Information processing system and program

Abstract

To provide an information processing system and a program which can increase the number of choices of products or services to be recommended, compared to a case of preliminarily registering products or services to be recommended.SOLUTION: Attribute information is acquired from a job executed by an image processing apparatus, joblog information including at least the attribute information is stored, recommendation information for recommending a product or a service related to the joblog information is generated from a search result of a search over the Internet on the basis of the joblog information, and the recommendation information is outputted to a user.SELECTED DRAWING: Figure 1

Description

[Technical Field]

[0001] The present invention relates to an information processing system and a program. [Background technology]

[0002] Patent document 1 discloses a recommendation system comprising: a power usage monitoring means disposed in each electricity consumer's home and acquiring the power usage status of each electrical device in the consumer's home; a usage status storage means acquiring and storing the power usage status from each power usage monitoring means; a product information storage means storing information on a plurality of products, with at least one of goods and services being the products; and a selection means selecting from the product information storage means a product that is suitable for the power usage status of the target consumer's home based on the power usage status of the target consumer's home and the power usage status of other consumer's homes.

[0003] Patent document 2 discloses an information processing device that includes a data acquisition means for acquiring product data, which is data on products that have already been introduced to a customer; a condition acquisition means for acquiring proposal conditions, which are conditions individually set for multiple other products that are different from the introduced product; and an output means for outputting proposal information, which is information indicating that, when the product data acquired by the data acquisition means satisfies any of the proposal conditions, the other product corresponding to the satisfied proposal condition is a product that is proposed to be introduced to the customer. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent Publication No. 2021-15329 [Patent Document 2] Japanese Patent Publication No. 2020-77047 Summary of the Invention [Problem to be solved by the invention]

[0005] A system is known that recommends other products or services to a user who is currently using a product or service. In such a system, products or services that are options for recommendations must be registered in advance. However, when products or services that are options for recommendations are registered in advance, there is a problem in that the products or services that can be recommended are limited.

[0006] The present disclosure aims to provide an information processing system and program that can increase the options for recommended products or services compared to when the products or services to be recommended are registered in advance. [Means for solving the problem]

[0007] An information processing system according to a first aspect includes a processor that acquires attribute information from a job executed by an image processing device, stores job log information including at least the attribute information, and creates recommendation information that recommends products or services related to the job log information from search results obtained through an Internet search based on the job log information, and outputs the recommendation information to a user.

[0008] In the information processing system of the second aspect, the processor creates the recommendation information from search results obtained by searching within a predetermined range of the company's own products or services based on the job log information, and if the recommendation information cannot be created from search results obtained by searching within the range of the company's own products or services, the processor creates the recommendation information from search results obtained by searching the Internet.

[0009] In the information processing system according to a third aspect, the processor creates the recommendation information based on the job log information and attribute information of the job being executed by the image processing device.

[0010] In the information processing system according to a fourth aspect, when the job log information satisfies a predetermined condition, the processor searches the Internet using a predetermined template for the condition.

[0011] In the information processing system according to a fifth aspect, the processor generates keywords to be searched on the Internet by inputting the job log information into a sentence generation model that generates sentences according to input sentences.

[0012] In the information processing system of the sixth aspect, the processor organizes product or service information obtained from search results on the Internet into predetermined categories, scores the degree of compatibility with the job log information, and recommends search results with a predetermined score or higher.

[0013] In the information processing system according to a seventh aspect, after obtaining a predetermined number of search results having scores equal to or higher than the score, the processor recommends the results having the highest scores to the user.

[0014] In the information processing system according to an eighth aspect, the processor does not recommend a product or service that has already been used.

[0015] An information processing program according to a ninth aspect causes a computer to acquire attribute information from a job executed by an image processing device, store job log information including at least the attribute information, create recommendation information that recommends products or services related to the job log information from search results obtained by searching the Internet based on the job log information, and output the recommendation information to a user. [Effects of the Invention]

[0016] According to the first aspect, there is an effect that it is possible to increase the number of options for products or services to be recommended compared to when products or services to be recommended are registered in advance.

