Information processing device, information processing method, and program

Abstract

The present invention provides an information processing device capable of improving the accuracy of predicting the future operating status of gaming machines for each specific model. [Solution] The information processing device 12 has a processor 26 that performs processing, and the processor 26 is configured to perform: a first process of acquiring web content and amusement store information; a second process of determining the models of amusement machines included in the web content and the usage status of the web content; a third process of determining the operating status of amusement machines included in the amusement store information; a fourth process of determining whether or not there is a correlation between the operating status of amusement machines and the usage status of web content; and a fifth process of predicting the future operating status of amusement machines installed in amusement stores if it is determined that there is a correlation between the operating status of amusement machines and the usage status of web content.

Description

[Technical Field]

[0001] This disclosure relates to an information processing device, an information processing method, and a program for processing information about the operation of a gaming parlor. [Background technology]

[0002] An example of an information processing device for processing information about the operation of amusement parlors is disclosed in Patent Document 1 and Patent Document 2. The information processing device described in Patent Document 1 is an information processing device comprising: means for acquiring first store information regarding the operation of resources at a target store; means for acquiring second store information regarding the operation of resources at competing stores of the target store; means for acquiring customer information regarding the customer visit status at the target store; and means for creating a plan for performance indicators of a target store by applying a trained model to model input data based on at least the first store information, the second store information, and the customer information.

[0003] Furthermore, the gaming information management system described in Patent Document 2 is a gaming information management system for a gaming parlor where multiple types of gaming machines are installed, and includes a posting collection means that collects posts from players on a predetermined SNS site regarding the new gaming machine, with a predetermined period before and after the day the new gaming machine is introduced as the target period.

[0004] Furthermore, the gaming information management system described in Patent Document 2 includes a post count calculation means for calculating the number of posts collected by a post collection means, an operation data calculation means for calculating operation data showing the actual operating status after a new gaming machine has been introduced, and a learning model generation means for performing machine learning using the post count and operation data for each machine model as training data to generate a learning model for predicting the operating status of the gaming machine. [Prior art documents] [Patent Documents]

[0005] [Patent Document 1] Japanese Patent Publication No. 2023-162787 [Patent Document 2] Japanese Patent Publication No. 2025-37390 [Overview of the project] [Problems that the invention aims to solve]

[0006] The inventors of this application recognized that the information processing device described in Patent Document 1 does not recognize the model of the gaming machine, and that the gaming information management system described in Patent Document 2 has limitations on the amount of training data used for machine learning of the learning model when the number of models released per year is small, resulting in a decrease in the accuracy of predicting the future operating status of each gaming machine model.

[0007] The purpose of this disclosure is to provide an information processing device, an information processing method, and a program that can improve the accuracy of predicting the future operating status of gaming machines for each type of gaming machine. [Means for solving the problem]

[0008] This embodiment includes an information processing device having a processor that is communicably connected to a content provisioning computer via a network and executes processing by running a non-temporary program, wherein the processor performs a first process of acquiring web content posted by a poster to the content provisioning computer and amusement store information of an amusement store where amusement machines are installed; a second process of determining the model of the amusement machine included in the web content and the usage status of the web content; a third process of determining the operating status of the amusement machine included in the amusement store information; and the amusement machine of a predetermined model installed in the amusement store. Disclosed is an information processing device configured to perform the following: a fourth process of determining whether there is a correlation between the operating status of the gaming machine and the usage status of the web content including the gaming machine of a predetermined model; and, if it is determined that there is a correlation between the operating status of the gaming machine of a predetermined model installed in the amusement parlor and the usage status of the web content including the gaming machine of a predetermined model, a fifth process of predicting the future operating status of the gaming machine of a predetermined model installed in the amusement parlor using the operating status of the gaming machine of a predetermined model installed in the amusement parlor and the usage status of the web content including the gaming machine of a predetermined model. [Effects of the Invention]

[0009] According to this embodiment, it is possible to improve the accuracy of predicting the future operating status of gaming machines for each model of gaming machine. [Brief explanation of the drawing]

[0010] [Figure 1] This is a schematic diagram showing an example of the configuration of an information processing system. [Figure 2] This is a schematic diagram showing an example of the configuration of an information processing device. [Figure 3] This is a schematic diagram showing an example configuration of the contributor's computer, the content provider's computer, and the user's computer. [Figure 4] This flowchart shows an example of an information processing method performed by an information processing device. [Modes for carrying out the invention]

[0011] (overview) In this embodiment, several specific examples of information processing systems, information processing devices, information processing methods, and programs are described with reference to the drawings. Figure 1 shows an example of an information processing system 10. The information processing system 10 may consist of a trade area 11, an information processing device 12, a contributor computer 70, a content provider computer 13, and a user computer 60. The trade area 11 is a geographical area that exists in different regions. Each trade area 11 has multiple amusement parlors 14. The multiple amusement parlors 14 may each be managed by a person in charge. The person in charge may be an individual, a company, a corporation, an organization, etc.

[0012] The amusement parlor 14 is an amusement facility equipped with numerous gaming machines (game machines) 15. The amusement parlor 14 is also equipped with a hall computer 16 that is connected to all of the numerous gaming machines 15 in a communication manner, and a gaming parlor computer 17 that is connected to the hall computer 16 in a communication manner.

[0013] The information processing device 12 may be connected to the content providing computer 13 via a network 18 so that they can communicate with each other. The content providing computer 13 may be connected to the contributor computer 70 and the user computer 60 via a network 18 so that they can communicate with each other.

[0014] Network 18 is a communication line for transmitting various types of information, and Network 18 can be implemented by, for example, the Internet or a wide area network. The various types of information may include information, data, commands, requests, folders, files, etc. Network 18 may consist of base stations, radio towers, communication antennas, repeaters, communication circuits, communication cables (copper wires, optical fibers), etc.

[0015] Network 18 is realized by one or more communication means, either wireless communication or wired communication. Wireless communication includes short-range wireless communication. Short-range wireless communication includes, for example, wireless LAN (Wi-Fi (registered trademark)), Bluetooth (registered trademark). Wireless communication includes electrical signals, optical signals, radio waves, infrared rays, satellite communication, etc. The signals used for communication include digital signals and analog signals.

[0016] (Configuration of the game parlor) The configuration inside the game parlor 14 will be specifically described. There are multiple models of the gaming machines 15. The models of the gaming machines 15 may be distinguished by, for example, pachinko, pachislot, smart slot, smart pachinko, etc. Pachinko is configured such that when balls enter the start checker, digital displays and the like change, and when the patterns align, it is a big win. Pachislot is configured to insert medals and spin the reels, and obtain medals by aligning specific symbols. Smart slot is a gaming machine that can be used without medals by managing the number of medals and credits with a dedicated card reader unit and a pachislot machine. Smart pachinko is a gaming machine in which balls are enclosed inside the machine, the balls circulate inside, and the held balls are managed electronically. Each gaming machine 15 may have an insertion slot for a membership card.

[0017] The models of the gaming machines 15 may be distinguished by, for example, the diameters of the medals of pachislot being 25 mm and 30 mm, etc. The models of the gaming machines 15 may be distinguished by different manufacturing manufacturers and suppliers. Furthermore, the models of the gaming machines 15 may be distinguished by the model names of the gaming machines 15, for example, XX Girl, XX Sekigahara, XX Battleship, XX Story, Golden XX, XX's Fist, etc. And when the models of the gaming machines 15 are different, the age group or gender of the players using the gaming machines 15 may be different. Also, when the regions of the game parlors 14 are different, the models of the gaming machines 15 provided in the game parlors 14 may also be different. The regional classification of the game parlors 14 may be, for example, prefectures or municipalities.

[0018] The hall computer 16 acquires and transmits to the arcade computer 17 information about each gaming machine 15, such as the machine number that identifies each gaming machine 15, the total number of gaming machines 15, the model name of each gaming machine 15, the actual daily operating time of each gaming machine 15, the daily number of balls dispensed by each gaming machine 15, the number of big wins, the number of bonuses, the number of near misses, the number of fevers, the usage status of the ATMs installed in the arcade 14, and the sales status of prepaid cards and IC cards in the arcade 14. The gaming machine information is associated with the machine number of each gaming machine 15.

