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 that propose a new project.SOLUTION: An information processing device according to the present application includes: an extraction unit that extracts a need from input information input by each user; a setting unit that sets a virtual corresponding target that satisfies the need extracted by the extraction unit; an estimation unit that estimates a questionnaire result for the corresponding target set by the setting unit; and a providing unit that provides a project book indicating the corresponding target and the questionnaire result estimated by the estimation unit.SELECTED DRAWING: Figure 2

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] Conventionally, a technique for estimating a user's needs based on a search query input to a search site has been proposed. For example, as a technique for estimating needs, it has been disclosed that the needs of a target user are estimated based on a comparison between a past search pattern and the search pattern of the target user (see, for example, Patent Document 1).

Prior Art Documents

Patent Documents

[0003]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0004] However, in the prior art, the needs of an individual user are estimated based on existing search patterns, and new planning has not been considered.

[0005] The present invention has been made in view of the above, and an object thereof is to provide an information processing apparatus, an information processing method, and an information processing program capable of proposing a new plan.

Means for Solving the Problems

[0006] In order to solve the above-described problems and achieve the object, an information processing apparatus according to the present invention includes an extraction unit that extracts needs from input information input by each user, a setting unit that sets a virtual correspondence target that satisfies the needs extracted by the extraction unit, an estimation unit that estimates a questionnaire result for the correspondence target set by the setting unit, and a provision unit that provides a proposal document showing the correspondence target and the questionnaire result estimated by the estimation unit.

Effect of the Invention

[0007] According to the present invention, a new proposal can be made.

Brief Description of the Drawings

[0008]

Figure 1

Figure 2

Figure 3

Figure 4

Figure 5

Figure 6

Figure 7

Mode for Carrying Out the Invention

[0009] Hereinafter, embodiments for implementing the information processing apparatus, information processing method, and information processing program according to the present application (hereinafter referred to as "embodiments") will be described in detail with reference to the drawings. Note that the information processing apparatus, information processing method, and information processing program according to the present application are not limited by these embodiments.

[0010] [Embodiment] [1. Information Processing] First, an example of the information processing according to the embodiment will be described with reference to FIG. 1. FIG. 1 is a diagram showing an example of the information processing according to the embodiment. Such an information processing method is executed, for example, by the information processing apparatus 1 shown in FIG. 1.

[0011] As shown in FIG. 1, the information processing apparatus 1 according to the embodiment is an information processing apparatus that provides various contents to the user terminal 50. For example, the information processing apparatus 1 provides various search services through a search site. Note that the information processing apparatus 1 is realized by, for example, a server apparatus, a cloud system, or the like.

[0012] The user terminal 50 is a terminal device owned by the user U and is a terminal that displays the contents provided from the information processing apparatus 1 through data communication with the information processing apparatus 1. Examples of the user terminal 50 include a smartphone, a tablet terminal, a personal computer, a wearable terminal, and the like. Note that in FIG. 1, for convenience of explanation, one user terminal 50 is shown, but the information processing apparatus 1 provides various services to a plurality of user terminals 50.

[0013] By the way, conventionally, a technique for estimating a user's needs from a search query has been disclosed. For example, the estimated user needs are utilized to match existing products, etc., with the needs of the user U, such as delivering advertisements suitable for the user's needs like search-linked advertisements.

[0014] In contrast, the information processing apparatus 1 according to the embodiment provides a new service that utilizes the estimated needs of the user U. Specifically, the information processing apparatus 1 sets a virtual target to be addressed that meets the needs of the user U, and provides a plan document regarding such a target to be addressed. In this embodiment, although the case where the target to be addressed is a "thing" such as a new product will be described, the target to be addressed shall include things other than "things" such as, for example, applications and services such as advertisements.

[0015] As shown in FIG. 1, the information processing apparatus 1 provides a search site to the user U through the user terminal 50 (step S1), and receives an input of a search query from the user U through the user terminal 50 (step S2). Note that in FIG. 1, only one user terminal 50 is shown, but the information processing apparatus 1 provides a search site to a plurality of user terminals 50 and receives an input of a search query from each user U. Further, the search query corresponds to an example of the input information. Note that the input information includes information input by each user U and publicly disclosed on the Web. The information publicly disclosed on the Web includes information posted on SNSs or blogs, comments written on various Web sites such as news sites, and the like.

