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

Abstract

To estimate a need for a commodity.SOLUTION: An information processing device includes: an acquisition unit that obtains an answer history including both a question about a commodity which is input to a model that generates an answer to an input question and an answer by the model; and an estimation unit that estimates a need for the commodity by analyzing the answer history obtained by the acquisition unit.SELECTED DRAWING: Figure 1

Description

[Technical Field]

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

[0002] With the rapid spread of the Internet, techniques have been provided for analyzing various types of information on the Internet. For example, a technique has been proposed for extracting information about product needs based on a search query entered by a user in an online shopping mall (see, for example, Patent Document 1). [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Japanese Patent Application Publication No. 2019-32776 Summary of the Invention [Problem to be solved by the invention]

[0004] However, the conventional techniques have room for improvement in estimating product needs.

[0005] The present invention has been made in view of the above, and has an object to provide an information processing device, an information processing method, and an information processing program that are capable of estimating needs for a product. [Means for solving the problem]

[0006] In order to solve the above-mentioned problems and achieve the objectives, the information processing device of the present invention includes an acquisition unit that acquires a response history including questions about a product input to a model that generates answers to input questions and answers from the model, and an estimation unit that analyzes the response history acquired by the acquisition unit and estimates needs for the product. [Effects of the Invention]

[0007] According to the present invention, it is possible to accurately estimate needs for a product. [Brief explanation of the drawings]

[0008] [Figure 1] FIG. 1 is a diagram illustrating an example of information processing according to an embodiment. [Figure 2] FIG. 2 is a block diagram illustrating an example of the configuration of the information processing device according to the embodiment. [Figure 3] FIG. 3 is a diagram illustrating an example of information stored in the answer history storage unit according to the embodiment. [Figure 4] FIG. 4 is an explanatory diagram of the estimation process according to the embodiment. [Figure 5] FIG. 5 is an explanatory diagram of the estimation process according to the embodiment. [Figure 6] FIG. 6 is a flowchart illustrating an example of a processing procedure of the providing process according to the embodiment. [Figure 7] FIG. 7 is an explanatory diagram regarding the visibility of a product according to the embodiment. [Figure 8] FIG. 8 is a hardware configuration diagram illustrating an example of a computer that realizes the functions of the information processing device according to the embodiment. DETAILED DESCRIPTION OF THE INVENTION

[0009] Hereinafter, an information processing device, an information processing method, and an information processing program according to the present application will be described in detail with reference to the drawings. Note that the information processing device, the information processing method, and the information processing program according to the present application are not limited to the embodiments.

[0010] [Embodiment] [1. Information Processing] First, an example of information processing according to the embodiment will be described with reference to Fig. 1. Fig. 1 is a diagram showing an example of information processing according to the embodiment. Note that the information processing according to the embodiment is realized by an information processing device 1 shown in Fig. 1.

[0011] 1 is, for example, an information processing device that operates various online shopping malls. As will be described later, the information processing device 1 estimates needs for products and provides information on the estimated needs for the products to various manufacturers, sellers in the online shopping malls, etc.

[0012] The user terminal 100 shown in Fig. 1 is a terminal device owned by a user U. For example, the user U can operate the user terminal 100 to access an online shopping mall operated by the information processing device 1 and view or purchase products. Note that Fig. 1 illustrates an example in which the user terminal 100 is a smartphone, but the user terminal 100 may be other devices such as a PC (Personal Computer).

[0013] The information providing device 200 shown in Fig. 1 has a model. The model is, for example, a sentence generation model that has learned from data published on the Web. For example, the model is a GPT (Generative Pre-trained Transformer) model that generates answers to questions. The model may be implemented in the information processing device 1.

[0014] By the way, such models generate answers to questions from data published on the Web. Since new data is published on the Web every day, the answers generated by the models are updated every day.

[0015] That is, even if the same question is asked, different answers will be generated because the data that the model refers to when generating the answer will differ depending on the time of the question, etc. Also, since the model can provide detailed answers to questions in a wide range of fields, a wide variety of questions will be asked of the model by user U.