[0019] The amusement parlor computer 17 receives output signals from the hall computer 16, camera 19, seat sensor 21, parking management machine 22, etc. Multiple cameras 19 are installed inside the amusement parlor 14 and generate output signals by capturing images of the inside of the amusement parlor 14. The seat sensor 21 detects the elapsed time a player is seated in a chair in front of a gaming machine 15 and generates an output signal.

[0020] The parking management machine 22 detects the number of vehicles entering and exiting the parking lot on the premises of the amusement parlor 14, the duration of stay of vehicles in the parking lot, etc., and generates output signals. The amusement parlor computer 17 is connected to an input device 23 and an output device 24 in a communication manner. The input device 23 is implemented by a keyboard and mouse, etc.

[0021] The person in charge of the amusement parlor 14 may input the business information of the amusement parlor 14 by operating the input device 23. The business information of the amusement parlor 14 may include, for example, the business days of the amusement parlor 14, the business hours of the amusement parlor 14, the work shift status of employees at the amusement parlor 14, employee placement data within the amusement parlor 14, the set temperature of the air conditioning system within the amusement parlor 14, the number and placement of lighting devices within the amusement parlor 14, and so on.

[0022] The output device 24 is implemented by a display, speaker, printer, etc. The display is implemented by, for example, a liquid crystal display or an organic electroluminescent display. Various information and data may be displayed on the display. The printer prints various information onto recording paper using ink or toner. The speaker outputs sound information. The output device 24 may also output various information acquired from the information processing device 12.

[0023] The amusement parlor computer 17 has a known configuration including a processor, main memory, auxiliary storage, communication device, etc. The processor may be composed of a central processing unit (CPU) which integrates an arithmetic unit (arithmetic circuit) and a control unit (control circuit). The processor is connected to the main memory, auxiliary storage, communication device, etc. via a communication bus so as to be able to communicate.

[0024] The main memory is a volatile memory device and may be implemented by semiconductor memory such as DRAM (Dynamic Random Access Memory) or SRAM (Static Random Access Memory). The auxiliary memory is a non-temporary storage medium. The auxiliary memory is sometimes understood as storage. The auxiliary memory may be implemented by any of the following: magnetic disks, optical disks, or flash memory. The communication device is implemented by, for example, communication circuits, communication cables, communication ports, antennas, etc.

[0025] The processor may operate a program stored in an auxiliary storage device, and may also process the output signals from the camera 19, the seat sensor 21, and the parking management machine 22. The processor generates control signals to be transmitted to the output device 24. The amusement parlor computer 17 can also transmit various information to the information processing device 12. The amusement parlor computer 17 can also receive various information from the information processing device 12.

[0026] (Configuration of information processing device) The information processing device 12 is a computer managed and operated by an administrator. The information processing device 12 is capable of transmitting various types of information to the amusement parlor computer 17. The information processing device 12 is capable of receiving various types of information from the amusement parlor computer 17. The information processing device 12 is located at a predetermined IP address on the network 18. The information processing device 12 is a computer implemented using various hardware and software components. The software includes an operating system and applications.

[0027] The information processing device 12 may have hardware such as a main unit (casing), ROM (Read Only Memory) 25, processor 26, main memory 27, auxiliary memory 28, media drive device 29, input device 50, output device 20, and communication device 30. The ROM 25 is a data read-only memory and the data written to it during manufacturing is not modified afterward. The ROM 25 stores the program that is executed first when the information processing device 12 starts up, such as the IPL (Initial Program Loader). The ROM 25 is a non-volatile memory device.

[0028] The processor 26 is located in the main body of the information processing device 12 and may be configured as a central processing unit (CPU) that integrates an arithmetic unit (arithmetic circuit) and a control unit (control circuit). The processor 26 is communicatively connected to the ROM 25, main memory 27, auxiliary memory 28, input device 50, output device 20, media drive device 29, and communication device 30 via a communication bus 31. The processor 26 comprehensively controls other devices and circuits located inside the main body and devices and circuits located outside the main body.

[0029] Furthermore, the processor 26 may be a multiprocessor. The processor 26 may be a combination of two or more elements from among, for example, a CPU, an MPU (Micro Processing Unit), a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), a PLD (Programmable Logic Device), an FPGA (Field Programmable Gate Array), and a GPU (Graphics Processing Unit).

[0030] The processor 26 may perform various processes by running a program. The processes performed by the processor 26 include calculations, decisions, learning, comparisons, identifications, classifications, analyses, inferences, regressions, suggestions, controls, calculations, and generation.

[0031] The processes performed by the processor 26 may include processing various types of information, storing various types of information in the auxiliary storage device 28, reading various types of information from the auxiliary storage device 28, obtaining various types of information from the amusement store computer 17, transmitting various types of information to the amusement store computer 17, and obtaining various types of information from the content provision computer 13. The various types of information processed by the processor 26 may include information, data, commands, signals, files, etc.

[0032] The main memory 27 is a volatile memory and may be implemented by semiconductor memory such as DRAM (Dynamic Random Access Memory) or SRAM (Static Random Access Memory). The processor 26 can perform processes to write various information to the main memory 27 and processes to read various information from the main memory 27. The main memory 27 functions as a work area and buffer area for storing programs, data, instructions, etc., retrieved from the auxiliary memory 28 when the processor 26 processes and executes such programs, data, instructions, etc.

[0033] The auxiliary storage device 28 is a non-temporary storage medium. The auxiliary storage device 28 may also be understood as storage. The auxiliary storage device 28 may be located inside the main unit, or it may be located outside the main unit and connected to the communication bus 31 by wireless or wired communication. The auxiliary storage device 28 operates according to input and output commands from the processor 26.

[0034] The auxiliary storage device 28 may be implemented by, for example, a magnetic disk, an optical disk, or flash memory. The magnetic disk is a storage device that can magnetically write and read various types of data to and from the storage medium 28A, and the storage medium 28A may be implemented by, for example, an HDD (Hard Disk Drive) or a floppy disk.

[0035] An optical disc is a storage device that can write various types of information to a storage medium 28A by irradiating it with laser light, and read various types of information. The storage medium 28A can be implemented as, for example, a CD (Compact Disc), a DVD (Digital Versatile Disc), or a BD (Blu-ray® Disc).

[0036] Flash memory is a storage device that uses semiconductor memory, and the storage medium 28A may consist of an SSD (Solid State Drive), a USB memory (USB Flash Drive), or an SD card (Secure Digital Card).

[0037] The auxiliary storage device 28 may have non-temporary programs pre-stored in it. Furthermore, the auxiliary storage device 28 may store non-temporary programs read by the media drive device 29. Additionally, the auxiliary storage device 28 may have non-temporary programs downloaded from the content provision computer 13 via the network 18 installed. Furthermore, the auxiliary storage device 28 may store various information obtained from the game store computer 17 and the content provision computer 13.

[0038] The media drive device 29 is hardware into which a non-temporary storage medium 29A is inserted and removed. The storage medium 29A is portable and can be implemented as, for example, a CD-ROM (Compact Disc Read Only Memory), a DVD, etc. The storage medium 29A may store a program that is operated by the processor 26.

[0039] The program stored in the storage medium 29A is installed into the auxiliary storage device 28 and then stored in the main memory device 27, making the program executable by the processor 26. The storage medium 29A of the media drive device 29 may also store various types of information. The various types of information stored in the storage medium 29A may also be stored in the auxiliary storage device 28.

[0040] The input device 50 is implemented by devices such as a keyboard, mouse, microphone, and reader. The administrator of the information processing device 12 may input various information, commands, and signals to the information processing device 12 by using the input device 50. The administrator of the information processing device 12 may specify a forecast period for the future operating status of the gaming machine 15 by using the input device 50. The administrator of the information processing device 12 may specify multiple mutually different periods, for example, a first period or a second period, as the forecast period for the future operating status of the gaming machine 15.

[0041] The output device 20 is implemented by a display, speaker, printer, etc. The display may be, for example, a liquid crystal display or an organic electroluminescent display. Various information and data may be displayed on the display. The printer prints various information onto recording paper using ink or toner. The speaker outputs sound information. The output device 20 may output various information.

[0042] The communication device 30 includes devices, equipment, and standards for connecting the information processing device 12 to the amusement store computer 17 and the content provision computer 13 via the network 18 using at least one of either a wireless communication system or a wired communication system. The hardware constituting the communication device 30 may consist of, for example, a network adapter, a network interface card, a communication cable, a communication antenna, a communication port, a communication circuit, etc.