[0016] The information processing apparatus 1 extracts needs by analyzing a search query group that accumulates information regarding the search queries input by each user U (step S3). For example, the information processing apparatus 1 extracts needs using an answer generation model that has been learned to generate an answer for an input natural language sentence. The answer generation model is, for example, GPT (Generative Pre-trained Transformer).

[0017] For example, the information processing apparatus 1 inputs the search query group and an instruction sentence for need extraction to the answer generation model as prompts. The instruction sentence is, for example, a sentence such as "Please extract needs from the following search query group". From the viewpoint of extracting new needs, the instruction sentence may include a sentence such as "Please extract niche needs".

[0018] Note that the information processing apparatus 1 may extract needs for each product category. For example, in this case, for the product category of "washing machine", needs related to the "washing machine" are extracted from the search queries searched together with the "washing machine". The product category may be, for example, a product category designated by the client company, or may be set on the side of the information processing apparatus 1 based on the product category provided by the client company.

[0019] Subsequently, the information processing apparatus 1 sets a virtual corresponding target that satisfies the extracted needs (step S4). For example, the information processing apparatus 1 groups the extracted needs using an answer generation model, and sets a virtual product (hereinafter also referred to as a virtual product) for the needs of each group.

[0020] At this time, the information processing apparatus 1 sets a virtual product using the above answer generation model. Specifically, the information processing apparatus 1 inputs an instruction sentence such as "Please set a virtual product that satisfies the extracted needs" to the answer generation model as a prompt.

[0021] Then, the information processing apparatus 1 sets the answer output by the answer generation model for the prompt as a virtual product. After that, the information processing apparatus 1 estimates the questionnaire results for the virtual product (step S5).

[0022] The information processing apparatus 1 estimates the questionnaire results for the virtual product using the answer generation model. For example, the information processing apparatus 1 inputs a prompt including information about a virtual persona and an instruction sentence to the answer generation model.

[0023] For example, the instruction sentence here is a sentence such as "Please estimate the questionnaire results by the following persona for the virtual product". Note that the information about the persona may utilize the personal information of the user U held by the search site. That is, by setting a persona using the information held by the company, it is possible to estimate questionnaire results close to those of the actual user U.

[0024] Then, the information processing apparatus 1 generates a project plan based on the answer by the answer generation model, and provides the generated project plan to the client company (step S6). Here, a specific example of the project plan will be described with reference to FIG. 2.

[0025] FIG. 2 is a diagram showing an example of a project plan according to the embodiment. In FIG. 2, the case where the virtual product is a product called "hanger fit clip" will be described. As shown in FIG. 2, the project plan A includes an illustration Ir of the virtual product, a radar chart Ch, an explanation of the product, and a persona's comment on the virtual product.

[0026] The illustration Ir is an image of the virtual product generated using an image generation model, as will be described later. The radar chart Ch is a chart that visualizes the evaluation regarding the product. In the example shown in FIG. 2, the case where the radar chart Ch includes items such as "purchase intention", "novelty", "price perception", "product benefit", and "ease of manufacture" is illustrated.

[0027] Among these, for the item of "purchase intention", the score is determined by aggregating the questionnaire results for the virtual product, and for each of the items of "novelty", "price perception", "product benefit", and "ease of manufacture", the score is determined, for example, at the stage of setting the virtual product.

[0028] In addition, the explanation of the product has items such as "product name", "product category", "detailed explanation", "problems to be solved and the background of the people having those problems", "value provided", "innovative nature", "similarity to competing products", "market size and competitiveness", "purchase timing and specific examples", "product shape and dimensions", "assumed selling price", "cost performance", "feasibility and realization method", and "ranking". These items may be instructed as prompts, or may be set on the side of the answer generation model.

[0029] In addition, the persona's comments on the virtual product have a "positive comment" item and a "negative comment" item. The information processing apparatus 1 inputs, to the answer generation model, a prompt for generating the questionnaire results regarding these items for generating by the answer generation model.

[0030] In this way, the information processing apparatus 1 according to the embodiment extracts needs based on the search query and sets the virtual product. Then, the information processing apparatus 1 provides a proposal document including the questionnaire results for the virtual product.