[0016] In this embodiment, focusing on this point, the needs for a product are estimated using the response history of the model. Specifically, as shown in Fig. 1, the information providing device 200 accepts a question from a user U through the user terminal 100 (step S1), and provides an answer generated by the model to the user terminal 100 in a conversational format (step S2).

[0017] For example, in the example shown in Figure 1, user U's question is, "Do they sell eye shadow for deep-set eyelids?" and the answer is, "They don't sell eye shadow for deep-set eyelids." In other words, user U's question reveals that there is a need for "eye shadow for deep-set eyelids," and the answer suggests that "eye shadow for deep-set eyelids" is not sold.

[0018] The information processing device 1 acquires an answer history including questions and answers from the information providing device 200 (step S3), and estimates the needs for the product by analyzing the answer history (step S4).

[0019] FIG. 1 shows a graph with two axes: the vertical axis shows the percentage of models who answered "no" and the horizontal axis shows "needs." Here, the "percentage of models who answered "no" indicates the percentage of all answers to questions about the corresponding product that suggest that the product does not exist. Note that the "percentage of models who answered "no" may also include the percentage of models who did not give appropriate answers to the product. For example, in response to a question about "eye shadow for double eyelids," a model may answer about "double eyelids" or "eye shadow," and the answer may be classified as "answer that answered "no." Furthermore, the needs on the horizontal axis shown in FIG. 1 correspond to the number of questions about the corresponding product from user U.

[0020] The information processing device 1 estimates the needs for each product by mapping the response history for each product onto a graph. Figure 1 shows the estimation results for "washing machine for leather," "eye shadow for double eyelids," and "eyebrow pencil for thick eyebrows."

[0021] In the example shown in Figure 1, the "leather washing machine" suggests that there is little demand and that it is an unsold product, while the "thick eyebrow pencil" suggests that there is a high demand but that it is already on sale.

[0022] Furthermore, "eye shadow for deep-set eyelids" is in high demand, and suggests that it is a product that has not yet been sold. In other words, there is little demand for "skin washing machines," so there is little benefit in selling (developing) the product, while "eyebrow products for thick eyebrows" are already on the market and already have a certain market share. On the other hand, "eye shadow for deep-set eyelids" suggests that, although the product itself does not exist, a certain level of demand can be expected.

[0023] For example, the information processing device 1 generates content related to a product that is in demand but not yet sold, such as "eye shadow for double eyelids," and provides it to the operator (manager) of the online shopping mall.

[0024] This allows online shopping mall operators to take action such as proposing new products or joint development to manufacturers and online shopping mall exhibitors based on such content.

[0025] For example, the information processing device 1 can propose new products that combine multiple keywords, such as "for double eyelids" and "eye shadow," to suggest products that are in demand but not on sale, i.e., products that have not previously captured demand.

[0026] In this way, the information processing device 1 according to the embodiment acquires an answer history including questions about products input to a model that generates answers to input questions and answers from the model, analyzes the answer history, and estimates needs for the products. Therefore, the information processing device 1 according to the embodiment can estimate needs for the products.

[0027] Furthermore, since demand for models that answer questions in a conversational format is expected to increase in the future, it is expected that an even greater number of questions will be accumulated in the models. Therefore, by analyzing the response history of the models, the information processing device 1 can estimate the needs for a wide range of products.

[0028] [2. Information Processing Device] Next, a configuration example of the information processing device 1 according to the embodiment will be described with reference to Fig. 2. Fig. 2 is a block diagram showing the configuration example of the information processing device 1 according to the embodiment. As shown in Fig. 2, the information processing device 1 includes a communication unit 2, a storage unit 3, and a control unit 4. Note that the information processing device 1 may also include an input unit (e.g., a keyboard or a mouse) that accepts various operations from an administrator who uses the information processing device 1, and a display unit (e.g., a liquid crystal display) that displays various information.

[0029] The communication unit 2 is realized by, for example, a network interface card (NIC), etc. The communication unit 2 is connected to a communication network such as 4G (4th Generation) or 5G (5th Generation) by wire or wirelessly, and transmits and receives information to and from each of the user terminal 100, the information providing device 200, etc. via the communication network.

