WO2021225575A1 - Création de profil de dispositif optimal - Google Patents

Création de profil de dispositif optimal Download PDF

Info

Publication number
WO2021225575A1
WO2021225575A1 PCT/US2020/031328 US2020031328W WO2021225575A1 WO 2021225575 A1 WO2021225575 A1 WO 2021225575A1 US 2020031328 W US2020031328 W US 2020031328W WO 2021225575 A1 WO2021225575 A1 WO 2021225575A1
Authority
WO
WIPO (PCT)
Prior art keywords
print
print job
user
optimal
metrics
Prior art date
Application number
PCT/US2020/031328
Other languages
English (en)
Inventor
Frederico Souza GERMANO BETTING
Pedro FURLANETTO
Ricardo RIBANI
Original Assignee
Hewlett-Packard Development Company, L.P.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Hewlett-Packard Development Company, L.P. filed Critical Hewlett-Packard Development Company, L.P.
Priority to PCT/US2020/031328 priority Critical patent/WO2021225575A1/fr
Publication of WO2021225575A1 publication Critical patent/WO2021225575A1/fr

Links

Classifications

    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1223—Dedicated interfaces to print systems specifically adapted to use a particular technique
    • G06F3/1237—Print job management
    • G06F3/126—Job scheduling, e.g. queuing, determine appropriate device
    • G06F3/1262—Job scheduling, e.g. queuing, determine appropriate device by grouping or ganging jobs
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1202—Dedicated interfaces to print systems specifically adapted to achieve a particular effect
    • G06F3/1211—Improving printing performance
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1278—Dedicated interfaces to print systems specifically adapted to adopt a particular infrastructure
    • G06F3/1285—Remote printer device, e.g. being remote from client or server
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/04—Architecture, e.g. interconnection topology
    • G06N3/045—Combinations of networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/00832—Recording use, e.g. counting number of pages copied
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N1/00—Scanning, transmission or reproduction of documents or the like, e.g. facsimile transmission; Details thereof
    • H04N1/23—Reproducing arrangements
    • H04N1/2307—Circuits or arrangements for the control thereof, e.g. using a programmed control device, according to a measured quantity
    • H04N1/2361—Selecting a particular reproducing device from amongst a plurality of devices, e.g. high or low resolution devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
    • G06F3/12—Digital output to print unit, e.g. line printer, chain printer
    • G06F3/1201—Dedicated interfaces to print systems
    • G06F3/1202—Dedicated interfaces to print systems specifically adapted to achieve a particular effect
    • G06F3/1218—Reducing or saving of used resources, e.g. avoiding waste of consumables or improving usage of hardware resources
    • G06F3/1219—Reducing or saving of used resources, e.g. avoiding waste of consumables or improving usage of hardware resources with regard to consumables, e.g. ink, toner, paper