[0043] The processor 26 may implement various functional components shown in Figure 2 by running non-temporary programs and cooperating with various hardware components constituting the information processing device 12. For example, the processor 26 may implement various information processing units 33, web content processing units 32, amusement store information processing units 34, correlation determination units 35, operating status prediction units 52, artificial intelligence units 36, etc.

[0044] The various information processing units 33 may, in cooperation with the artificial intelligence unit 36 ​​and the auxiliary storage device 28, process various information acquired from the content provision computer 13, various information acquired via the input device 50, and various information acquired from the game store computer 17, and store the processing results in the auxiliary storage device 28.

[0045] The various information processing units 33 may process sound information and store the processing results in the auxiliary storage device 28. The sound information may include human voices, music, and noise. The various information processing units 33 may convert the sound information into text data by performing sampling and quantization processing.

[0046] Furthermore, the various information processing units 33 may perform filtering processing to emphasize sounds in a specific frequency band. By performing filtering processing, the various information processing units 33 can achieve things like clarifying human-generated speech and removing noise. The various information processing units 33 may also work in cooperation with the artificial intelligence unit 36 ​​to perform processes such as analyzing the meaning of words in speech and identifying the characteristics of the speaker.

[0047] Furthermore, the various information processing units 33 may process image information and store the processing results in the auxiliary storage device 28. The image information processed by the various information processing units 33 may include still images, videos, images, photographs, illustrations, etc. The various information processing units 33 may, in cooperation with the artificial intelligence unit 36, perform image modification, filtering, transformation, synthesis, etc. The various information processing units 33 may also process acquired text data and store the processing results in the auxiliary storage device 28.

[0048] The various information processing units 33 may determine the attributes of the uploader of the uploaded video. The meanings of uploaded video and uploader attributes will be described later. The various information processing units 33 may also have a function to determine whether the models of the gaming machines 15 included in the web content and operational information are competing models. The meaning of operational information will be described later. Competing models may include gaming machines 15 installed in gaming parlors 14 operated by different companies, and gaming machines 15 manufactured and supplied by different manufacturers. The various information processing units 33 may determine whether predetermined conditions are met by processing the usage status of the web content and the gaming parlor information. The meanings and specific examples of the usage status of the web content, the gaming parlor information, and the predetermined conditions will be described later.

[0049] The web content processing unit 32 may process the web content acquired from the content providing computer 13 to determine the usage status of the web content and store the determination result in the auxiliary storage device 28. The web content processing unit 32 may also process the web content in cooperation with the artificial intelligence unit 36 ​​and the auxiliary storage device 28 to determine the model of the gaming machine 15 included in the web content and store the determination result in the auxiliary storage device 28.

[0050] The web content processing unit 32 may obtain "viewing metrics for posted videos" related to the gaming machine 15. Specifically, it uses the model name of the gaming machine 15, the name of the gaming parlor, the name of the poster, etc., entered by content user A2 from the input device 62 as a search query, and searches for posted videos containing the corresponding model via API (Application Programming Interface) integration.

[0051] Furthermore, for each searched posted video, the following items may be obtained: video title, description, posting date, number of views, number of likes and dislikes given by content user A2 who watched the video, number of comments by content user A2 who watched the video, etc. In other words, "viewing metrics for posted videos" may be obtained and stored in the auxiliary storage device 28. The description of the posted video may include items such as the name of the amusement arcade, the location of the amusement arcade, the model name of the amusement machine, and the date the amusement machine was introduced.

[0052] Furthermore, the web content processing unit 32 may classify the posted videos included in the web content into multiple categories with different posting periods. For example, starting from the date of introduction of the gaming machine 15 at the gaming parlor 14, videos posted "8 weeks to 4 weeks before the introduction date" may be classified as "teaser videos," videos posted "3 weeks to 2 weeks before the introduction date" as "test play videos," videos posted "1 week before the introduction date to the week including the introduction date" as "introduction videos," and videos posted in weeks after the week including the introduction date as "explanatory videos."

[0053] Furthermore, the web content processing unit 32 may determine and analyze the category of the posted video, the number of views of the posted video during a predetermined period, the retention rate (view rate) of the posted video during a predetermined period, the evaluation content, comments, etc., and based on the results of that determination and analysis, it may estimate the change in the level of interest of content user A2. The retention rate of the posted video during a predetermined period is, for example, Video retention rate (%) = Average viewing time / Video length × 100 You may also request it as follows:

[0054] Furthermore, the web content processing unit 32 may calculate the approval rating for each posted video. The approval rating for a posted video is an indicator that shows how much content user A2 has watched the posted video. For example, the web content processing unit 32 may calculate the approval rating for each posted video based on the number of high ratings and low ratings obtained. Alternatively, the web content processing unit 32 may calculate the approval rating for a posted video using the following formula.

[0055] Approval rating of submitted videos = (Share of submitted video views / Share of submitted videos) × 100 In the above formula, "posted video playback share" means the ratio of the number of plays for the relevant model to the total number of plays for all posted videos within a specified period. Similarly, "posted video number share" means the ratio of the number of videos for the relevant model to the total number of posted videos within a specified period. The posted video support rate indicator shows "how much higher the number of plays per posted video is compared to the overall average number of plays for all posted videos."

[0056] Furthermore, the web content processing unit 32 may calculate the number of views for each posted video for each model of the gaming machine 15, and from the calculation results, calculate the approval rating of the posted video.

[0057] Furthermore, the web content processing unit 32 may work with the artificial intelligence unit 36 ​​to analyze the content of the comments using natural language processing technology and calculate a positive ratio. The positive ratio is the ratio of positive comments to negative comments. Positive comments may include, for example, "It's not boring even with long playtimes," "It has a deep system and strategic depth," and "It's immersive and has replayability." Negative comments may include, for example, "It lacks gambling elements," and "The scenario is too ordinary."

[0058] The amusement parlor information processing unit 34 may determine the operating status items for each type of amusement machine 15, that is, the operating indicators, based on the amusement parlor information obtained from the amusement parlor computer 17, and store the determination results in the auxiliary storage device 28.

[0059] The correlation determination unit 35 may include a function to calculate a correlation coefficient and a function to determine whether or not there is a correlation between the operating status of each type of gaming machine 15 and the usage status of web content including the gaming machines 15. The meaning and calculation examples of the correlation coefficient, and specific examples of determining whether or not there is a correlation will be described later.

[0060] The operating status prediction unit 52 may have a function to determine whether or not to predict the future operating status of each type of gaming machine 15, a function to predict the future operating status of each type of gaming machine 15, and a function to output prediction information including the results of the prediction of the future operating status. The operating status prediction unit 52 may also have a function to predict the future operating status of each competing type of gaming machine 15. Specific examples of how the operating status prediction unit 52 predicts the future operating status of each type of gaming machine 15 will be described later.

[0061] When the program is run, the artificial intelligence unit 36 ​​may cooperate with various information processing units 33, web content processing unit 32, amusement store information processing unit 34, operating status prediction unit 52, and auxiliary storage device 28 to perform various processes. The processes performed by the artificial intelligence unit 36 ​​include learning processes (learning stage) and inference processes (inference stage). The various information used by the artificial intelligence unit 36 ​​to perform the processes includes information, data, signals, commands, files, various models, etc. The data includes video data, sound data, and text data.

[0062] The artificial intelligence unit 36 ​​outputs processing results (output data) by processing the input learning target data with a learning model during learning processing, for example, machine learning processing. The artificial intelligence unit 36 ​​outputs inference results by processing the inference target data with a learning model during inference processing. In this embodiment, the inference target data is obtained from the amusement store computer 17 and the content provision computer 13.

[0063] The artificial intelligence unit 36 ​​may extract features from the input data using machine learning. The input data processed by the artificial intelligence unit 36 ​​may include text data, audio information, video information, etc. Feature extraction from the input data includes classification and regression. Classification is the process of classifying and identifying features. Features may include regularities in the input data. Regression includes understanding the overall trend of the classified features, predicting the future state of the features, etc. The learning model is stored in the auxiliary memory device 28, and the learning model is trained as the artificial intelligence unit 36 ​​repeats machine learning.