[0017] According to the second aspect, there is an effect that it is possible to recommend a company's own products or services with priority over products or services of other companies.

[0018] According to the third aspect, it is possible to provide a recommendation that reflects the user's usage history of the image processing device.

[0019] According to the fourth aspect, there is an effect that a search can be performed on the Internet using a fixed phrase.

[0020] According to the fifth aspect, there are advantages that a sentence generation model can be used to search the Internet, and that the information processing system can be used to reflect the results in the management device and set up.

[0021] According to the sixth aspect, it is possible to prevent recommendations that differ from the user's usage history of the image processing device from being made.

[0022] According to the seventh aspect, it is possible to recommend products or services that are highly compatible with the user's usage history of the image processing device.

[0023] According to the eighth aspect, it is possible to prevent products or services that are unnecessary for the user from being recommended.

[0024] According to the ninth aspect, there is an effect that it is possible to increase the number of options for products or services to be recommended, compared to when products or services to be recommended are registered in advance. [Brief explanation of the drawings]

[0025] [Figure 1] 1 is a schematic configuration diagram of a recommendation system according to an embodiment of the present disclosure. [Figure 2] 1 is a schematic block diagram of an image processing device according to an embodiment of the present disclosure. [Figure 3]FIG. 10 is an explanatory diagram for explaining attribute information of a job according to an embodiment of the present disclosure. [Figure 4] 1 is a schematic block diagram of an information processing device according to an embodiment of the present disclosure. [Figure 5] 10 is a flowchart illustrating an example of a process flow for outputting recommendation information to a user according to an embodiment of the present disclosure. [Figure 6] FIG. 10 is an explanatory diagram for explaining service attribute information of other companies according to an embodiment of the present disclosure. [Figure 7] FIG. 10 is an explanatory diagram illustrating an example of a case where internet search results according to an embodiment of the present disclosure are stored as service attribute information of other companies. [Figure 8] FIG. 10 is an explanatory diagram illustrating an example of scores of service attribute information of other companies according to an embodiment of the present disclosure. [Figure 9] FIG. 10 is a diagram illustrating an example of output of recommendation information according to an embodiment of the present disclosure. DETAILED DESCRIPTION OF THE INVENTION

[0026] (Embodiment) An example of an embodiment of the present disclosure will be described below with reference to the drawings. The same or equivalent components and parts in each drawing are designated by the same reference numerals. The dimensional proportions in the drawings are exaggerated for the sake of explanation and may differ from the actual proportions.

[0027] An example of a recommendation system 10 according to this embodiment will be described with reference to FIG.

[0028] FIG. 1 is a diagram showing an example of a schematic configuration of a recommendation system 10 according to this embodiment. As shown in FIG. 1, a recommendation system 10 according to this embodiment includes an image processing device 20 and an information processing device 30.

[0029] The image processing device 20 and the information processing device 30 are connected via a network N. This network N may be, for example, a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, or the like.

[0030] The image processing device 20 is a device that forms an image on paper as a recording medium. In this embodiment, the image processing device 20 has various functions such as a printing function, a copying function, a facsimile function, and a scanning function.

[0031] The information processing device 30 is an example of an information processing system. Note that the "system" in this embodiment includes both a system configured by multiple devices and a system configured by a single device. Note that in this embodiment, a device installed in a cloud environment is applied as the information processing device 30. However, this example is not limiting. The information processing device 30 does not have to be installed in a cloud environment.

[0032] The recommendation system 10 of this embodiment is a system that recommends products or services related to job log information based on job log information including attribute information of jobs executed by the image processing device 20. The following description will be mainly based on a system that recommends services. Also, descriptions of services may be applied to products.

[0033] FIG. 2 is a block diagram showing the hardware configuration of the image processing device 20 according to this embodiment.