[0031] Therefore, according to the information processing apparatus 1 according to the embodiment, a new proposal that matches the user's needs can be proposed.

[0032] 〔2. Information Processing Apparatus〕 Next, with reference to FIG. 3, a configuration example of the information processing apparatus 1 according to the embodiment will be described. FIG. 3 is a block diagram showing a configuration example of the information processing apparatus 1 according to the embodiment. As shown in FIG. 3, the information processing apparatus 1 includes a communication unit 2, a storage unit 3, and a control unit 4. Note that the information processing apparatus 1 may have an input unit (for example, a keyboard or a mouse) that receives various operations from an administrator or the like who uses the information processing apparatus 1, and a display unit (for example, a liquid crystal display) for displaying various information.

[0033] The communication unit 2 is realized by, for example, a NIC (Network Interface Card) or the like. The communication unit 2 is connected to a communication network such as 4G (4th Generation) or 5G (5th Generation) in a wired or wireless manner, and transmits and receives information to and from each of the user terminals 50 or the like via the communication network.

[0034] The storage unit 3 is implemented by, for example, a semiconductor memory device such as a RAM (Random Access Memory) or a flash memory, or a storage device such as a hard disk or an optical disk. The storage unit 3 includes a search history storage unit 31, a user information storage unit 32, an answer generation model storage unit 33, and an image generation model storage unit 34.

[0035] The search history storage unit 31 stores the search history. The search history is a history of search queries input by the user U. FIG. 4 is a diagram showing an example of information stored in the search history storage unit 31 according to the embodiment.

[0036] As shown in FIG. 4, the search history storage unit 31 stores information on items such as "search date and time", "search query", and "user ID" in association with each other. In the "search date and time" item, information regarding the date and time when the user U performed a search on the search site is stored.

[0037] In the "search query" item, information regarding the search query used by the user U on the search site (for example, the keywords used in the search) is stored. In the "user ID" item, an identifier for identifying the user U who performed the search is stored.

[0038] Returning to the description of FIG. 3, the user information storage unit 32 will be described. The user information storage unit 32 stores user information. Note that the user information corresponds to an example of customer information held by a company.

[0039] FIG. 5 is a diagram showing an example of information stored in the user information storage unit 32 according to the embodiment. As shown in FIG. 5, the user information storage unit 32 stores information on items such as "user ID", "registration information", and "attribute information" in association with each other.

[0040] In the "user ID" item, an identifier for identifying the user U is stored. The "registration information" stores information registered by the user U identified by the corresponding user ID. The registration information includes information regarding name, age, occupation, address, etc.

[0041] In the "attribute information" item, information regarding the attributes of user U identified by the corresponding user ID is stored. The attribute information is information regarding the attributes of the corresponding user U and includes information regarding hobbies and preferences. Information regarding hobbies and preferences can be estimated from the search history of user U and the behavior history of user U in services such as online shopping that are linked.

[0042] Returning to the description of FIG. 3, the answer generation model storage unit 33 will be described. The answer generation model storage unit 33 stores an answer generation model. The answer generation model is a model that is learned to generate a natural language answer for an input natural language sentence, and is, for example, GPT.

[0043] The image generation model storage unit 34 stores an image generation model. The image generation model is a model that is learned to generate an image for an input natural language sentence.

[0044] Next, the control unit 4 will be described. The control unit 4 is a controller and is realized, for example, by various programs (corresponding to an example of an information processing program) stored in the storage device inside the information processing apparatus 1 being executed with the RAM as a work area by a CPU (Central Processing Unit), an MPU (Micro Processing Unit), or the like. Further, the control unit 4 is, for example, a controller and is realized by an integrated circuit such as an ASIC (Application Specific Integrated Circuit) or an FPGA (Field Programmable Gate Array).

[0045] As shown in FIG. 3, the control unit 4 includes an acquisition unit 41, an extraction unit 42, a setting unit 43, an estimation unit 44, and a provision unit 45, and realizes or executes the functions and operations of the information processing described below. Note that the internal configuration of the control unit 4 is not limited to the configuration shown in FIG. 3, and may be any other configuration as long as it can perform the information processing described later. Also, the connection relationship between the respective processing units included in the control unit 4 is not limited to the connection relationship shown in FIG. 3, and may be any other connection relationship.