[0064] The machine learning performed by the artificial intelligence unit 36 ​​may include three types: supervised learning, unsupervised learning, and reinforcement learning. In supervised learning, the artificial intelligence unit 36 ​​uses a loss function to calculate the error between the processing result and the ground truth data, and trains the learning model based on that error. Specifically, it adjusts weights, biases, etc., to minimize the error. The artificial intelligence unit 36 ​​trains the learning model by comparing the output data with the ground truth data (ground truth labels).

[0065] Unsupervised learning is a method of training a model using training data that does not contain correct answers, and it involves classifying the training data into groups of data with similar features. Reinforcement learning involves repeatedly processing input data with a learning model to obtain output data, and training the learning model so that it can maximize rewards by acting according to the output data.

[0066] The artificial intelligence unit 36 ​​can use a neural network as a learning model to realize machine learning. A neural network has an input layer, an intermediate layer (hidden layer), and an output layer. The intermediate layer is configured to convert the input information into a format that is useful for the output layer. Furthermore, the artificial intelligence unit 36 ​​can perform deep learning in realizing the intermediate layer of the neural network.

[0067] Furthermore, the artificial intelligence unit 36 ​​may perform tasks such as analyzing and interpreting text data, generating prompts, and generating sentences of inference results corresponding to the prompts, using the functions of a large-scale language model. The analysis and interpretation of chat content includes analyzing and interpreting text data, and converting audio data into text data for analysis and interpretation.

[0068] When the artificial intelligence unit 36 ​​functions as a generative artificial intelligence unit, it can perform text generation, image generation, video generation, and speech generation. Text generation is a function that, when a prompt (in text format), such as an instruction or question, is input, analyzes the content and intent of the prompt and uses the information and data stored in the auxiliary storage device 28 to automatically generate a response (in text format) to the prompt. Because a large-scale language model is used, natural and highly accurate responses can be obtained.

[0069] Image generation is a function that automatically generates an original image similar to the prompt's image by using the information and data stored in the auxiliary storage device 28 in response to the input prompt (in text format).

[0070] The video generation function automatically generates an original video that closely resembles the image of the prompt (in text format) by using the information and data stored in the auxiliary storage device 28 in response to the input prompt. The audio generation function automatically generates original audio data (optimal actions, responses, music, etc.) by using the information and data stored in the auxiliary storage device 28 in response to the input prompt (in voice or text format).

[0071] In this embodiment, the learning model stored in the model storage unit 42 is trained by supervised learning using image information, sound information, and text data including the gaming machine, and correct labels including the gaming machine model name. In addition, the learning model stored in the model storage unit 42 is trained by unsupervised learning that identifies and classifies the gaming machine model using image information, sound information, and text data including the gaming machine.

[0072] Furthermore, the auxiliary storage device 28 may be implemented including various information storage units 38, a program storage unit 41, a model storage unit 42, etc., as shown in Figure 2. The various information storage units 38 store information about the amusement parlor 14, various information obtained from the content provision computer 13, various information used by the processor 26 to perform various processes, and various information used by the artificial intelligence unit 36 ​​to perform learning and inference processes as a result of the processor 26 performing various processes. Various mathematical formulas used in the information processing method may also be stored in the various information storage units 38.

[0073] The program storage unit 41 may store applications that are operated by the processor 26. The applications stored in the program storage unit 41 include non-temporary programs, manuals, configuration files, data storage files, data, various libraries, etc. The processor 26 may execute the information processing method by reading and operating non-temporary programs stored in the program storage unit 41. Alternatively, the processor 26 may execute the information processing method by reading and operating non-temporary programs stored in the storage medium 29A of the media drive device 29. The model storage unit 42 stores learning models and large-scale language models that realize the artificial intelligence unit 36, multiple regression models used to predict the future operating status of the gaming machine 15, etc.

[0074] (Description of the content-providing computer) The content-providing computer 13 may provide web content to user computers 60 accessed via the network 18. The content-providing computer 13 includes a processor 80, a storage device 81, a communication device 82, etc. The content-providing computer 13 provides a website via a predetermined URL (Uniform Resource Locator) on the network 18.

[0075] The website publishes web content, such as gaming information about players using amusement parlors. This gaming information is obtained from the contributor's computer 70 and processed by the content provider computer 13. The gaming information includes, for example, submitted videos, which may consist of image information, sound information, text data, etc.

[0076] Game information is information transmitted by poster A1, including players, to the user computer 60 regarding the gaming machine 15. Game information may include, for example, posted videos, audio information, photos, text data, etc. Posted videos are videos posted by the poster to the network 18 for others, and may include teaser videos of the gaming machine 15, test play videos of the gaming machine 15, introductory videos of the gaming machine 15, explanatory videos of the gaming machine 15, etc. Teaser videos may show fragments of the gaming machine 15's model name and part of the main unit, as well as silhouettes of the characters that appear.

[0077] A test play video may be a video that shows someone playing the gaming machine 15, conveying its functions, gameplay, and effects in an experiential way. An introductory video should clearly convey the features and appeal of the gaming machine 15 as a whole, and may summarize its main functions, installed systems, and key points of its effects. An explanatory video may be a video that provides a detailed explanation of specific functions, systems, or effects of the gaming machine 15, or delves deeply into how to play or strategies.

[0078] Gaming information may include the region of the 14 gaming establishments used by poster A1, the name of the gaming establishment, the model name of the 15 gaming machines, poster A1's attributes, etc. Poster A1's attributes are poster A1's profile and may include items such as poster A1's gender, age, gender, and whether they are a professional or amateur. Professionals in the gaming industry are those who make a living from pachinko and pachislot, and amateurs in the gaming industry are those who do not make a living from pachinko and pachislot.

[0079] The processor 80 may determine the usage status of the web content by the user computer 60 and store the results in the storage device 81. The processor 80 may also transmit various information, including the web content and the usage status of the web content, to the information processing device 12.

[0080] (Description of the poster's computer) The poster computer 70 may be operated by an unspecified number of posters A1. Poster A1 may be a person who has gone to the amusement parlor 14 and used the amusement machine 15. The poster computer 70 has a processor 71, an input device 72, an output device 73, a storage device 74, a communication device 75, etc.

[0081] The processor 71 may be implemented by a combination of one or more elements from among CPU, MPU, DSP, ASIC, PLD, FPGA, GPU, etc. The input device 72 may be implemented by a mouse, keyboard, camera, microphone, display, etc. The output device 63 may be implemented by a display, speaker, headphones, earphones, etc. Poster A1 may use the input device 72 to create game information and store the game information in the storage device 74. Specifically, poster A1 may use the camera to create a video to post, use the microphone to create audio information, and use the mouse, keyboard, and display buttons to create text data.

[0082] The storage device 74 is a non-temporary storage medium. The storage device 74 may be implemented by, for example, a magnetic disk, an optical disk, or flash memory. The communication device 65 is implemented by, for example, a communication circuit, a communication cable, a communication port, an antenna, etc.

[0083] The processor 71 is connected to the input device 72, output device 73, storage device 74, and communication device 75 via a communication bus, and performs various processes. The processor 71 may process game information input from the input device 72 and store it in the storage device 74. The processor 71 may also transmit game information input to the submitter computer 70 to the content providing computer 13.

[0084] Poster A1 may input posting information into poster computer 70 and transmit the posting information from poster computer 70 to content provider computer 13 while using the gaming machine 15 inside the gaming parlor 14. Alternatively, poster A1 may input posting information into poster computer 70 and transmit the posting information from poster computer 70 to content provider computer 13 while outside the gaming parlor 14.

[0085] (Description of the user's computer) The user computer 60 may be operated by an unspecified number of content users A2. Content users A2 may be people who have gone to the amusement parlor 14 and used the amusement machine 15, people who may go to the amusement parlor 14 and use the amusement machine 15, people who have an interest in the amusement machine 15, etc. The user computer 60 has a processor 61, an input device 62, an output device 63, a storage device 64, a communication device 65, etc.

[0086] The processor 61 may be implemented by a combination of one or more elements from among CPU, MPU, DSP, ASIC, PLD, FPGA, GPU, etc. The input device 62 may be implemented by a mouse, keyboard, display, etc. Content user A2 can search for posted videos by operating the input device 62 and entering the model name of the gaming machine 15, the name of the gaming parlor, the name of the poster, a predetermined URL from which the posted video can be obtained, etc. Content user A2 may also view posted videos, input high and low ratings, comments, etc., and send them to the content providing computer 13 by operating the input device 62.