[0034] 2, the image processing device 20 includes a CPU (Central Processing Unit) 201, a ROM (Read Only Memory) 202, a RAM (Random Access Memory) 203, a storage unit 204, an input unit 205, a display unit 206, a document reading unit 207, an image forming unit 208, and a communication unit 209. Each component is connected to each other via a bus 210 so as to be able to communicate with each other.

[0035] The CPU 201 is a central processing unit that executes various programs and controls each part. That is, the CPU 201 reads programs from the ROM 202 or the storage unit 204 and executes the programs using the RAM 203 as a work area. The CPU 201 controls each of the above components and performs various arithmetic processing in accordance with the programs recorded in the ROM 202 or the storage unit 204.

[0036] In this embodiment, the storage unit 104 stores attribute information acquired from a job (such as a print, scan, or copy job) executed by the image processing device 20 in combination with a job ID assigned to the job.

[0037] As shown in FIG. 3 , the attribute information includes the frequency of use, the type of input object, the type of output object, the installation location of the image processing device 20, the user's characteristics and the type of function, etc. The frequency of use is, for example, the frequency of use of the image processing device 20, and includes the number of times used per month, per year, per hour, per day, etc. The type of input object includes, for example, whether the content of a job input by a user to the image processing device 20 is a photograph, an illustration, text, a document, personal information, etc. The determination of the job content includes, for example, determining that the content of a job is a photograph when the user selects a mode suitable for printing photos in the print settings when printing a job using the image processing device 20, or determining that the content of a job is text when the type of job sent from a PC or the like to the image processing device 20 is text. Note that the attribute information is not limited to that shown in FIG. 3 and may include other attribute information, or may not include all of the attribute information shown in FIG. 3 . The type of output object includes whether the content of a job output by a user from the image processing device 20 is a photograph, an illustration, text, a document, personal information, etc. Here, only one of the type of input object and the type of output object may be stored as attribute information. The installation location of the image processing device 20 includes information on the location where the image processing device 20 is installed, such as a convenience store, an office, or a hospital. The user characteristics include the characteristics of the user who caused the image processing device 20 to execute a job, such as age and gender. The type of function includes the type of function of the job executed by the image processing device 20, such as a print function, a scanner function, a facsimile function, or a copy function.

[0038] The ROM 202 stores various programs and various data. The RAM 203 temporarily stores programs or data as a working area. The storage unit 204 is configured with an HDD (Hard Disk Drive) or an SSD (Solid State Drive) and stores various programs including an operating system and various data.

[0039] The input unit 205 includes a pointing device such as a mouse and a keyboard, and is used to input various information. In this embodiment, the touch panel display unit 206 functions as the input unit 205.

[0040] The display unit 206 is, for example, a liquid crystal display. The display unit 206 displays various information under the control of the CPU 201. In this embodiment, recommended information, which will be described later, is displayed. The display unit 206 also functions as the input unit 205 by adopting a touch panel system.

[0041] The document reading unit 207 takes in, one by one, documents placed on a paper feed tray of an automatic document feeder (ADF: Automatic Document Feeder) (not shown) provided on top of the image processing device 20, and optically reads the taken-in documents to obtain image information. Alternatively, the document reading unit 207 optically reads documents placed on a tray such as a platen glass to obtain image information.

[0042] The image forming unit 208 forms, i.e., prints, on a recording medium such as paper, print data contained in a job obtained from a PC (not shown) connected via a network, or an image based on a job obtained by reading by the document reading unit 207.

[0043] The communication unit 209 is connected to the network N, and performs communication such as job transfer processing between the image processing device 20 and other devices such as the information processing device 30. The communication unit 209 also connects the image processing device 20 to a public line, and transmits and receives image information obtained by reading by the document reading unit 207 to and from other image processing devices having a facsimile function.

[0044] FIG. 4 is a block diagram showing the hardware configuration of the information processing device 30 according to this embodiment.

[0045] 4, the information processing device 30 includes a CPU 301, which is an example of a processor, a ROM 302, a RAM 303, a storage unit 304, and a communication unit 305. These are connected via a bus 306 so as to be able to communicate with each other.