Definitions

  • Multi-function devices often combine different components such as a printer, scanner, and copier into a single device. Such devices frequently receive refills of consumables, such as print substances (e.g., ink, toner, and/or additive materials) and/or media (e.g., paper, vinyl, and/or other print substrates).
  • print substances e.g., ink, toner, and/or additive materials
  • media e.g., paper, vinyl, and/or other print substrates
  • FIG. 1 is a block diagram of an example computing device for providing optimal device profile creation.
  • FIG. 2 is a flowchart of an example method for providing optimal device profile creation.
  • FIG. 3 is a block diagram of an example system for providing optimal device profile creation.
  • MFPs multi-function-print devices
  • the scanning portion of an MFP may comprise an optical assembly located within a sealed enclosure.
  • the sealed enclosure may have a scan window through which the optical assembly can scan a document, which may be placed on a flatbed and/or delivered by a sheet feeder mechanism.
  • a device such as a printing device, that offers a suboptimal set of capabilities.
  • Such sub-optimal devices may not have necessary features, such as photograph quality color, connectivity, finishing options (e.g., stapling, binding, duplexing, etc.), and/or job type support (e.g., scanning, faxing, emailing, copying, etc.).
  • sub-optimal devices may offer more features than a user needs, resulting in a higher cost to print, own, and/or maintain the device.
  • an optimal device profile may be created.
  • Such a device profile may identify most-used features, such a job types and/or quality, as well as take account of outlying metrics to create an optimal device profile for the user(s).
  • An optimal device profile may also account for other devices accessible to a user(s), including third party services.
  • a user who regularly prints short office documents in black & white may find a printing device capable of photo-quality color to be cost-inefficient, even if they do occasionally print a picture.
  • the user may be recommended to utilize a lower-cost print device model for the majority of their printing and recommended to use another, higher-cost device only for specific jobs that need the additional features provided by the higher-cost device.
  • the user may be recommended to use a third party print service, such as a web-based photo ordering service and/or a print shop in order to provide services for which the regular print device is not as well suited,
  • users' profiles of past job metrics may be used to create an optimal device profile in order to recommend which of a set of available print device models best meets their needs at time of purchase- For example, a user who has already has and/or has access to a photo printer, but who regularly prints black and white text documents, may be provided with a recommendation of a mono laser printer as the optimal device profile,
  • Optimal characteristics may differ from user to user and may be based on analysis of the print job metrics associated with the user and/or specific inputs solicited from the user. For example, a user may be asked whether speed or cost is more important to their decision making, and the answer may be used to weigh criteria of available print models when creating an optimal device profile for that user. In some situations, however, a users behavior, as demonstrated by their print job metrics, may indicate that their actual preference may differ from their response to such a question. For example, a user may respond to such a question that cost efficiency is more important, but may also regularly override a shared print queue to prioritize the speed with which their own jobs are printed relative to other users, thus indicating that speed is of relatively high importance.
  • Deep learning is a specialized area of machine learning and/or artificial intelligence that may be used in different areas, such as computer vision, speech recognition, behavior prediction, text translation, etc.
  • a deep learning model refers to or includes a trained machine learning model that has undergone a training process and may make inferences from received data.
  • Example deep learning models include neural networks, such as convolution neural networks and deep neural networks. Such a model may be trained, for example, on a training corpus of other users’ job metrics, device profiles used by those users, and satisfaction surveys associated with those users.
  • a non-transitory machine-readable medium may store instructions executable by a processor to log a plurality of print job metrics for each of a plurality of print jobs, create an optimal device profile according to the plurality of print job metrics, identify an available print device model according to the optimal device profile, and provide a recommendation of the available print device model to a user.
  • methods for providing optimal device profile creation may comprise fogging a plurality of print job metrics for each of a plurality of print jobs, wherein each of the plurality of print job metrics comprise at least one job setting and at least one device feature used, creating an optimal device profile according to the plurality of print job metrics, identifying an available print device model according to the optimal device profile, and providing a recommendation of the available print device model to a user.
  • systems for providing optimal device profile creation may comprise a log engine to log a plurality of print job metrics for each of a plurality of print jobs associated with a user, a profile engine to create an optimal device profile according to the plurality of print job metrics and identify an available print device model according to the optimal device profile, and a recommendation engine to provide a recommendation of the available print device model to a user.
  • FIG. 1 is a block diagram of an example computing device 110 for providing optimal device profile creation.
  • Computing device 110 may comprise a processor 112 and a non-transitory, machine-readable storage medium 114, Storage medium 114 may comprise a plurality of processor-executable instructions, such as log print job metric instructions 120, create optimal device profile instructions 125, identify available print model instructions 130, and provide recommendation instructions 135.
  • instructions 120, 125, 130, 135 may be associated with a single computing device 110 and/or may be communicatively coupled among different computing devices such as via a direct connection, bus, or network.
  • Processor 112 may comprise a central processing unit (CPU), a semiconductor-based microprocessor, a programmable component such as a complex programmable logic device (CPLD) and/or field-programmable gate array (FPGA), or any other hardware device suitable for retrieval and execution of instructions stored in machine-readable storage medium 114,