[0030] The storage unit 3 is realized by, for example, a semiconductor memory element 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 has an answer history storage unit 31.

[0031] The answer history storage unit 31 stores an answer history. The answer history is a history of questions posed to a model and answers. Fig. 3 is a diagram showing an example of information stored in the answer history storage unit 31 according to the embodiment.

[0032] 3, the answer history storage unit 31 stores information on items such as "question," "answer," and "date and time" in association with one another. "Question" indicates the content of the question that the user U asked the model.

[0033] "Answer" indicates the content of the answer output by the model in response to the corresponding question. "Date and time" indicates the date and time when the user U asked the model a question. If it is possible to obtain information about the attributes of the user U who asked the question, the answer history storage unit 31 may store the information related to the attributes of the user U in association with the answer.

[0034] Returning to the explanation of Fig. 2, the control unit 4 will now be described. The control unit 4 is a controller, and is realized, for example, by a CPU (Central Processing Unit) or an MPU (Micro Processing Unit) using RAM as a work area to execute various programs (corresponding to examples of information processing programs) stored in a storage device inside the information processing device 1. The control unit 4 is also, 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).

[0035] As shown in Fig. 2, the control unit 4 includes an acquisition unit 41, an estimation unit 42, and a provision unit 43, and realizes or executes the functions and actions of information processing described below. The internal configuration of the control unit 4 is not limited to the configuration shown in Fig. 2, and may be other configurations as long as they perform the information processing described below. Furthermore, the connection relationship between the processing units included in the control unit 4 is not limited to the connection relationship shown in Fig. 2, and may be other connection relationships.

[0036] The acquisition unit 41 acquires an answer history including questions about products input to a model that generates answers to input questions and answers generated by the model. For example, the acquisition unit 41 acquires the answer history from the information providing device 200 (see FIG. 1) at a predetermined interval.

[0037] For example, the acquisition unit 41 acquires questions about each product sold in the online shopping mall and an answer history including the answers to the questions. Note that the acquisition unit 41 may acquire the answer history by asking the information providing device 200 the same question about a specific product at a predetermined cycle and acquiring the answers to the questions.

[0038] For example, the acquisition unit 41 repeatedly asks questions previously asked by the user U or questions set by an administrator or the like at a predetermined cycle, and acquires the answer history to these questions. For example, in the example of Fig. 1, the acquisition unit 41 repeatedly asks the question "Do they sell eye shadow for double eyelids?" asked by the user U at a predetermined cycle, and acquires the answer history to these questions.

[0039] The estimation unit 42 estimates needs for a product by analyzing the answer history acquired by the acquisition unit 41. For example, the estimation unit 42 estimates needs from the number of questions about the product included in the answer history, and estimates the sales status of the product from the content of the answers included in the answer history.

[0040] For example, the estimation unit 42 extracts questions and answers about each product from the answer history using a predetermined language analysis. Next, the estimation unit 42 tallies the number of questions about each product, and estimates that the greater the number of questions, the greater the need for that product. Note that when tallying the number of questions, the estimation unit 42 excludes questions asked by the acquisition unit 41 from the tallying.

[0041] Furthermore, the estimation unit 42 performs a predetermined language analysis on the content of the answers included in the answer history to classify the answers into answers suggesting that a corresponding product exists and answers suggesting that a corresponding product does not exist. The estimation unit 42 estimates the sales status of the product according to the tendency between answers suggesting that a corresponding product exists and answers suggesting that a corresponding product does not exist.

[0042] For example, the sales status of a product is classified into a situation where the product is already on sale and a situation where the product is not on sale, but also includes, for example, a situation where the product is not on sale but is scheduled to be sold.

[0043] The estimation unit 42 tally up questions asked over a predetermined period (for example, one week or one month) and analyzes the tendency between answers suggesting that a corresponding product exists and answers suggesting that a corresponding product does not exist. The analysis results suggest the change in sales status over each period.