[0046] The CPU 301 is a central processing unit that executes various programs and controls each section. That is, the CPU 301 reads programs from the ROM 302 or the storage section 304, and executes the programs using the RAM 303 as a work area. The CPU 301 controls the above-mentioned components and performs various arithmetic processing in accordance with the programs recorded in the ROM 302 or the storage section 304. In this embodiment, the programs are stored in the ROM 302 or the storage section 304.

[0047] The ROM 302 stores various programs and various data. The RAM 33 temporarily stores programs or data as a working area. The storage unit 304 is configured with an HDD (Hard Disk Drive) or an SSD (Solid State Drive) and stores various programs including the operating system and various data.

[0048] In this embodiment, the storage unit 304 of the information processing device 30 also stores various data such as job log information including attribute information (see FIG. 3) acquired from the image processing device 20. The job log information is information relating to the history of jobs previously executed by the image processing device 20, and in this embodiment, is a combination of a job ID and attribute information, but may also include other information. The job log information is stored for each image processing device 20. That is, job log information representing the history of jobs executed by the same image processing device 20 is accumulated and stored in the storage unit 304 of the information processing device 30. The job log information may be stored for each image processing device 20, or may be stored for each user who executed the job.

[0049] In this embodiment, a company service database that predetermines company services is stored in the storage unit 304 of the information processing device 30. Here, the company services include services that can be provided to users of the image processing device 20 via the image processing device 20 by organizations that manage and sell the recommendation system 10 and the image processing device 20.

[0050] The communication unit 305 is connected to the network N and communicates with the information processing device 30 and other devices such as the image processing device 20.

[0051] Next, the operation of the information processing device 30 will be described with reference to Fig. 5 to Fig. 9. Here, the explanation will be given assuming that a company service database in which the company's services are predetermined by a person in charge of the recommendation system 10 and the organization that manages and sells the image processing device 20 is stored in the storage unit 304 of the information processing device 30, and furthermore, the image processing device 20 is installed in a location where it can be used by a user.

[0052] FIG. 5 is a flowchart showing an example of the flow of processing in which the information processing device 30 outputs recommendation information to a user.

[0053] First, in step S100, the CPU 301 acquires job log information from the image processing device 20. Then, the process proceeds to the next step S101.

[0054] In step S101, the CPU 301 searches for recommendation information within the scope of its own company's services stored in its own company's service database, based on the job log information acquired in step S100 and the attribute information of the job being executed by the image processing device 20. Then, the process proceeds to the next step, S102.

[0055] For example, when the attribute information of a job being executed by the image processing device 20 indicates that the "function type" is a "scanner function," the job log information related to the "scanner function" is acquired. If the job log information indicates that the "scanner function" has been used at a frequency of 50 times per day, which is a predetermined threshold, or more, the search for recommendation information is performed in the company's service database. Specifically, a service that performs scanning processing on behalf of the user is considered. Furthermore, when the attribute information of a job being executed by the image processing device 20 indicates that the "function type" is a "print function," the job log information related to the "print function" is acquired. If the job log information indicates that the "print function" has been used at a frequency of 50 times per day, which is a predetermined threshold, the search for recommendation information is performed in the company's service database. Specifically, a service that prints photos and creates an album is considered. Here, the search for recommendation information within the scope of the company's services is performed based on multiple pre-defined patterns, such as a pattern that combines the type of function and frequency of use, as in the example of the "scanner function" mentioned above, a pattern that combines the type of function, frequency of use, and type of input, as in the example of the "print function" mentioned above, and a pattern that combines the type of input and user characteristics, and the like, and the search is performed based on whether the job log information matches such a pattern.

[0056] In step S102, CPU 301 determines whether recommendation information can be created from the search results searched in step S101. That is, the determination is made based on whether there is a company service that matches the search results searched in step S101. If there is no matching service and it is not determined that recommendation information can be created, that is, if recommendation information cannot be created, the process proceeds to the next step S103.