  • processor 112 may fetch, decode, and execute instructions 120, 125, 130, 135,
  • Executable instructions 120, 125, 130, 135 may comprise logic stored in any portion and/or component of machine-readable storage medium 114 and executable by processor 112.
  • the machine-readable storage medium 114 may comprise both volatile and/or nonvolatile memory and data storage components. Volatile components are those that do not retain data values upon toss of power. Nonvolatile components are those that retain data upon a loss of power.
  • the machine-readable storage medium 114 may comprise, for example, random access memory (RAM), read-only memory (ROM), hard disk drives, solid-state drives, USB flash drives, memory cards accessed via a memory card reader, floppy disks accessed via an associated floppy disk drive, optical discs accessed via an optical disc drive, magnetic tapes accessed via an appropriate tape drive, and/or other memory components, and/or a combination of any two and/or more of these memory components.
  • the RAM may comprise, for example, static random access memory (SRAM), dynamic random access memory (DRAM), and/or magnetic random access memory ( MRAM) and other such devices.
  • the ROM may comprise, for example, a programmable read-only memory (PROM), an erasable programmable read-only memory (EPROM), an electrically erasable programmable read-only memory (EEPROM), and/or other like memory device.
  • PROM programmable read-only memory
  • EPROM erasable programmable read-only memory
  • EEPROM electrically erasable programmable read-only memory
  • Log print job metric instructions 120 may log a plurality of print job metrics for each of a plurality of print jobs.
  • Print job metrics may comprise, for example, details about the print jobs such as a print job setting, a print job size, a print job type, a print device component used, and a print device capability used.
  • Print job settings for example, may comprise color settings, resolution settings, finishing settings, page layouts, paper sizes, and the like.
  • print job types may comprise any operation capable of being performed by a print device, such as scanning, copying, faxing, transmitting, error correction, image enhancement, publishing and finishing operations, etc.
  • device components may comprise a scanner assembly, media handling components such as offset output trays, paper selections, and duplexing, facsimile components, and/or network components such as wireless and/or wired networks, Bluetooth, radio frequency, cellular, etc.
  • Device capabilities may include image manipulation and/or enhancement, color and/or resolution quality , speed, usable paper sizes, etc.
  • Print job metrics may, for example, be anonymized to remove actual data (e.g., the actual text, images, and/or other content of the print job) to protect user privacy.
  • the plurality of print jobs may be completed at a single print device and/or at a plurality of print devices.
  • the metrics logged may be associated with print jobs completed at multiple print devices associated with a user and/or plurality of users, such as print jobs completed at different devices within a fleet of printers owned by a person and/or organization.
  • the plurality of print job metrics may be stored on the single print device and/or on a network device.
  • the print job metrics may be stored in an on-board memory of the single print device.
  • the user may comprise an originating user for the plurality of print jobs.
  • the plurality of print jobs may be associated with a plurality of users.
  • Print job metrics may, for example, be anonymously aggregated across multiple users and multiple devices, such as when an optimal print device profile for a group of users is desired to be created,
  • Create optimal device profile instructions 125 may create an optimal device profile according to the plurality of print job metrics. Various factors learned from the logged print job metrics may be synthesized to create the optimal device profile, such as in a deep learning model. The model may take into account frequency of use of the device(s) and various features. The optimal device profile may offer a balance between features used, cost, and efficiency based on an analysis of the needs of the user(s).
  • a user who prints 90% of the time in duplexed black and white may receive an optimal device profile comprising a monochrome print device with a duplexer when an available color model may add an unacceptable, to the user(s), cost.
  • Identify available print model instructions 130 may identify an available print device model according to the optimal device profile.
  • the optimal device profile may comprise an alignment between a first plurality of print device features associated with the available print device model and a second plurality of print device features as logged in the plurality of print job metrics.
  • a plurality of available print models may comprise several lines such as home/small office, large office, and enterprise that are categorized based on their capacity for printing for a certain range and/or number of users that will use the print device.
  • device 110 may maintain and update a list of device models, their capabilities, and, in some implementations, a ranking score for each capability.
  • the capability lists may be compared to the optimal device profile to find an alignment where the optimal device profile matches as many of the capabilities of an available device model as possible.
  • the characteristics may comprise a ranked list in order of priority.
  • an optimal device profile may comprise characteristics such as:
  • Such an optimal device profile may, for example, be matched to a small office line, color laser-based multi-function printer with WiFi networking.
  • Such an available device may not comprise the low priority fax capability of the optimal device profile if, for example, the cost difference between a model with fax and without exceeds a configurable cost difference threshold.
  • Provide recommendation instructions 135 may provide a recommendation of the available print device model to a user, Once the available print device model has been identified, device 110 may provide that model as a recommendation to a user, for example, at a point of purchase to suggest which model the user should buy. For example, a service may be run on an e-commerce site to direct the user (e.g., by displaying or otherwise sending a link) to the recommended model's page on that site.
  • FIG. 2 is a flowchart of an example method 200 for optimal device profile creation. Although execution of method 200 is described below with reference to computing device 110, other suitable components for execution of method 200 may be used,