[0087] The output device 63 may be implemented by a display, speaker, headphones, earphones, etc. The storage device 64 is a non-temporary storage medium. The storage device 64 may be implemented by, for example, a magnetic disk, optical disk, or flash memory. The communication device 65 may be implemented by, for example, a communication circuit, communication cable, communication port, antenna, etc.

[0088] The processor 61 is connected to the input device 62, output device 63, storage device 64, and communication device 65 via a communication bus, and performs various processes. The processor 61 may also control the output device 63 to output various information, such as web content.

[0089] Content user A2 may have user computer 60 access the website provided by content provider computer 13 and obtain web content on user computer 60. Content user A2 may also operate user computer 60 to output the web content on output device 63. Therefore, content user A2 can view the game information contained in the web content.

[0090] (An example of an information processing method) The information processing device 12 may execute the information processing method shown in Figure 4. In step S10, the information processing device 12 may acquire web content from the content provision computer 13 and also acquire amusement parlor information from the hall computer. Note that the web content acquired by the information processing device 12 from the content provision computer 13 may have supplementary information attached to it. The meaning of supplementary information will be explained later.

[0091] The amusement parlor information may consist of image information, sound information, and text data. The amusement parlor information is information related to the amusement parlor 14 and may include, for example, basic information and operational information. The basic information may include the name of the operating company of the amusement parlor 14, the location (address) of the amusement parlor 14, the business days and hours of the amusement parlor 14, a unique amusement parlor identifier that identifies the amusement parlors 14 from each other, an account, etc. The location of the amusement parlor 14 identifies the trading area where the amusement parlor computer 17 is installed, that is, the location, and includes the prefecture, city, town, and street address, etc. The amusement parlor identifier, which is unique to identify the amusement parlor 14, may consist of a combination of symbols and numbers, or a combination of a regional name and numbers, etc.

[0092] Each account is unique to identify the gaming parlor computer 17, which is set up for each gaming parlor 14, and may consist of an ID and a password. The account is associated with the location of the gaming parlor 14 and the gaming parlor identifier. When the gaming parlor computer 17 is connected to the information processing device 12, the IP address of the gaming parlor computer 17 on the network 18 is transmitted to the information processing device 12.

[0093] Operational information consists of gaming machine information and player information. Gaming machine information may include items such as the machine number that identifies each gaming machine 15, the total number of gaming machines 15 installed in the gaming parlor 14, the model name of each gaming machine 15, the daily operating hours and number of players for each gaming machine 15, the number of coins inserted into each gaming machine 15 per day, the number of payouts per day for each gaming machine 15, the number of balls dispensed per day for each gaming machine 15, the number of jackpots per day for each gaming machine 15, the number of bonuses per day for each gaming machine 15, the number of near misses per day for each gaming machine 15, the number of fevers per day for each gaming machine 15, and the daily time that players are seated in the seats of each gaming machine 15. The model name of the gaming machine 15 may include the name of the manufacturer of the gaming machine 15. Gaming machine information is associated with the machine number of the gaming machine 15.

[0094] Player information refers to information about players who visit the amusement parlor 14, and may include player behavior data and player payment data. Player information may include items such as: usage history of the amusement parlor 14 based on membership information, vehicle dwell time in the parking lot, player movement patterns and traffic flow data within the amusement parlor 14, cashless payment information of players within the amusement parlor 14, cash acquisition status of players using ATMs within the amusement parlor 14, sales status of prepaid cards and IC cards within the amusement parlor 14, player credit information, and player segment information.

[0095] The player segment information is stored on the membership card. The player segment information may include the player's gender and age, family structure, residential area, etc. The arcade computer 17 obtains player movement patterns and traffic flow data within the arcade 14 by processing the video from the camera 19.

[0096] In step S11, the information processing device 12 may process the web content to determine the model of the gaming machine 15 included in the web content, and determine the usage status of the content for each determined model of gaming machine 15. The information processing device 12 processes the web content to determine the model of the gaming machine 15 that appears in the web content.

[0097] To explain in more detail, when image information, sound information, and text data are input as data to be inferred, the artificial intelligence unit 36 ​​of the information processing device 12 analyzes the data to be inferred using a learning model and can determine the model of the gaming machine 15.

[0098] Furthermore, in step S11, the information processing device 12 may classify the posted videos included in the web content into multiple categories with different posting times, such as "teaser videos," "test play videos," "introduction videos," and "explanatory videos." The posting time may be either "one day" or "multiple consecutive days." In addition, in step S11, the information processing device 12 may calculate the aforementioned "support rate of posted videos."

[0099] The artificial intelligence unit 36 ​​may determine the model of the gaming machine 15 from the image information, including the external shape of the gaming machine 15, the design and color of the external shape of the gaming machine 15, the characters attached to the gaming machine 15, the display content of the monitor installed on the gaming machine 15, the flashing and color of the lamps installed on the gaming machine 15, the special features and PUSH buttons installed on the gaming machine 15, etc.

[0100] The artificial intelligence unit 36 ​​may determine the model of the gaming machine 15 from the player's statements included in the sound information and the sound effects during the operation of the gaming machine 15. The artificial intelligence unit 36 ​​may also determine the model of the gaming machine 15 from the description and comments of the gaming machine 15 included in the text data.

[0101] The information processing device 12 may process supplementary information in step S11. The supplementary information may include the usage status of web content for each model of gaming machine 15. The usage status of web content for each model of gaming machine 15 is the status of the user computer 60 accessing the content provision computer 13 and using the web content, and may include the number of times the web content was played in a predetermined period, the amount of time the web content was viewed within the predetermined period, the time of day the web content was viewed, the region in which the web content was viewed, etc. The predetermined period used to determine the usage status of web content may be, for example, 30 consecutive days.

[0102] The information processing device 12 may determine the operating status of each type of gaming machine 15 in the gaming parlor 14 by processing the hall computer information in step S12. The operating status of each type of gaming machine 15 may include items such as the number of times each type is operated during a predetermined period, the number of players using each type during a predetermined period, and the amount of money spent on each type during a predetermined period. The average operating rate for each type during a predetermined period is, for example, the ratio of the number of gaming machines 15 that are actually in operation to the total number of predetermined types of gaming machines 15 installed in the gaming parlor 14. The predetermined period may be, for example, 30 consecutive days.

[0103] The information processing device 12 may execute steps S11 and S12 in parallel. Furthermore, the information processing device 12 may execute step S12 after the completion of step S11. Additionally, the information processing device 12 may execute step S11 after the completion of step S12.

[0104] The information processing device 12 may determine in step S13, following steps S11 and S12, whether a predetermined condition has been met. The predetermined condition may be, for example, that the region in which the amusement parlor 14 included in the web content is located matches the region in which the amusement parlor 14 included in the amusement parlor information is located.

[0105] Furthermore, the specified condition may be that the age range of the posters included in the web content matches the age range of the players included in the amusement parlor information. The age range of players may be distinguished as under 30, 30 to under 50, 51 and over, etc. Furthermore, the specified condition may be that the gender of the posters included in the web content matches the gender of the players included in the amusement parlor information.

[0106] The reason the information processing device 12 makes the decision in step S13 is that if the "process for predicting the future operating status of the gaming machine 15" described later is executed when the predetermined conditions are not met, the accuracy of predicting the future operating status of the gaming machine 15 may decrease.

[0107] The information processing device 12 may determine "Yes" in step S13 if one or more of the above-mentioned predetermined conditions are met. If the information processing device 12 determines "Yes" in step S13, it may calculate the correlation coefficient in step S14. The correlation coefficient is an index that shows the correspondence between the operating status of a predetermined model of gaming machine 15 and the usage status of web content including the predetermined model of gaming machine 15. The information processing device 12 may calculate the correlation coefficient r using the following formula 1, assuming Pearson's product-moment correlation coefficient.

[0108] r=[n·Σxiyi-(Σxi)(Σyi)] / √{[n·Σxi 2 -(Σxi) 2 ][n·Σyi 2 -(Σyi) 2 ]···(Equation 1) In this equation 1, n is the sample size (number of models) of the 15 gaming machines, Σxiyi is the sum of the products of the number of views of the posted videos × the number of times the 15 gaming machines were operated, Σxi is the total number of views of the posted videos, Σyi is the total number of times the 15 gaming machines were operated, and Σxi 2 Σyi is the sum of the squares of the number of plays for the gaming machine 15. 2 This is the sum of the squares of the number of times the gaming machine 15 was operated.