[0046] The acquisition unit 41 acquires input information input by the user U. In the present embodiment, the acquisition unit 41 acquires, through a search site, information related to the search query input by the user U as input information, and stores it in the search history storage unit 31 together with the user ID of the user U.

[0047] The extraction unit 42 extracts needs from the input information input by the user. In the present embodiment, the extraction unit 42 estimates needs from the search history stored in the search history storage unit 31.

[0048] First, the extraction unit 42 determines the product category. For example, the product category can be determined by accepting a designation from the client company or by acquiring product information provided by the client company. Subsequently, the extraction unit 42 extracts needs using the answer generation model stored in the answer generation model storage unit 33. For example, the extraction unit 42 inputs a prompt including the search history and an instruction sentence to the answer generation model.

[0049] The instruction sentence is, for example, a sentence such as "Please extract needs related to the following product category from the following search history" or a sentence such as "Please extract niche needs from the following search history". The answer generation model generates a sentence related to the extracted needs as an answer to the prompt including these instruction sentences.

[0050] Note that when extracting needs, the extraction unit 42 may accept the specification of user attributes from the client company and extract the needs related to the specified user attributes. For example, in this case, the extraction unit 42 extracts the search history of the specified user attributes and extracts the needs from such search history.

[0051] The setting unit 43 sets a virtual corresponding object that satisfies the needs extracted by the extraction unit 42. In the present embodiment, the setting unit 43 sets a virtual product that satisfies the needs in the specified product category. For example, the setting unit 43 groups the needs extracted by the extraction unit 42 in each product category and sets a virtual product for each group.

[0052] For example, the setting unit 43 groups the needs using an answer generation model. For example, the prompt at this time includes the extracted needs and an instruction sentence. For example, the instruction sentence is a sentence such as "Please group the following needs".

[0053] Subsequently, the setting unit 43 sets a virtual product that satisfies the needs of the product category for each group. For example, the setting unit 43 inputs an instruction sentence such as "Please set a virtual product that satisfies the needs for each group in the following product category" to the answer generation model.

[0054] Note that at this time, the setting unit 43 may ask the answer generation model about the type of corresponding object that satisfies the needs for each group. The types here are classified into things, applications, services, etc.

[0055] Through these processes, when the setting unit 43 finishes setting the virtual product, it generates a prompt for generating the illustration Ir (see Figure 2) of the virtual product using the answer generation model. For example, the prompt here includes information about the virtual product and an instruction sentence for generating the prompt.

[0056] For example, the instruction text is a text such as "Please generate a prompt for generating an illustration of the following virtual product using an image generation model". At this time, the setting unit 43 may input an instruction text for generating an illustration of a three-view drawing to the answer generation model.

[0057] The setting unit 43 inputs the prompt generated by the answer generation model into the image generation model stored in the image generation model storage unit 34 to generate an illustration of the virtual product. Then, the setting unit 43 generates questionnaire content. For example, the questionnaire content includes a description of the virtual product and an illustration of the virtual product.

[0058] The estimation unit 44 estimates the questionnaire results for the corresponding target set by the setting unit 43. First, the estimation unit 44 sets the persona to be the target of the questionnaire. For example, the persona is set based on the user information registered in the user information storage unit 32. For example, the estimation unit 44 randomly selects a specified number of user information from the user information registered in the user information storage unit 32 and selects the persona. Note that for the persona, for example, a designation from the client company may be accepted.

[0059] For example, in such a case, the client company can specify the target user attributes, and the estimation unit 44 selects the user information of the user attributes specified by the client company from the user information storage unit 32 and sets the persona.

[0060] Subsequently, the estimation unit 44 inputs information about the virtual product set by the setting unit 43, information about the set persona, and a prompt including the instruction text to the answer generation model. The instruction text is, for example, a text such as "Please estimate the results of a questionnaire by the following persona for the following product".

[0061] At this time, for example, as shown in FIG. 2, the estimation unit 44 requests the response generation model to generate items related to the radar chart Ch such as "purchase intention" and "price perception", and comments such as "positive comments" and "negative comments".