  • Method 200 may begin at stage 205 and advance to stage 210 where device 110 may log a plurality of print job metrics for each of a plurality of print jobs, wherein each of the plurality of print job metrics comprise at least one job setting and at least one device feature used.
  • device 110 may execute log print job metric instructions 120 to log a plurality of print job metrics for each of a plurality of print jobs.
  • Print job metrics may comprise, for example, details about the print jobs such as a print job seting, a print job size, a print job type, a print device component used, and a print device capability used.
  • Print job settings for example, may comprise color settings, resolution settings, finishing settings, page layouts, paper sizes, and the like.
  • print job types may comprise any operation capable of being performed by a print device, such as scanning, copying, faxing, transmitting, error correction, Image enhancement, publishing and finishing operations, etc.
  • device components may comprise a scanner assembly, media handling components such as offset output trays, paper selections, and duplexing, facsimile components, and/or network components such as wireless and/or wired networks, Bluetooth, radio frequency, cellular, etc.
  • Device capabilities may include image manipulation and/or enhancement, color and/or resolution quality, speed, usable paper sizes, etc.
  • Print job metrics may, for example, be anonymized to remove actual data (e.g. the actual text, images, and/or other content of the print job) to protect user privacy.
  • the plurality of print jobs may be completed at a single print device and/or at a plurality of print devices.
  • the metrics logged may be associated with print jobs completed at multiple print devices associated with a user and/or plurality of users, such as print jobs completed at different devices within a fleet of printers owned by a person and/or organization.
  • the plurality of print job metrics may be stored on the single print device and/or on a network device.
  • the print job metrics may be stored in an on-board memory of the single print device.
  • the user may comprise an originating user for the plurality of print jobs.
  • the plurality of print jobs may be associated with a plurality of users.
  • Print job metrics may, for example, be anonymously aggregated across multiple users and multiple devices, such as when an optimal print device profile for a group of users is desired to be created.
  • Method 200 may then advance to stage 220 where computing device 110 may create an optimal device profile according to the plurality of print job metrics.
  • device 110 may execute create optimal device profile instructions 125 to create an optimal device profile according to the plurality of print job metrics.
  • Various factors learned from the logged print job metrics may be synthesized to create the optimal device profile, such as in a deep learning model.
  • the model may take into account frequency of use of the device(s) and various features.
  • the optimal device profile may offer a balance between features used, cost, and efficiency based on an analysis of the needs of the user(s). For example, a user who prints 90% of the time In duplexed black and white may receive an optimal device profile comprising a monochrome print device with a duplexer when an available color model may add an unacceptable, to the user(s), cost,
  • Method 200 may then advance to stage 230 where computing device 110 may identify an available print device model according to the optimal device profile.
  • device 110 may execute identify available print model instructions 130 to identify an available print device model according to the optimal device profile.
  • the optimal device profile may comprise an alignment between a first plurality of print device features associated with the available print device model and a second plurality of print device features as logged in the plurality of print job metrics.
  • a plurality of available print models may comprise several lines such as home/small office, large office, and enterprise that are categorized based on their capacity for printing for a certain range and/or number of users that will use the print device.
  • different devices may offer different features and/or capabilities, such as finishing options, resolutions, color options, components (e.g., fax, scan, etc.), and/or communications.
  • device 110 may maintain and update a list of device models, their capabilities, and, in some implementations, a ranking score for each capability.
  • the capability lists may be compared to the optimal device profile to find an alignment where the optimal device profile matches as many of the capabilities of an available device model as possible.
  • the characteristics may comprise a ranked list in order of priority.
  • an optimal device profile may comprise characteristics such as:
  • Such an optimal device profile may, for example, be matched to a small office line, color laser-based multi-function printer with WiFi networking.
  • Such an available device may not comprise the tow priority fax capability of the optimal device profile if, for example, the cost difference between a model with fax and without exceeds a configurable cost difference threshold.
  • Method 200 may then advance to stage 240 where computing device 110 may provide a recommendation of the available print device model to a user.
  • device 110 may execute provide recommendation instructions 135 to provide a recommendation of the available print device model to a user.
  • device 110 may provide that model as a recommendation to a user, for example, at a point of purchase to suggest which model the user should buy.
  • a service may be run on an e-commerce site to direct the user (e.g., by displaying or otherwise sending a link) to the recommended model’s page on that site.
  • the recommendation of the available print device model comprises a recommended replacement for the at least one print device owned by the user.
  • Method 200 may then end at stage 250.
  • FIG. 3 is a block diagram of an example apparatus 300 for providing optimal device profile creation.
  • Apparatus 300 may comprise a multi-function printer device 302 comprising a storage medium 310, and a processor 312.
  • Device 302 may comprise and/or be associated with, for example, a general and/or special purpose computer, server, mainframe, desktop, laptop, tablet, smart phone, game console, printer, multi-function device, and/or any other system capable of providing computing capability consistent with providing the implementations described herein.
  • Device 302 may store, in storage medium 310, a log engine 320, a profile engine 325, and a recommendation engine 330.