[0109] Here, various definitions are possible regarding the number of times the gaming machine 15 is operated. It may be defined as one operation each time the same player uses a different gaming machine 15. In the case of pachinko, it may also be defined as one operation when a ball enters the start checker and the symbols on the LCD screen change once.

[0110] In pachislot, the series of actions from inserting a token and pulling the lever until the reels spin and stop may be defined as one operation. In smart slots, the number of games displayed on the LCD and the unique points may be defined as one operation. Needless to say, when calculating the correlation coefficient r using formula 1, the definition of the number of operations for the gaming machine 15 must be standardized.

[0111] Furthermore, the information processing device 12 may change the weighting used when determining whether or not there is a correlation based on the attributes of the video uploader A1 determined in step S11. For example, when calculating the correlation coefficient in step S14, if the uploader A1's attributes are above a first threshold based on a predetermined influence indicator (e.g., number of channel subscribers, average number of views of past videos, or a combination thereof), the weighting may be adjusted to set a relatively larger weight coefficient for the viewing indicator of the video. If the uploader A1's attributes are below the first threshold for the influence indicator, the weighting may be adjusted to set a relatively smaller weight coefficient for the viewing indicator of the video.

[0112] In step S15, following step S14, the information processing device 12 may determine whether the absolute value of the correlation coefficient is greater than or equal to a predetermined value, for example, 0.7 or greater. This predetermined value is stored in the auxiliary storage device 28 to determine whether there is a correlation between the operating status of a predetermined model of gaming machine 15 installed in the gaming parlor 14 and the usage status of web content including the predetermined model of gaming machine 15. Here, the predetermined model of gaming machine 15 itself is not limited; it is sufficient that the predetermined model of gaming machine 15 installed in the gaming parlor 14 and the predetermined model included in the web content are the same.

[0113] For example, if the number of times a predetermined type of gaming machine 15 is operated increases during a predetermined period, and the number of views of posted videos including the predetermined type of gaming machine 15 increases, the information processing device 12 determines Yes in step S15. When the information processing device 12 determines Yes in step S15, it treats the operating status of the predetermined type of gaming machine 15 installed in the gaming parlor 14 as having a correlation with the usage status of web content including the predetermined type of gaming machine 15, and executes the process in step S16.

[0114] In step S16, the information processing device 12 may predict the future operating status of a gaming machine 15 of a predetermined model provided in the gaming parlor 14 and generate prediction information by using the operating status of the gaming machine 15 of the predetermined model provided in the gaming parlor 14 and the usage status of web content including the gaming machine 15 of the predetermined model.

[0115] For example, the information processing device 12 may calculate a predicted value y of a future operating index by substituting the obtained video viewing index into a multiple regression model constructed by using a predicted operating index (target variable) and a viewing index of a posted video (explanatory variable) determined to have a correlation with the operating index. The multiple regression model is represented by Equation 2.

[0116] y = β0 + β1x1 + β2x2 +... + β n x n ···(Equation 2) In Equation 2, x 1 , x2... are viewing indexes of posted videos, β0 is an intercept, and β1, β2 are regression coefficients indicating the viewing indexes of posted videos. The regression coefficients and the intercept are determined in advance by the least squares method using data including the operating status of the gaming machine 15 and the usage status of posted videos in the past.

[0117] When predicting the "number of future players in the week including the day the gaming machine was introduced" in step S16, the information processing device 12 may select the correlation coefficient of the "number of teaser video plays" determined to be Yes in step S15 or the correlation coefficient of the "cumulative number of introduction video plays" as the viewing index of the posted video and construct the multiple regression model of Equation 2. Further, after determining the number of plays of a teaser video or an introduction video corresponding to a new model gaming machine, the information processing device 12 may substitute that value into Equation 2 and predict the "number of future players in the week including the day the gaming machine was introduced" in step S16.

[0118] Furthermore, when the information processing device 12 predicts the "operating lifespan of the gaming machine" in step S16, it may select the correlation coefficient of "the retention rate of test play videos over a predetermined period" or the correlation coefficient of "the rate of decrease in the number of views of explanatory videos over a predetermined period" as the viewing index for posted videos and construct a multiple regression model using Equation 2. In this way, the information processing device 12 can improve the accuracy of predicting the future operating status of the gaming machine 15 by using different viewing indexes for posted videos or multiple regression models to calculate the predicted value y, depending on the characteristics of the operating index to be predicted, for example, whether to predict the short-term operating index of the gaming machine 15 or the medium- to long-term operating index of the gaming machine 15.

[0119] For example, depending on whether you are predicting the short-term operational indicators (operating status) of the gaming machine 15, or the medium- to long-term operational indicators of the gaming machine 15, you may select one of the following categories of posted videos to use in calculating the predicted value y: "teaser video," "test play video," "introduction video," or "explanatory video." In other words, the longer the future prediction period (prediction range) for predicting the operation of the gaming machine 15, the more appropriate it may be to select posted videos from categories that were posted later.

[0120] Furthermore, in step S16, the information processing device 12 may use the predicted number of future operations M of the gaming machine 15 to predict sales revenue for a predetermined future period using formula 3.

[0121] Future sales = M * α ... (Equation 3) In formula 3, α is the average sales revenue corresponding to 1 operation of the gaming machine 15. The forecast information may also include the predicted number of operations of the gaming machine 15 in a predetermined future period, future sales revenue, etc. The information processing device 12 may also construct the forecast results of the operating status performed in step S16 using image information and text data, such as tables, graphs, and text.

[0122] Furthermore, in step S17 following step S16, the information processing device 12 outputs prediction information and terminates the routine shown in Figure 3. The processing performed by the information processing device 12 in step S17 may be one or more of the following: outputting prediction information from the output device 20, storing it in the storage medium 29A of the media drive device 29, and transmitting the prediction information to the game store computer 17.

[0123] On the other hand, if, at the time of the decision in step S13 described above, none of the predetermined conditions described above are met, the information processing device 12 may decide in step S13 to be No. If the information processing device 12 decides in step S15 to be No, it decides in step S18 not to calculate the correlation coefficient. Furthermore, in step S19 following step S18, the information processing device 12 decides not to execute the "process of predicting the future operating status for each type of gaming machine 15" and terminates the routine in Figure 3.

[0124] Furthermore, if the information processing device 12 determines No in step S15, it treats the operating status of a predetermined type of gaming machine 15 installed in the gaming parlor 14 as having no correlation with the usage status of web content including the predetermined type of gaming machine 15, and makes the decision in step S19. For example, if the number of times the predetermined type of gaming machine 15 is operated over a predetermined period remains almost constant, and the number of views of posted videos including the predetermined type of gaming machine 15 increases, it determines Yes in step S15.

[0125] The information processing device 12 may use the following as a specific example to calculate the correlation coefficient in step S14. For example, it may calculate the correlation coefficient between operational information, which includes items such as "the number of players per day in the week including the day the gaming machine was introduced," "the average number of coins inserted into the gaming machine over a four-week period," "the retention rate during which players used the gaming machine at least a predetermined number of times per day over a 12-week period," and "the operating life of the gaming machine," and the usage status of web content, which includes items such as "the number of teaser video views during a predetermined period," "the retention rate of the trial play video during a predetermined period," and "the rate of decrease in the number of explanatory video views during a predetermined period."

[0126] Then, if the information processing device 12 calculates a correlation coefficient of 0.72 between the "number of teaser video views" and the "number of players per day in the week including the day the gaming machine was introduced" in step S14, the information processing device 12 may decide to determine Yes in step S15. Also, if the information processing device 12 calculates a correlation coefficient of -0.72 between the "rate of decrease in the number of views of the explanatory video" and the "operating lifespan of the gaming machine" in step S14, the information processing device 12 may decide to determine Yes in step S15. In other words, a negative correlation coefficient for the "operating lifespan of the gaming machine" can be inferred to mean that the number of views of the posted videos is on a downward trend, and the operating lifespan of the gaming machine is shortening.

[0127] Furthermore, the predetermined model of the gaming machine 15 may be one or more. If there are multiple predetermined models of the gaming machine 15, the information processing device 12 may determine in step S15 whether or not there is a correlation for each model of the gaming machine 15. Then, in step S16, the information processing device 12 may create prediction information for each model of the gaming machine 15. The information processing device 12 may also store the results of the processing and the determinations made in steps S11 to S19 in the auxiliary storage device 28.