[0057] In step S103, the CPU 301 acquires keywords to search on the Internet. For example, if the job log information and the attribute information of the job being executed by the image processing device 20 satisfy a predetermined condition, a predetermined template for the condition is acquired. Specifically, if the attribute information of the job being executed by the image processing device 20 indicates that the "function type" is "scanner function," job log information related to the "scanner function" is acquired. If the job log information indicates that the "scanner function" is used "at least 10 times per day" as a "usage frequency," a template for the three keywords "scanning agent monthly fee" is predefined. If the attribute information of the job being executed by the image processing device 20 indicates that the "function type" is "print function," job log information related to the "print function" is acquired. If the job log information indicates that the "print function" is used "at least 5 times per day" as a "photo input type" and a predetermined threshold for the frequency of use is "at least 5 times per day," a template for the three keywords "photo memory album creation service" is predefined. Such template text is stored in the storage unit 304 of the information processing device 30, but may be stored in another storage unit. Furthermore, such template text is created by a person in charge of an organization that manages or sells the recommendation system 10 or the image processing device 20, but is not limited to this and may be created by someone else. Then, the process proceeds to the next step S104.

[0058] Note that keywords to search on the Internet may be generated by inputting job log information as a prompt into a sentence generation model that generates sentences according to input sentences. For example, the CPU 301 generates a prompt such as "Please create search keywords to search for services for people with this job log information" and inputs it into the sentence generation model. Here, the sentence generation model is a so-called generative AI (Artificial Intelligence). An example of a sentence generation model is ChatGPT (Internet Search<URL: https: / / openai.com / blog / chatgpt> Examples of generative AI include AI based on deep learning. Sentence generation models are obtained by performing deep learning on neural networks. These sentence generation models are composed of large language models (LLMs).

[0059] In step S104, CPU 301 searches the Internet using the keywords created in step S103. Specifically, CPU 301 inputs the keywords into a search engine and performs a search. Then, the process proceeds to the next step, S105.

[0060] In step S105, the results of the internet search performed in step S104 are stored as service attribute information of other companies. Specifically, as shown in Fig. 6, CPU 301 sorts and stores the internet search results, starting from the top search results, into predetermined service attribute information items. Then, the process proceeds to the next step, S106.

[0061] Here, items of the service attribute information of other companies include service name, service category, usage fee and fee structure for each function, etc. The service name includes, for example, the service name of the service obtained from the Internet search results. The service category includes, for example, the type of service content obtained from the Internet search results, such as scanning service, printing service, document management service, etc. The usage fee for each function includes, for example, the usage fee for each plan of the service obtained from the Internet search results. The fee structure includes, for example, whether the fee structure of the service obtained from the Internet search results is a subscription, a time-based charge, or a per-use charge. Note that the items are not limited to those shown in FIG. 6 and may include other items, or may not include all of the items shown in FIG. 6. For example, other items may include basic functions, such as default functions provided by the service obtained from the Internet search results; optional functions, such as functions available for an additional fee for the service obtained from the Internet search results; and the service provision type, such as whether the service obtained from the Internet search results is a web service, an app-based service, or an offline face-to-face service. Furthermore, the services of other companies include services that can be provided to users of the image processing device 20 by organizations other than the organizations that manage and sell the recommendation system 10 and the image processing device 20. Furthermore, since it is conceivable that the company's own services may also be searched for through an Internet search, it is desirable to first determine whether the company's own services are stored in the company's own service database, and if the search results are not stored in the company's own service database, to store the results as service attribute information of the other company.

[0062] Furthermore, when storing the results of an Internet search as service attribute information of another company, if the results match a predetermined keyword, the service attribute information is entered in the service attribute field of the other company. Specifically, the "service category" of the service attribute field has predetermined keywords, such as "scan" for a "scan service" and "print" for a "print service." For example, if the keyword "scan" is included in the Internet search results, the service of the other company in the Internet search results is stored in the "service category" as a "scan service," as shown in FIG. 7. Furthermore, the "fee for each function" of the service attribute field has predetermined keywords, such as "yen" and "amount." If the keywords "yen" and "amount" are included in the Internet search results, the numerical values ​​of the keywords "yen" and "amount" within a predetermined range (for example, 10 characters or less) are stored as the "fee for each function" of the other company's service, as shown in FIG. 7. Additionally, the service attribute item "fee structure" has predetermined keywords, such as "subscription" for "subscription," "hourly" for "hourly billing," and "per use" for "count billing." For example, if the keyword "subscription" is included in the results of an internet search, the services of other companies found in the internet search results are stored as "subscriptions" in the "fee structure," as shown in Figure 7.