[0044] The estimation unit 42 may also estimate the time when a product was released based on a time series change in the responses to the product. For example, the estimation unit 42 estimates that the time when the proportion of responses suggesting the existence of a corresponding product began to increase is the time when the product was released.

[0045] Fig. 4 is an explanatory diagram of the estimation process according to the embodiment. Fig. 4 shows answers about a product before and after the product is newly released. As shown in Fig. 4, the estimation unit 42 analyzes time-series changes in questions about the same product.

[0046] In the example shown in Figure 4, at time t2, the answer is "They don't sell eye shadow for double eyelids," and at a later time t3, the answer is "It seems that eye shadow for double eyelids is sold at XX (store name)."

[0047] 4 indicates that the product was already on sale at time t3, but was not on sale before time t2. In other words, it suggests that "eye shadow for double eyelids" was on sale between time t2 and time t3.

[0048] In this case, the estimation unit 42 may estimate the time when the product was released according to a change in the level of abstraction of the answer about the product. For example, the estimation unit 42 may estimate, as the time when the product was released, the time when the answer about the product changed from whether or not the product was available to specific information about the product, such as "It seems a new color has been released" or "It seems to be sold at XX." Note that the estimation unit 42 may estimate, in addition to the answer, the time when the product was released according to a change in the level of abstraction of the question. In other words, the estimation unit 42 may estimate, as the time when the product was released, the time when the question of the user U became more specific.

[0049] The estimation unit 42 can also estimate needs for products that have already been sold. Fig. 5 is an explanatory diagram of the estimation process according to the embodiment. For example, the estimation unit 42 classifies answers included in a specific product from the answer history into positive answers and negative answers.

[0050] The estimation unit 42 then estimates the needs for products that have already been sold based on changes in these ratios. More specifically, as shown in Figure 5, if the ratio of positive responses to negative responses increases over time, it is estimated that there is a risk that the future market size will decrease. On the other hand, if the ratio of negative responses to positive responses increases over time, it is estimated that there is a risk that the future market size will increase.

[0051] The responses may be classified into categories such as "cheap" and "expensive," "dangerous" and "safe," "easy to use" and "difficult to use," "difficult to obtain" and "in stock," etc., and the estimation unit 42 may estimate future increases or decreases in the market size based on the results of these classifications.

[0052] Returning to the explanation of Fig. 2, the providing unit 43 will be described. The providing unit 43 provides information on products whose needs estimated by the estimation unit 42 exceed a threshold and that are not yet on sale. From the estimation results regarding needs by the estimation unit 42, the providing unit 43 extracts products whose needs are estimated to be above a certain level and that are not yet on sale.

[0053] For example, the providing unit 43 provides information about products that are in demand but are not yet available on the market to operators of online shopping malls. This enables operators of online shopping malls to propose highly unique products that are differentiated from existing products.

[0054] [3. Processing flow] Next, a processing procedure executed by the information processing device 1 according to the embodiment will be described with reference to Fig. 6. Fig. 6 is a flowchart showing an example of the processing procedure of the provision processing according to the embodiment.

[0055] 7, the information processing device 1 acquires a response history from the information providing device 200 (step S101). Subsequently, the information processing device 1 estimates the needs of each product from the acquired response history (step S102).

[0056] Next, the information processing device 1 extracts products that are in demand but are not on sale (step S103), and then provides content related to the extracted products (step S104).

[0057] [4. Modifications] In the above embodiment, the case where the needs for a product and the sales status of the product are estimated has been described, but the present invention is not limited to this. For example, the recognition level of a product may be estimated.

[0058] An example of product recognition will now be described with reference to Fig. 7. Fig. 7 is an explanatory diagram relating to product recognition according to an embodiment. For example, the information processing device 1 asks the model a question such as "What is AAA (product name)?" a predetermined number of times and acquires a response history.

[0059] The information processing device 1 classifies the answers included in the answer history into a plurality of categories, and obtains, for example, the histogram shown in Fig. 7. Note that Fig. 7 shows a case where the answers of the model are classified into categories F1 to F5, and it is assumed that recognition increases from category F1 to category F5.