[0128] The information processing device 12 may execute the information processing method shown in Figure 4 at predetermined intervals, or each time new viewing metrics for a posted video are collected, or it may execute the information processing method shown in Figure 4 at a timing specified by the operation of the input device 50.

[0129] (Effects of the embodiment) The information processing device 12, when it determines that there is a correlation between the operating status of a predetermined type of gaming machine 15 installed in the gaming parlor 14 and the usage status of web content including the predetermined type of gaming machine 15, predicts the future operating status of the gaming machine 15 installed in the gaming parlor 14 for each type of gaming machine 15. Therefore, it is possible to improve the accuracy of predicting the future operating status of the gaming machine 15 installed in the gaming parlor 14 for each type of gaming machine 15.

[0130] Therefore, the above effects can be obtained even when the amount of training data sample used for machine learning of the learning model is small, or when the model of the gaming machine 15 is a minor model and the number of submitted videos obtained from the content provision computer 13 is insufficient.

[0131] Furthermore, the inventors of this application recognized that the technology described in Patent Document 1 has the following problems. The first problem is that while text data reflects the "opinions" and "impressions" of users (players), it does not necessarily accurately reflect the scale of "interest" or "enthusiasm" in the overall market. Text postings tend to be concentrated among a small number of enthusiastic users, and there was a possibility that the trends of the silent majority could not be fully captured.

[0132] The second challenge is that the wealth of information contained in "behavioral" data from video content viewing is not being utilized. In particular, on video distribution platforms, when a new amusement machine is announced, a large number of diverse videos are posted and viewed, including official promotional videos (teaser videos) from manufacturers, test play videos by media and influencers, and practical play videos by ordinary users. Examples of video distribution platforms include YouTube®, Niconico Video®, TikTok®, and Twitch®. Metrics such as the number of views, retention rate, and number of likes of these posted videos are "behavioral data" that indicates the degree of active interest of users, and are thought to reflect market expectations more directly and quantitatively than text information, but have not been fully utilized with conventional technology.

[0133] The third challenge concerns the timing of predictions. With conventional technology, sufficient data could not be obtained until a certain amount of buzz had formed on social networking services (SNS), that is, relatively soon before the introduction of the gaming machines, for example, six weeks before the machines were introduced, making accurate predictions difficult. Enabling earlier, more accurate predictions was strongly desired for optimizing store operations and manufacturing plans.

[0134] In contrast, the information processing device 12 of this embodiment can predict the future operating status of each type of gaming machine 15 based on objective and quantitative data of user viewing behavior on the video distribution platform.

[0135] Therefore, according to the information processing device 12 of this embodiment, it is possible to predict the future operating status of each type of gaming machine 15 with higher accuracy and at an earlier stage compared to the conventional technology. As a result, the gaming parlor 14 can make decisions regarding the introduction of new models, setting allocation, and replacement plans more strategically, contributing to increased profits at the gaming parlor 14. In addition, the manufacturer of the gaming machine 15 can grasp market demand at an earlier stage and optimize production plans and marketing strategies.

[0136] Furthermore, web content information can be classified into multiple categories based on the posting dates of the videos, and correlation coefficients can be calculated for each category. Therefore, for each of the 15 gaming machine models, future operating status can be predicted for the first period and for a second period that is longer than the first period, further improving prediction accuracy.

[0137] For example, the correlation coefficient (e.g., r=0.72) obtained by applying the number of views of the teaser video and the number of players in the week including the introduction date of the gaming machine 15 to Equation 1 may be used to predict the future operating status of each gaming machine 15 model in the first period (short-term forecast). Alternatively, the correlation coefficient (e.g., r=0.74) obtained by applying the number of views of the introductory video and the number of players in the week including the introduction date of the gaming machine 15 to Equation 1 may be used to predict the future operating status of each gaming machine 15 model in the first period.

[0138] Alternatively, the correlation coefficient (for example, r=0.71) obtained by applying the viewership rating of the test play videos and the operating life of the gaming machine 15 to Equation 1 may be used to predict the future operating status of each gaming machine 15 model in the second period (medium-term or long-term forecast).

[0139] (Examples of information processing methods applications) If the prediction period for the future operating status of the gaming machine 15 is the first period, the information processing device 12 may predict the future operating status of the gaming machine 15 using the number of views of the posted videos in step S16. Conversely, if the prediction period for the future operating status of the gaming machine 15 is a second period which is longer than the first period, the information processing device 12 may predict the future operating status of the gaming machine 15 using the retention rate of the posted videos.

[0140] In step S16, if the prediction period for the future operating status of the gaming machine 15 is the first period, the information processing device 12 may predict the future operating status of the gaming machine 15 using a posted video whose posting date is the first period. If the prediction period for the future operating status of the gaming machine 15 is the second period, which is longer than the first period, the information processing device 12 may predict the future operating status of the gaming machine 15 using a posted video whose elapsed time is later than the first period, which is the second period.

[0141] Alternatively, the information processing device 12 may determine "Yes" in step S13 if the region where the amusement parlor 14 is located in the web content matches the region where the amusement parlor 14 is located in the amusement parlor information, and then calculate the correlation coefficient for each model of amusement machine 15 for each region where the amusement parlor 14 is located. Therefore, the accuracy of predicting the future operating status for each model of amusement machine 15 for each region where the amusement parlor 14 is located is improved.

[0142] The information processing device 12 may determine "Yes" in step S13 if the age group of poster A1 included in the web content matches the age group of players included in the amusement parlor information, and may calculate the correlation coefficient for each model of amusement machine 15 for each age group included in the amusement parlor information. Therefore, the accuracy of predicting the future operating status for each model of amusement machine 15 for each age group included in the amusement parlor information is improved.

[0143] The information processing device 12 may determine "Yes" in step S13 if the gender of poster A1 included in the web content matches the gender of the player included in the amusement parlor information, and then calculate the correlation coefficient for each type of amusement machine 15 for each gender of the player. Therefore, the accuracy of predicting the future operating status of each type of amusement machine 15 for each gender of the player is improved. Note that after executing steps S11 and S12, the information processing device 12 may skip the determination in step S13 and execute the process in step S14.

[0144] Furthermore, the information processing device 12 may perform the processing in step S14 and obtain the correlation coefficient for each competing model of the gaming machine 15. Then, in step S16, the information processing device 12 may predict the future operating status of the gaming machine 15 for each competing model. Therefore, the accuracy of predicting the future operating status of the gaming machine 15 for each competing model is improved.

[0145] Furthermore, the information processing device 12 may use 0.4 instead of 0.7 as the "predetermined value" used in the determination in step S15. In addition, the information processing device 12 may determine in step S15 whether "the absolute value of the correlation coefficient is greater than or equal to the predetermined value and falls into one of the multiple numerical ranges." For example, if the information processing device 12 sets the "predetermined value" to 0.4 and defines "a first numerical range in which the absolute value of the correlation coefficient is between 0.4 and 0.7" and "a second numerical range in which the absolute value of the correlation coefficient is between 0.71 and 1.0", the information processing device 12 may determine whether "the absolute value of the correlation coefficient falls into the first numerical range or the second numerical range."

[0146] The information processing device 12 may then treat the absolute value of the correlation coefficient as being within a first numerical range, indicating a moderate correlation, and determine Yes in step S15. Alternatively, the information processing device 12 may also treat the absolute value of the correlation coefficient as being within a second numerical range, indicating a strong correlation, and determine Yes in step S15. Furthermore, when the information processing device 12 performs operation predictions for each type of gaming machine in step S16, it may differentiate the content of the operation predictions depending on whether there is a moderate correlation or a strong correlation.

[0147] (supplementary explanation) To confirm the effects of this embodiment, the inventors of the present invention conducted statistical verification and the results are as follows. As an example, significance verification was performed using a t-test.