[0063] In step S106, CPU 301 evaluates the service attribute information stored in step S105 and scores the degree of compatibility with the job log information. Specifically, as shown in Fig. 8, the service attribute information of other companies (see Fig. 7) entered in the other company service attribute item is scored based on the score criteria. For example, as shown in Fig. 8, it is determined whether the information entered in the "service category" field matches the "type of function" (see Fig. 3) of the job being executed by image processing device 20, and the score is calculated based on the predetermined score criteria of "match: 100 points / 100, mismatch: 0 points / 100." In addition, when the "Service Category" is "Scan Service," the usage fee entered in the "Fee for Each Function" field is applied to a predetermined score scale: 100 yen / 100 for 5,000 yen / month or less, 90 points / 100 for 8,000 yen / month or less, 80 points / 100 for 10,000 yen / month or less, and 60 points / 100 for 15,000 yen / month or less. In addition, when the "Service Category" is "Scan Service," the information entered in the "Fee Structure" field is "Subscription," the score is calculated by applying the predetermined score scale for "Frequency of Use" (see Figure 3): 50 points / 100 for 10 times / month or less, 70 points / 100 for 50 times / month or less, 80 points / 100 for 100 times / month or less, and 100 points / 100 for 200 times / month or less. The total score is then calculated. Note that there may be cases where recommendation information is created from the search results of the Internet without calculating the degree of suitability and is output to the user.Then, the process proceeds to the next step S107.

[0064] In step S107, CPU 301 determines whether the score of compatibility with the job log information executed in step S106 exceeds a predetermined threshold. If it is determined that the score exceeds the predetermined threshold, for example, 220 points or a score rate of 75% out of a maximum score, the process proceeds to the next step S108. If it is not determined that the score exceeds the predetermined threshold, that is, if the score does not exceed the predetermined threshold, the process returns to step S104 described above. Note that if the score does not exceed the predetermined threshold, the process is not limited to returning to step S104, and may also return to step S103.

[0065] In step S108, the CPU 301 creates recommendation information from the services of other companies determined to have exceeded the threshold in step S107, and outputs the information to the display unit 106.

[0066] 9, the creation of recommendation information and output to display unit 106 may involve, for example, displaying the name of another company's service, creating and displaying a two-dimensional code (e.g., QR Code (registered trademark)) 106B indicating the URL (Uniform Resource Locator) of the website for the other company's service, displaying URL 106C of the website for the other company's service, or creating and displaying explanation 106D explaining the other company's service. Then, the process ends.

[0067] The description 106D may be created based on information contained in predetermined keyword fields, such as "description" or "service overview," of the other company's service obtained by searching the Internet, or by inputting a prompt (e.g., "Please create a 200-character description of the service at this URL") to a generation AI such as ChatGPT described above to create a description of the other company's service. The two-dimensional code 106B can be read by a user on a smartphone or the like to access the website of the other company's service. The URL can be displayed on the display unit 106 by a user touching the URL. If the other company's service is software or a service that can be added to the functions of the image processing device 20, a download URL for the software may be displayed as recommendation information, allowing the software to be downloaded and installed on the image processing device 20.

[0068] In the above-mentioned step S102, if the CPU 301 determines that it is possible to create recommendation information, the process proceeds to the next step S110, where the CPU 301 creates recommendation information from its own company's services and outputs it to the display unit 106. The creation of recommendation information and output to the display unit 106 are similar to the above-mentioned step S108. Then, the process ends.