[0060] In the example shown in Figure 7, the percentage for category F3 is the highest, indicating that the current awareness of "AAA" is at a level corresponding to category F3, and that the current awareness level is at the third level.

[0061] In this way, the information processing device 1 classifies each answer into each category and estimates the awareness of the product according to the proportion of these. This allows the awareness to be estimated appropriately. Note that the information processing device 1 may also ask the model a question such as, "Which demographic (user attribute) is it popular with?"

[0062] The information processing device 1 may also compare answers from multiple models trained using different data sources to estimate needs. For example, the same question may be asked to multiple models at the same time, and the answers may be compared to estimate needs. In other words, in this case, if one model and the other model give the same answer, it can be inferred that the level of understanding is low or that there are mixed opinions, and if both models give the same answer, it can be inferred that the answer has become common knowledge. Note that each model may be trained using data sources with different user demographics, for example.

[0063] The information processing device 1 may also estimate the degree of awareness of a product according to the degree of dispersion of answers to the same model. That is, the more dispersed the answers, the lower the level of understanding or the more controversial the product is, and the more convergent the answers, the more common knowledge it is.

[0064] Furthermore, in the above-described embodiment, the model outputs text as an answer, but the output from the model may be other content such as an image, music, or video.

[0065] [5. Effects] The information processing device 1 according to the embodiment includes an acquisition unit 41 that acquires a response history including questions about a product input to a model that generates responses to the input questions and responses from the model, and an estimation unit 42 that analyzes the response history acquired by the acquisition unit 41 and estimates needs for the product.

[0066] The estimation unit 42 estimates the needs from the number of questions about the product included in the answer history, and estimates the sales status of the product from the content of the answers included in the answer history. The information processing device 1 also includes a provision unit 43 that provides information about products whose needs estimated by the estimation unit 42 exceed a threshold and are not on sale.

[0067] The estimation unit 42 also classifies the answers included in the answer history into positive answers and negative answers, and estimates future needs for the product from changes in the trends between the positive answers and the negative answers.

[0068] By performing any one or a combination of the above-described processes, the information processing device according to the present application can estimate the needs for a product.

[0069] [6. Hardware Configuration] The information processing device 1 according to the embodiment described above is realized by, for example, a computer 1000 configured as shown in Fig. 8. Fig. 8 is a hardware configuration diagram showing an example of a computer that realizes the functions of the information processing device according to the embodiment. The computer 1000 has 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.

[0070] The CPU 1100 operates and controls each unit based on programs stored in the ROM 1300 or the HDD 1400. The ROM 1300 stores a boot program executed by the CPU 1100 when the computer 1000 starts up, programs that depend on the hardware of the computer 1000, and the like.

[0071] The HDD 1400 stores programs executed by the CPU 1100, data used by such programs, etc. The communication interface 1500 receives data from other devices via a network (communication network) N and sends the data to the CPU 1100, and transmits data generated by the CPU 1100 to other devices via the network N.

[0072] The CPU 1100 controls output devices such as a display and a printer, and input devices such as a keyboard and a mouse (in FIG. 8, 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 devices via the input / output interface 1600. The CPU 1100 also outputs generated data to the output devices via the input / output interface 1600.

[0073] Media interface 1700 reads a program or data stored in recording medium 1800 and provides it to CPU 1100 via RAM 1200. CPU 1100 loads the program or data from recording medium 1800 onto RAM 1200 via media interface 1700 and executes the loaded program. Recording medium 1800 is, for example, an optical recording medium such as a DVD (Digital Versatile Disc) or a PD (Phase Change Rewritable Disc), a magneto-optical recording medium such as an MO (Magneto-Optical disk), a tape medium, a magnetic recording medium, or a semiconductor memory.

[0074] For example, when the computer 1000 functions as the information processing device according to the embodiment, the CPU 1100 of the computer 1000 executes programs loaded onto the RAM 1200 to realize the functions of the control unit 4. The CPU 1100 of the computer 1000 reads and executes these programs from the recording medium 1800, but as another example, the CPU 1100 may obtain these programs from another device via the network N.