[0148] For the case of r=0.58 and n=20 models, t=3.02>t 0.01 The result is 2.878, which is significant at the 1% level. **Coefficient of determination R 2 **: R for evaluating the accuracy of multiple regression models 2 = 0.72 (This can explain 72% of the fluctuations in operating capacity) **MEPE (Mean Prediction Error Rate)**: 12.5%

[0149] The correlation determination unit 35 of the information processing device 12 may use other correlation analysis methods, such as Spearman's rank correlation coefficient or Kendall's rank correlation coefficient, when calculating the correlation coefficient in step S14. The operating status prediction unit 52 of the information processing device 12 may construct a prediction model using other machine learning methods, such as random forests, support vector machines, or neural networks, when executing the process in step S16. This allows for the capture of nonlinear relationships between variables and further improves prediction accuracy.

[0150] An example of the technical meaning disclosed in this embodiment is as follows: Information processing device 12 is an example of an information processing device and a computer. Content providing computer 13 is an example of a content providing computer. Processor 26 is an example of a processor. Step S10 shown in Figure 4 is an example of the first process. Step S11 is an example of the second and eighth processes. Step S12 is an example of the third process. Step S15 is an example of the fourth process. Step S16 is an example of the fifth process. Step S13 is an example of the sixth and seventh processes.

[0151] The computer comprising the information processing device 12 may be a single computer or a distributed computer composed of multiple devices. The information processing device 12 may also be composed of one or more computers, such as a server, supercomputer, mainframe, or workstation.

[0152] This embodiment discloses the following characteristic configuration: For example, a non-temporary storage medium that stores a non-temporary program to be read and operated by a computer that is communicably connected to a content-providing computer via a network, wherein the program includes a first process for the computer to acquire web content posted by a poster to the content-providing computer and amusement store information of an amusement store where amusement machines are installed; a second process for determining the model of the amusement machine included in the web content and the usage status of the web content; a third process for determining the operating status of the amusement machine included in the amusement store information; and information provided at the amusement store. A storage medium is disclosed that performs the following steps: a fourth process for determining whether there is a correlation between the operating status of a predetermined type of gaming machine and the usage status of the web content including the predetermined type of gaming machine; and, if it is determined that there is a correlation between the operating status of a predetermined type of gaming machine installed in the amusement parlor and the usage status of the web content including the predetermined type of gaming machine, a fifth process for predicting the future operating status of the predetermined type of gaming machine installed in the amusement parlor using the operating status of the predetermined type of gaming machine installed in the amusement parlor and the usage status of the web content including the predetermined type of gaming machine. The auxiliary storage device 28 and the media drive device 29 are examples of storage mediums. Note that the program can also be understood as a program product. [Industrial applicability]

[0153] This embodiment can be used as an information processing device, an information processing method, and a program for processing information about the operation of a gaming parlor. [Explanation of Symbols]

[0154] 12... Information processing device, 13... Content providing computer, 14... Amusement parlor, 15... Amusement machine, 26... Processor, A1... Contributor, A2... Content user

Claims

1. An information processing device having a processor that is connected to a content-providing computer via a network in a communicable manner and executes processing by running a non-temporary program, The aforementioned processor, A first process that acquires web content posted by the poster to the content-providing computer, and information about the amusement parlor where the amusement machines are installed, A second process for determining the model of the gaming machine included in the web content and the usage status of the web content, A third process for determining the operating status of the gaming machines included in the aforementioned gaming parlor information, A fourth process for determining whether there is a correlation between the operating status of a predetermined type of gaming machine installed in the aforementioned gaming parlor and the usage status of the web content including the predetermined type of gaming machine, If it is determined that there is a correlation between the operating status of a predetermined type of gaming machine installed in the aforementioned gaming parlor and the usage status of web content including the predetermined type of gaming machine, a fifth process is performed to predict the future operating status of the predetermined type of gaming machine installed in the aforementioned gaming parlor, using the operating status of the predetermined type of gaming machine installed in the aforementioned gaming parlor and the usage status of web content including the predetermined type of gaming machine. An information processing device configured to perform the following actions.

2. An information processing apparatus according to claim 1, The information processing apparatus is configured such that the second process performed by the processor includes a process of calculating a web content support rate by dividing the playback share of a predetermined model of posted video included in the web content by the share of the number of posted videos.

3. An information processing apparatus according to claim 1, The second process performed by the aforementioned processor is configured to classify the posted videos included in the web content into multiple categories with different posting dates. The fifth process performed by the aforementioned processor is: If the prediction period for the future operating status of the gaming machine is the first period, the process of predicting the future operating status of the gaming machine is performed using the posted videos posted during the first period. If the prediction period for the future operating status of the gaming machine is a second period which is longer than the first period, the process of predicting the future operating status of the gaming machine is performed using the posted videos posted in the second period which is later than the first period. An information processing device comprising the above configuration.

4. An information processing apparatus according to claim 1, The second process performed by the aforementioned processor is configured to determine the number of views and retention rate of posted videos included in the web content over a predetermined period of time. The fifth process performed by the aforementioned processor is: If the prediction period for the future operating status of the gaming machine is the first period, the process of predicting the future operating status of the gaming machine using the number of views of the posted video is performed. If the prediction period for the future operating status of the gaming machine is a second period which is longer than the first period, the process of predicting the future operating status of the gaming machine using the retention rate of the posted videos is performed. An information processing device comprising the above configuration.

5. An information processing apparatus according to claim 1, The processor is configured to perform a sixth process before executing the fourth process, which determines whether the region where the amusement parlor is located, as contained in the web content, matches the region where the amusement parlor is located, as contained in the amusement parlor information. The aforementioned processor, In the sixth process, if it is determined that the region where the amusement parlor is located, as contained in the web content, matches the region where the amusement parlor is located, the fourth process is executed. If the sixth process determines that the region where the amusement parlor is located, as included in the web content, does not match the region where the amusement parlor is located, as included in the amusement parlor information, the fourth process is not performed. The component is an information processing device.

6. An information processing apparatus according to claim 1, The processor is configured to perform a seventh process before executing the fourth process, which determines whether the age group of the posters included in the web content matches the age group of the players who use the gaming machines and are included in the gaming parlor information. The aforementioned processor, If the seventh process determines that the age group of the poster and the age group of the players match, the fourth process is executed. An information processing device configured such that, if the seventh process determines that the age group of the poster and the age group of the players are different, the fourth process is not executed.

7. An information processing apparatus according to claim 1, The processor is configured to perform an eighth process, which determines the attributes of the poster of the web content, before performing the fourth process. The information processing apparatus is configured such that the fourth process performed by the processor changes the weighting used when determining whether or not there is a correlation based on the attributes of the poster.

8. An information processing device executed by a computer that is connected to a content-providing computer via a network and runs a non-temporary program, The aforementioned computer, A first process that acquires web content posted by the poster to the content-providing computer, and information about the amusement parlor where the amusement machines are installed, A second process for determining the model of the gaming machine included in the web content and the usage status of the web content, A third process for determining the operating status of gaming machines included in the aforementioned gaming parlor information, A fourth process for determining whether there is a correlation between the operating status of a predetermined type of gaming machine installed in the aforementioned gaming parlor and the usage status of the aforementioned web content, including the aforementioned predetermined type of gaming machine. If it is determined that there is a correlation between the operating status of a predetermined type of gaming machine installed in the aforementioned gaming parlor and the usage status of web content including the predetermined type of gaming machine, a fifth process is performed to predict the future operating status of the predetermined type of gaming machine installed in the aforementioned gaming parlor, using the operating status of the predetermined type of gaming machine installed in the aforementioned gaming parlor and the usage status of web content including the predetermined type of gaming machine. An information processing method configured to perform the following.

9. A non-temporary program that is loaded and run by a computer that is connected to a content-providing computer via a network, To the aforementioned computer, A first process that acquires web content posted by the poster to the content-providing computer, and information about the amusement parlor where the amusement machines are installed, A second process for determining the model of the gaming machine included in the web content and the usage status of the web content, A third process for determining the operating status of gaming machines included in the aforementioned gaming parlor information, A fourth process for determining whether there is a correlation between the operating status of a predetermined type of gaming machine installed in the aforementioned gaming parlor and the usage status of the aforementioned web content, including the aforementioned predetermined type of gaming machine. If it is determined that there is a correlation between the operating status of a predetermined type of gaming machine installed in the aforementioned gaming parlor and the usage status of web content including the predetermined type of gaming machine, a fifth process is performed to predict the future operating status of the predetermined type of gaming machine installed in the aforementioned gaming parlor, using the operating status of the predetermined type of gaming machine installed in the aforementioned gaming parlor and the usage status of web content including the predetermined type of gaming machine. A program configured to execute [something].

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