[0069] The present invention is not limited to the above-described embodiment, and various modifications and applications are possible within the scope of the gist of the present invention.

[0070] For example, after obtaining a predetermined number of services of other companies, for example, three services, whose scores of compatibility with job log information exceed a predetermined threshold from the search results on the Internet, recommendation information may be created and output from the services of other companies. In this case, the services of other companies with the highest scores are recommended, but the present invention is not limited to this, and it is also possible to recommend all services of other companies whose scores of compatibility with job log information exceed a predetermined threshold.

[0071] Furthermore, if the image processing device 20 is equipped with a billing device that allows users to pay usage fees for the image processing device 20, such as copy fees, by inserting money into the device, the billing device may also be used to pay usage fees for other companies' services. In this case, the URL for downloading software displayed as recommendation information may be made available to the user after payment of the usage fee.

[0072] The user may also be able to select a mode for outputting recommendation information. For example, three modes may be selectable: "stop," "normal operation," and "reduced operation." "Stop" is a mode in which the output of recommendation information is disabled. "Normal operation" is a mode in which the output of recommendation information is enabled and the user can set the frequency of output of recommendation information, for example, once a day. "Reduced operation" is a mode that can be set when the user is already using a service provided by the company or another company. In "reduced operation," the currently used service provided by the company or another company is stored in the storage unit 304 as used service information. When storing used service information, it is desirable to store the service contract period together with the used service information. During the service contract period, recommendations for the "service category" that is the same as the used service information are stopped. After the service contract period has expired, recommendations for the "service category" that is the same as the used service information are resumed. Furthermore, when used service information is stored for multiple "service categories," the contract periods are also stored separately, and when the contract period for one of the services has expired, recommendations are resumed for the "service category" of the service whose contract period has expired, while recommendations are suspended for the "service category" of the service whose contract period has not yet expired. Furthermore, a guide on whether to renew the contract or recommended information for other services in the same "service category" may be output within a predetermined period before the end of the contract period for the service, for example, one month before.

[0073] In the above embodiment, the program is described as being pre-stored (installed) in the ROM 202, 302 or the storage unit 204, 304, but is not limited to this. The program may be provided in a form recorded on a recording medium such as a CD-ROM (Compact Disk Read Only Memory), a DVD-ROM (Digital Versatile Disk Read Only Memory), or a USB (Universal Serial Bus) memory. The program may also be downloaded from an external device via the network N.

[0074] Furthermore, in the above-described embodiments, the term "processor" refers to a processor in a broad sense, and includes general-purpose processors (e.g., CPU: Central Processing Unit, etc.) and dedicated processors (e.g., GPU: Graphics Processing Unit, ASIC: Application Specific Integrated Circuit, FPGA: Field Programmable Gate Array, programmable logic device, etc.).

[0075] Furthermore, the operations of the processors in the above-described embodiments may not only be performed by a single processor, but may also be performed by multiple processors located at physically separate locations working together. Furthermore, the order of the operations of the processors is not limited to the order described in the above-described embodiments, and may be changed as appropriate.

[0076] The following additional notes are provided regarding the above-described embodiments.

[0077] (((1))) a processor; The processor: acquiring attribute information from a job executed by the image processing device, and storing job log information including at least the attribute information; creating recommendation information that recommends products or services related to the job log information from search results obtained by searching the Internet based on the job log information; An information processing system that outputs the recommendation information to a user.

[0078] (((2))) The processor: Based on the job log information, the recommendation information is created from search results obtained within a predetermined range of the company's products or services. An information processing system as described in (((1))) that creates the recommendation information from search results obtained by searching the Internet when the recommendation information cannot be created from search results obtained within the scope of the company's own products or services.

[0079] (((3))) The processor: The information processing system according to (((1))) or (((2))) creates the recommendation information based on the job log information and attribute information of the job being executed by the image processing device.

[0080] (((4))) The processor: An information processing system described in any one of (((1))) to (((3))), wherein when the job log information satisfies a predetermined condition, a search is performed on the Internet using a predetermined template for that condition.