[0075] [7. Other] Although the embodiments of the present application have been described above, the present invention is not limited to the contents of these embodiments. Furthermore, the above-described components include those that can be easily imagined by a person skilled in the art, those that are substantially the same, and those that are within the scope of so-called equivalents. Furthermore, the above-described components can be combined as appropriate. Furthermore, various omissions, substitutions, or modifications of the components can be made without departing from the spirit of the above-described embodiments.

[0076] Furthermore, among the processes described in the above embodiments, 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 using a known method. In addition, the information including the processing procedures, specific names, various data, and parameters shown in the above documents and drawings can be changed as desired unless otherwise specified. For example, the various information shown in each drawing is not limited to the information shown in the drawings.

[0077] Furthermore, the components of each device shown in the figure are conceptual functional components and do not necessarily have to be physically configured as shown in the figure. In other words, the specific form of distribution and integration of each device is not limited to that shown in the figure, and all or part of them can be functionally or physically distributed and integrated in any unit depending on various loads, usage conditions, etc.

[0078] For example, the above-mentioned information processing device may be realized using multiple server computers, and depending on the function, the configuration can be flexibly changed, such as by calling an external platform using an API (Application Programming Interface) or network computing.

[0079] Furthermore, the above-described embodiments and modifications can be combined as appropriate within the scope of not causing any contradiction in the processing content.

[0080] Furthermore, the above-mentioned "section, module, unit" can be read as "means" or "circuit," etc. For example, an acquisition unit can be read as an acquisition means or an acquisition circuit. [Explanation of symbols]

[0081] 1. Information processing equipment 2. Communications Department 3 Storage section 4. Control Unit 31 Answer history memory section 41 Acquisition Department 42 Estimation part 43 Providing Department 100 user terminals 200 Information provision device

Claims

1. an acquisition unit that acquires a question about a product input to a model that generates an answer to the input question and an answer history including the answer generated by the model; an estimation unit that analyzes the response history acquired by the acquisition unit and estimates needs for the product; Equipped with The acquisition unit Obtaining answers to questions with the same content as questions included in the answer history from the model at a predetermined interval; The estimation unit The needs are estimated based on a time series change in the answers acquired at a predetermined interval.

1. An information processing device comprising:

2. The estimation unit Inferring the needs from the number of questions about the product included in the answer history, and inferring the sales status of the product from the content of the answers included in the answer history.

2. The information processing device according to claim 1,

3. The estimation unit Estimating the time when the product was sold from the time series change in the ratio of responses suggesting the sale of the product among the responses to the product 2. The information processing device according to claim 1,

4. The estimation unit Estimating the awareness of the product according to a dispersion degree indicating a dispersion state of responses to the same product among the responses included in the response history.

2. The information processing device according to claim 1,

5. a provision unit that provides information about products whose needs estimated by the estimation unit exceed a threshold and that are not on sale; To be prepared 2. The information processing device according to claim 1,

6. The estimation unit Classifying the answers included in the answer history into positive answers regarding the product and negative answers regarding the product, and estimating future needs for the product from changes in the ratio of the positive answers to the negative answers.

2. The information processing device according to claim 1,

7. 1. A computer-implemented information processing method, comprising: an acquisition step of acquiring an answer history including questions about products input to a model that generates answers to input questions and answers generated by the model; an estimation step of analyzing the response history acquired by the acquisition step and estimating needs for the product; Including, The obtaining step includes: Obtaining answers to questions with the same content as questions included in the answer history from the model at a predetermined interval; The estimation step includes: The needs are estimated based on a time series change in the answers acquired at a predetermined interval.

1. An information processing method comprising:

8. an acquisition step of acquiring an answer history including questions about products input to a model that generates answers to input questions and answers generated by the model; an estimation step of analyzing the response history acquired by the acquisition step and estimating needs for the product; on the computer, The acquisition procedure includes: Obtaining answers to questions with the same content as questions included in the answer history from the model at a predetermined interval; The estimation procedure comprises: The needs are estimated based on a time series change in the answers acquired at a predetermined interval. An information processing program characterized by:

Images