  • Each of engines 320, 325, 330 may comprise any combination of hardware and programming to implement the functionalities of the respective engine, in examples described herein, such combinations of hardware and programming may be implemented in a number of different ways.
  • the programming for the engines may be processor executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the engines may include a processing resource to execute those instructions
  • the machine-readable storage medium may store instructions that, when executed by the processing resource, implement engines 320, 325, 330.
  • device 302 may comprise the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to apparatus 300 and the processing resource
  • Log engine 320 may log a plu rality of print job metrics for each of a plurality of print jobs associated with a user.
  • log engine 320 may execute log print job metric instructions 120 to log a plurality of print job metrics for each of a plurality of print jobs.
  • Print job metrics may comprise, for example, details about the print jobs such as a print job setting, a print job size, a print job type, a print device component used, and a print device capability used.
  • Print job settings for example, may comprise color settings, resolution settings, finishing settings, page layouts, paper sizes, and the like.
  • print job types may comprise any operation capable of being performed by a print device, such as scanning, copying, faxing, transmitting, error correction, image enhancement, publishing and finishing operations, etc.
  • device components may comprise a scanner assembly, media handling components such as offset output trays, paper selections, and duplexing, facsimile components, and/or network components such as wireless and/or wired networks, Bluetooth, radio frequency, cellular, etc.
  • Device capabilities may include image manipulation and/or enhancement, color and/or resolution quality, speed, usable paper sizes, etc.
  • Print job metrics may, for example, be anonymized to remove actual data (e.g., the actual text, images, and/or other content of the print job) to protect user privacy.
  • the plurality of print jobs may be completed at a single print device and/or at a plurality of print devices.
  • the metrics logged may be associated with print jobs completed at multiple print devices associated with a user and/or plurality of users, such as print jobs completed at different devices within a fleet of printers owned by a person and/or organization.
  • the plurality of print job metrics may be stored on the single print device and/or on a network device.
  • the print job metrics may be stored in an on-board memory of the single print device. In some situations, it may be more efficient to store the print job metrics by uploading them to a server, web service, and/or other network connected application for storage on a different device’s memory.
  • the user may comprise an originating user for the plurality of print jobs
  • the plurality of print jobs may be associated with a plurality of users.
  • Print job metrics may, for example, be anonymously aggregated across multiple users and multiple devices, such as when an optimal print device profile for a group of users is desired to be created.
  • Profile engine 325 may create an optimal device profile according to the plurality of print job metrics and identify an available print device model according to the optimal device profile. For example, profile engine 325 may execute create optimal device profile instructions 125 to create an optimal device profile according to the plurality of print job metrics. Various factors learned from the logged pri nt Job metrics may be synthesized to create the optimal device profile, such as in a deep learning model The model may take into account frequency of use of the device(s) and various features. The optimal device profile may offer a balance between features used, cost, and efficiency based on an analysis of the needs of the user(s). For example, a user who prints 90% of the time in duplexed black and white may receive an optimal device profile comprising a monochrome print device with a duplexer when an available color model may add an unacceptable, to the user(s), cost.
  • Profile engine 325 may further execute identify available print model instructions 130 to identify an available print device model according to the optimal device profile.
  • the optimal device profile may comprise an alignment between a first plurality of print device features associated with the available print device model and a second plurality of print device features as logged in the plurality of print job metrics.
  • a plurality of available print models may comprise several lines such as home/small office, large office, and enterprise that are categorized based on their capacity for printing for a certain range and/or number of users that will use the print device.
  • different devices may offer different features and/or capabilities, such as finishing options, resolutions, color options, components (e.g., fax, scan, etc. ⁇ , and/or communications.
  • device 110 may maintain and update a list of device models, their capabilities, and, in some implementations, a ranking score for each capability.
  • the capability lists may be compared to the optimal device profile to find an alignment where the optimal device profile matches as many of the capabilities of an available device model as possible.
  • the characteristics may comprise a ranked list in order of priority.
  • an optimal device profile may comprise characteristics such as:
  • Such an optimal device profile may, for example, be matched to a small office line, color laser-based multi-function printer with WiFi networking.
  • Such an available device may not comprise the tow priority fax capability of the optimal device profile if, for example, the cost difference between a model with fax and without exceeds a configurable cost difference threshold.
  • Recommendation engine 330 may provide a recommendation of the available print device model to a user.
  • recommendation engine 330 may execute provide recommendation instructions 135 to provide a recommendation of the available print device model to a user.
  • device 110 may provide that model as a recommendation to a user, for example, at a point of purchase to suggest which model the user should buy.
  • a service may be run on an e-commerce site to direct the user (e.g., by displaying or otherwise sending a link) to the recommended model’s page on that site.
  • the optimal device profile may comprise an alignment between a first plurality of print device features associated with the available print device model and a second plurality of print device features as logged in the plurality of print job metrics,