[0062] The providing unit 45 provides a plan document showing the virtual product and the questionnaire results estimated by the estimation unit 44. First, the providing unit 45 generates a plan document including the virtual product set by the setting unit 43 and the questionnaire results estimated by the estimation unit 44.

[0063] For example, the providing unit 45 generates a plan document using the response generation model. For example, the providing unit 45 inputs information about the virtual product, the questionnaire results, and the instruction text as a prompt into the response generation model.

[0064] For example, the instruction text in this case is a text such as "Please generate a plan document from the following information about the virtual product and the following questionnaire results". Note that the plan document may be in a preset format, or the format itself may be generated by the response generation model.

[0065] Also, when the plan document is in a preset format, the providing unit 45 may automatically generate it using another program. For example, the other program may be a program generated by the response generation model. Then, the providing unit 45 provides the generated plan document to the client company via the communication unit 2.

[0066] 〔3. Processing Flow〕 Next, with reference to FIG. 6, the processing procedure executed by the information processing apparatus 1 according to the embodiment will be described. FIG. 6 is a flowchart showing an example of the providing process according to the embodiment.

[0067] As shown in FIG. 6, first, the information processing apparatus 1 determines a product category (step S101). Subsequently, the information processing apparatus 1 extracts a search query corresponding to the product category (step S102).

[0068] Subsequently, the information processing apparatus 1 estimates needs from the extracted search query (step S103), and sets products that satisfy the needs (step S104). Subsequently, the information processing apparatus 1 conducts a virtual questionnaire (step S105), provides a proposal (step S106), and ends the process.

[0069] [4. Modification Example] By the way, in the above-described embodiment, the case where the input information is a search query has been described, but the present invention is not limited thereto. For example, the input information may be a prompt input to the answer generation model. For example, in such a case, on the search site, the answer generation model may be generally provided, and the information of the prompt input to the answer generation model may be acquired as the input information.

[0070] [5. Effect] The information processing apparatus 1 according to the above-described embodiment includes an extraction unit 42 that extracts needs from input information input by each user, a setting unit 43 that sets a virtual corresponding target that satisfies the needs extracted by the extraction unit 42, an estimation unit 44 that estimates a questionnaire result for the corresponding target set by the setting unit 43, and a provision unit 45 that provides a proposal indicating the corresponding target and the questionnaire result estimated by the estimation unit 44.

[0071] Further, the setting unit 43 sets a corresponding target that satisfies the needs for each category of the corresponding target. Further, the extraction unit 42 extracts needs from a search query input by the user as the input information.

[0072] Further, the estimation unit 44 sets a plurality of personas and estimates questionnaire results by the plurality of personas. Further, the estimation unit 44 sets personas based on customer information held by the company.

[0073] Further, the setting unit 43 generates an image corresponding to the input text using an image generation model trained to generate an image corresponding to the input text, and the providing unit 45 provides a proposal document including the image corresponding to the target. Further, the setting unit 43 generates the text to be input to the image generation model using a response generation model trained to generate a response to the input text.

[0074] By any one or a combination of the above-described processes, the information processing apparatus according to the present application can propose a new plan.

[0075] [6. Hardware Configuration] Also, the information processing apparatus 1 according to the above-described embodiment is realized by a computer 1000 having a configuration as shown in FIG. 7, for example. FIG. 7 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing apparatus 1 according to the embodiment. The computer 1000 includes a CPU 1100, a RAM 1200, a ROM 1300, an HDD 1400, a communication interface (I / F) 1500, an input / output interface (I / F) 1600, and a media interface (I / F) 1700.

[0076] The CPU 1100 operates based on a program stored in the ROM 1300 or the HDD 1400 and controls each part. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 is started up, a program depending on the hardware of the computer 1000, and the like.

[0077] The HDD 1400 stores a program executed by the CPU 1100, data used by such a program, and the like. The communication interface 1500 receives data from other devices via a network (communication network) N and sends it to the CPU 1100, and sends data generated by the CPU 1100 to other devices via the network N.

