output devices such as displays and printers, and input devices such as keyboards and mice, via the input / output interface 1600. The CPU 1100 acquires data from input devices via the input / output interface 1600. The CPU 1100 also outputs the generated data to output devices via the input / output interface 1600.

[0064] The media interface 1700 reads a program or data stored in the recording medium 1800 and provides it to the CPU 1100 via the RAM 1200. The CPU 1100 loads the program from the recording medium 1800 onto the RAM 1200 via the media interface 1700 and executes the loaded program. The recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or PD (Phase Change Rewritable Disk), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0065] For example, when the computer 1000 functions as an information processing device 100 according to the embodiment, the CPU 1100 of the computer 1000 realizes the functions of the control unit 130 by executing a program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, these programs may be obtained from other devices via a predetermined communication network.

[0066] Although some embodiments of the present invention have been described in detail above with reference to the 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.

[0067] [6. Other] Furthermore, among the processes described in the above embodiments and modifications, all or part of the processes described as being performed automatically can be performed manually, or all or part of the processes described as being performed manually can be performed automatically by known methods. In addition, the processing procedures, specific names, and information including various data and parameters shown in the above document and drawings can be changed at will unless otherwise specified. For example, the various information shown in each figure is not limited to the information shown.

[0068] Furthermore, the components of each illustrated device are functionally conceptual and do not necessarily need 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, and all or part of them can be functionally or physically distributed and integrated in any unit according to various loads and usage conditions.

[0069] Furthermore, the embodiments and modifications described above can be combined as appropriate, provided that the processing content is not inconsistent. [Explanation of symbols]

[0070] 100 Information Processing Devices 110 Communications Department 120 Storage section 121 User information storage unit 122 Customer Service Staff Information Storage Department 130 Control Unit 131 Reception Department 132 Acquisition Department 133 Calculation Section 134 Provision Department

Claims

1. A reception unit that receives from the user of an online customer service service, which is a service in which the user receives customer service from a customer service staff member online, and a reception unit that receives from the user of the online customer service service, which receives from the user of the online customer service service information that indicates the criteria for matching the customer service staff member desired by the user with the user, An acquisition unit that acquires customer service staff information relating to the aforementioned customer service staff, A calculation unit that calculates a matching degree indicating the degree of matching based on the aforementioned viewpoint information and the aforementioned customer service staff information, A provisioning unit that recommends the customer service staff whose matching degree exceeds a predetermined threshold to the user, An information processing device equipped with the following features.

2. The aforementioned reception unit is The aforementioned perspective information accepts a string. The information processing apparatus according to claim 1.

3. The aforementioned reception unit is The aforementioned viewpoint information accepts multiple strings and percentage information indicating the proportion that each of the multiple strings occupies within the multiple strings. The information processing apparatus according to claim 1.

4. The aforementioned reception unit is The system generates content including a graph that displays the multiple strings and the percentage information in association, and provides the content including the graph to the user. The information processing apparatus according to claim 3.

5. The aforementioned reception unit is The system accepts weight information indicating the weight of the aforementioned viewpoint information. The calculation unit described above, Based on the aforementioned weights, the degree of matching is calculated. The information processing apparatus according to claim 1.

6. The aforementioned reception unit is A slider bar is generated that displays the weight according to the position of the slider, and the slider bar is provided to the user. The information processing apparatus according to claim 5.

7. The aforementioned reception unit is The system generates content that is displayed in a predetermined direction according to the order in which multiple perspective information is input, and provides the content to the user. The calculation unit described above, The degree of matching is calculated based on the weights corresponding to the order in which the multiple viewpoint information is arranged. The information processing apparatus according to claim 1.

8. The aforementioned reception unit is The service provider receives information from the user indicating the degree to which the recommendation results recommended by the service provider reflect the degree of matching. The aforementioned supply unit is, The system recommends to the user a customer service staff member who matches the aforementioned degree information. The information processing apparatus according to claim 1.

9. An information processing method performed by an information processing device, A reception process for receiving information from a user that indicates the criteria for matching the user with the customer service staff the user desires, in an online customer service service where the user receives customer service from customer service staff online, A process for acquiring customer service staff information relating to the aforementioned customer service staff, A calculation process for calculating the degree of matching, which indicates the degree of matching, based on the aforementioned viewpoint information and the aforementioned customer service staff information, A provision process that recommends the customer service staff whose matching degree exceeds a predetermined threshold to the user, Information processing methods including

10. A reception procedure for receiving information from a user that indicates the criteria for matching the user with the customer service staff the user desires, in an online customer service service where the user receives customer service from customer service staff online, The procedure for obtaining customer service staff information regarding the aforementioned customer service staff, A calculation procedure for calculating the degree of matching, which indicates the degree of matching, based on the aforementioned viewpoint information and the aforementioned customer service staff information, A provision procedure for recommending the customer service staff whose matching degree exceeds a predetermined threshold to the user, An information processing program that causes a computer to execute something.

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