Landscapes

  • Engineering & Computer Science (AREA)
  • Theoretical Computer Science (AREA)
  • Physics & Mathematics (AREA)
  • General Physics & Mathematics (AREA)
  • General Engineering & Computer Science (AREA)
  • Human Computer Interaction (AREA)
  • General Health & Medical Sciences (AREA)
  • Biomedical Technology (AREA)
  • Data Mining & Analysis (AREA)
  • Evolutionary Computation (AREA)
  • Biophysics (AREA)
  • Molecular Biology (AREA)
  • Computing Systems (AREA)
  • Computational Linguistics (AREA)
  • Artificial Intelligence (AREA)
  • Mathematical Physics (AREA)
  • Software Systems (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Multimedia (AREA)
  • Signal Processing (AREA)
  • Health & Medical Sciences (AREA)
  • Facsimiles In General (AREA)

Abstract

Des exemples selon l'invention se rapportent à la consignation d'une pluralité de mesures de tâche d'impression pour chaque tâche d'une pluralité de tâches d'impression, à la création d'un profil de dispositif optimal en fonction de la pluralité de mesures de tâche d'impression, à l'identification d'un modèle de dispositif d'impression disponible en fonction du profil de dispositif optimal, et à la fourniture d'une recommandation du modèle de dispositif d'impression disponible à un utilisateur.
PCT/US2020/031328 2020-05-04 2020-05-04 Création de profil de dispositif optimal WO2021225575A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/US2020/031328 WO2021225575A1 (fr) 2020-05-04 2020-05-04 Création de profil de dispositif optimal