[0078] The CPU 1100 controls output devices such as displays and printers, and input devices such as keyboards and mice (in FIG. 7, the output devices and input devices are collectively referred to as "input / output devices") via the input / output interface 1600. The CPU 1100 acquires data from the input device via the input / output interface 1600. Further, the CPU 1100 outputs the generated data to the output device via the input / output interface 1600.

[0079] 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 such a 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 a 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 or the like.

[0080] For example, when the computer 1000 functions as the information processing apparatus 1 according to the embodiment, the CPU 1100 of the computer 1000 realizes the functions of the control unit 4 by executing the program loaded on the RAM 1200. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800. As another example, these programs may be acquired from other devices via the network N.

[0081] As described above in detail some of the embodiments of the present application with reference to the drawings, these are examples, and the present invention can be implemented in other forms with various modifications and improvements based on the knowledge of those skilled in the art, starting from the aspects described in the column of the disclosure of the invention.

[0082] 〔7. Others〕 Also, among the processes described in the above embodiments and modified examples, all or part of the processes described as being automatically performed can be manually performed, or all or part of the processes described as being manually performed can be automatically performed by a known method. In addition, regarding the processing procedures, specific names, and information including various data and parameters shown in the above documents and drawings, they can be arbitrarily changed unless otherwise specified. For example, the various information shown in each figure is not limited to the illustrated information.

[0083] Also, each component of each device shown in the drawings is conceptually functional and does not necessarily have to be physically configured as shown in the drawings. That is, the specific form of the distribution and integration of each device is not limited to that shown, and all or part of it can be functionally or physically distributed and integrated in any unit according to various loads, usage situations, etc.

[0084] Also, the above-described embodiments and modified examples can be appropriately combined within a range that does not conflict with the processing content.

[0085] Also, the above-described "section, module, unit" can be read as "means", "circuit", etc. For example, the generation unit can be read as a generation means or a generation circuit.

Explanation of Reference Numerals

[0086] 1 Information processing device 2 Communication unit 3 Storage unit 4 Control unit 31 Search history storage unit 32 User information storage unit 33 Answer generation model storage unit 34 Image generation model storage unit 41 Acquisition unit 42 Extraction unit 43 Setting unit 44 Estimation unit 45 Provision unit 50 User terminal A Project document U User

Claims

1. An extraction unit that extracts needs from input information input by each user, A setting unit that sets a virtual corresponding target that satisfies the needs extracted by the extraction unit, An estimation unit that estimates a questionnaire result for the corresponding target set by the setting unit, And a providing unit that provides a proposal document showing the corresponding target and the questionnaire result estimated by the estimation unit An information processing apparatus characterized by comprising the above.

2. The setting unit Sets the corresponding target that satisfies the needs for each category of the corresponding target The information processing apparatus according to claim 1, characterized in that.

3. The extraction unit Extracts the needs from a search query input by each user as the input information The information processing apparatus according to claim 1, characterized in that.

4. The estimation unit Sets a plurality of personas and estimates the questionnaire results by the plurality of personas The information processing apparatus according to claim 1, characterized in that.

5. The estimation unit Sets the persona based on customer information held by the company The information processing apparatus according to claim 4, characterized in that.

6. The setting unit Generates an image of the corresponding target using an image generation model learned to generate an image corresponding to the input text, The providing unit Provides the proposal document including the image of the corresponding target The information processing apparatus according to claim 1, characterized in that.

7. The setting unit After setting the corresponding target using an answer generation model learned to generate an answer for the input text, generates the text to be input to the image generation model The information processing apparatus according to claim 6, characterized in that.

8. An information processing method executed by a computer, An extraction step of extracting needs from input information input by each user, A setting step of setting a virtual corresponding target that satisfies the needs extracted by the extraction step, An estimation step of estimating a questionnaire result for the corresponding target set by the setting step, And a providing step of providing a proposal document showing the corresponding target and the questionnaire result estimated by the estimation step An information processing method characterized by including the above.

9. An extraction procedure for extracting needs from input information input by each user, A setting procedure for setting a virtual corresponding target that satisfies the needs extracted by the extraction procedure, An estimation procedure for estimating the questionnaire results for the corresponding target set by the setting procedure, A provision procedure for providing a project plan showing the corresponding target and the questionnaire results estimated by the estimation procedure, An information processing program characterized by causing a computer to execute the above.

Images