[0081] (((5))) The processor: An information processing system described in any one of (((1))) to (((4)))) that generates keywords to search on the Internet by inputting the job log information into a sentence generation model that generates sentences based on input sentences.

[0082] (((6))) The processor: Organizing the product or service information obtained from the search results of the Internet search into predetermined categories; The information processing system according to any one of (((1))) to (((5)))) scores the degree of compatibility with the job log information and recommends search results with a predetermined score or higher.

[0083] (((7))) The processor: The information processing system according to (((6))) above, wherein after a predetermined number of search results equal to or higher than the score are obtained, the search results with the highest scores are recommended to the user.

[0084] (((8))) The processor: An information processing system according to any one of (((1))) to (((7))), which does not recommend products or services that have already been used.

[0085] (((9))) On the computer, acquiring attribute information from a job executed by the image processing device, and storing job log information including at least the attribute information; creating recommendation information that recommends products or services related to the job log information from search results obtained by searching the Internet based on the job log information; A program for executing a process for outputting the recommendation information to a user.

[0086] According to (((1))), it is possible to increase the number of options for recommended products or services compared to when the products or services to be recommended are registered in advance.

[0087] According to (((2))), there is an effect that the company's own products or services can be recommended with priority over products or services of other companies.

[0088] According to (((3))), it is possible to provide a recommendation that reflects the user's usage history of the image processing device.

[0089] According to (((4))), it is possible to perform a search on the Internet using a fixed phrase.

[0090] According to (((5))), it is possible to perform a search on the Internet using a sentence generation model, and it is possible to use an information processing system to reflect the results in a management device and make settings.

[0091] According to (((6))), it is possible to prevent recommendations that differ from the user's usage history of the image processing device from being made.

[0092] According to (((7))), it is possible to recommend products or services that are highly compatible with the user's usage history of the image processing device.

[0093] According to (((8))), it is possible to prevent the recommendation of products or services that are unnecessary for the user.

[0094] According to (((9))), there is an advantage that the number of options for recommended products or services can be increased compared to when the products or services to be recommended are registered in advance. [Explanation of symbols]

[0095] 10 Recommendation Systems 20 Image processing device 30 Information processing equipment

Claims

1. a processor; The processor: acquiring attribute information from a job executed by the image processing device, and storing job log information including at least the attribute information; creating recommendation information that recommends products or services related to the job log information from search results obtained by searching the Internet based on the job log information; An information processing system that outputs the recommendation information to a user.

2. The processor: Based on the job log information, the recommendation information is created from search results obtained within a predetermined range of the company's products or services. The information processing system of claim 1 , wherein if the recommendation information cannot be created from search results within the scope of the company's products or services, the recommendation information is created from search results obtained by searching the Internet.

3. The processor: The information processing system according to claim 1 , wherein the recommendation information is created based on the job log information and attribute information of the job currently being executed by the image processing device.

4. The processor:

2. The information processing system according to claim 1, wherein when the job log information satisfies a predetermined condition, a search is performed on the Internet using a predetermined fixed phrase for the condition.

5. The processor:

2. The information processing system according to claim 1, wherein the job log information is input to a sentence generation model that generates a sentence according to an input sentence, thereby generating keywords to be searched on the Internet.

6. The processor: Organizing the product or service information obtained from the search results of the Internet search into predetermined categories; The information processing system according to claim 1 , wherein a degree of compatibility with the job log information is scored, and search results having a predetermined score or higher are recommended.

7. The processor: The information processing system according to claim 6 , wherein after a predetermined number of search results having a score equal to or higher than the score are obtained, the search results having the highest scores are recommended to the user.

8. The processor: The information processing system according to claim 1 , wherein products or services that have already been used are not recommended.

9. On the computer, acquiring attribute information from a job executed by the image processing device, and storing job log information including at least the attribute information; creating recommendation information that recommends products or services related to the job log information from search results obtained by searching the Internet based on the job log information; A program for executing a process for outputting the recommendation information to a user.

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