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/US2020/031328 WO2021225575A1 (fr) 2020-05-04 2020-05-04 Création de profil de dispositif optimal

Publications (1)

Publication Number Publication Date
WO2021225575A1 true WO2021225575A1 (fr) 2021-11-11

Family

ID=78468166

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/US2020/031328 WO2021225575A1 (fr) 2020-05-04 2020-05-04 Création de profil de dispositif optimal

Country Status (1)

Country Link
WO (1) WO2021225575A1 (fr)

Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5969796A (en) * 1996-07-30 1999-10-19 Fuji Photo Film Co., Ltd. Method for determining a state of processing solution in a printer processor and a printer processor
US6407821B1 (en) * 1998-09-08 2002-06-18 International Business Machines Corporation Method and apparatus for printing documents including embedded print objects with an intelligent printing system
US20060206445A1 (en) * 2005-03-14 2006-09-14 Xerox Corporation Probabilistic modeling of shared device usage
US20180145908A1 (en) * 2016-11-21 2018-05-24 Cisco Technology, Inc. System and method for forwarder connection information in a content centric network

Patent Citations (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US5969796A (en) * 1996-07-30 1999-10-19 Fuji Photo Film Co., Ltd. Method for determining a state of processing solution in a printer processor and a printer processor
US6407821B1 (en) * 1998-09-08 2002-06-18 International Business Machines Corporation Method and apparatus for printing documents including embedded print objects with an intelligent printing system
US20060206445A1 (en) * 2005-03-14 2006-09-14 Xerox Corporation Probabilistic modeling of shared device usage
US20180145908A1 (en) * 2016-11-21 2018-05-24 Cisco Technology, Inc. System and method for forwarder connection information in a content centric network

Similar Documents

Publication Publication Date Title
US7880912B2 (en) Network printing system having automated selection of a destination printer
JP5702538B2 (ja) 統制ルール及びポリシーに基づくデータを追跡するための方法及びシステム
US20170054860A1 (en) Image forming apparatus, management apparatus, non-transitory computer-readable storage medium and load control method
US8818032B2 (en) Image processing system, image processing apparatus and server in the image processing system, and data control method and storage medium storing program thereof
US20090021782A1 (en) Image forming system, recording medium having image forming program recorded thereon and image forming apparatus
EP2287720A2 (fr) Procédé et système de création automatique de règles et politiques d'environnement d'impression
US20180097959A1 (en) Image forming apparatus, method for controlling image forming, apparatus and storage medium
WO2021225575A1 (fr) Création de profil de dispositif optimal
US20200394004A1 (en) Apparatus and method for sharing a printable electronic document between users
US10976977B2 (en) Apparatus and method for managing the printing of an electronic document having multiple page sizes
US20220070325A1 (en) Information processing apparatus
US11140283B2 (en) Action tags for multi-function devices to build a job
JP6459793B2 (ja) 情報処理装置及びプログラム
US11231893B2 (en) System and method for printing and reusing customized sample sets while printing documents
US10915273B2 (en) Apparatus and method for identifying and printing a replacement version of a document
US20200310699A1 (en) Management apparatus and terminal apparatus
US10789029B2 (en) Systems and methods for managing one or more incomplete jobs in a multi-function device
US9232084B2 (en) Tracking source of job parameters in print jobs
US20150373220A1 (en) Image processing apparatus and image processing system
US11829671B2 (en) Transfer of print queues via machine readable codes
US12124746B2 (en) Printing control apparatus and non-transitory computer readable medium storing program that manage output of document data based on printing restriction information
US9030707B2 (en) Log image creating system that creates log image of job in image forming apparatus
US20220385556A1 (en) Communication asset usage metrics
US11635926B2 (en) Printer identifying characteristics
US10761787B1 (en) Method and system for detection and avoidance of duplicate print jobs with pre-imaging technique using document stacker and central system

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 20934685

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

122 Ep: pct application non-entry in european phase

Ref document number: 20934685

Country of ref document: EP

Kind code of ref document: A1