Information processing apparatus, image forming apparatus, and content evaluation method

Abstract

To provide an information processing apparatus which can support improvement in quality of a content to be posted in a print service in which a user other than a poster prints and outputs a content posted by the poster.SOLUTION: The information processing apparatus comprises: a posting unit which receives posting of a content; and a processing unit which determines an evaluation value of the posted content on the basis of collected data. The processing unit generates feedback information according to the determined evaluation value and outputs the generated feedback information together with the evaluation value to a poster of the content.SELECTED DRAWING: Figure 1

Description

Technical Field

[0001] The present disclosure relates to an information processing apparatus and the like.

Background Art

[0002] Among the online services provided at convenience stores and the like, there is a printing service that allows other users other than the poster to print and output by registering and sharing the content posted by the poster.

[0003] In such a printing service, in order to increase the number of prints of the content, the poster needs to provide content of the quality required by other users.

[0004] For example, Patent Document 1 describes a technique for determining the evaluation value of content before it becomes available by using the evaluation value of the keyword of the content calculated based on the keyword of the content before it becomes available and the related content after it becomes available.

[0005] Further, Patent Document 2 describes a technique for generating content including information indicating the number of searches and the growth rate of the number of searches for each search target corresponding to the selected category based on the selected category and the generated search target information.

Prior Art Documents

Patent Documents

[0006]

Patent Document 1

Patent Document 2

Summary of the Invention

Problems to be Solved by the Invention

[0007] The present disclosure aims to provide an information processing apparatus and the like that can assist in improving the quality of content to be posted in a printing service in which other users than the poster print and output the content posted by the poster.

Means for Solving the Problems

[0008] In order to solve the above problems, an information processing apparatus according to the present disclosure includes a posting unit that receives a posting of content, and a processing unit that determines an evaluation value of the posted content based on the collected data. The processing unit generates feedback information corresponding to the determined evaluation value, and outputs the generated feedback information together with the evaluation value to the poster of the content.

[0009] Further, an image forming apparatus according to the present disclosure includes a posting unit that receives a posting of content, a processing unit that determines an evaluation value of the posted content based on the collected data, and an image forming unit that forms an image of the content. The processing unit outputs the feedback information corresponding to the determined evaluation value together with the evaluation value to the poster of the content.

[0010] Further, a content evaluation method according to the present disclosure is a content evaluation method that receives a posting of content and determines an evaluation value of the posted content based on the collected data. The method generates feedback information corresponding to the determined evaluation value, and outputs the generated feedback information together with the evaluation information to the poster of the content.

Advantages of the Invention

[0011] According to the present disclosure, it is possible to provide an information processing apparatus and the like that can assist in improving the quality of content to be posted in a printing service in which other users than the poster print and output the content posted by the poster.

Brief Description of the Drawings

[0012]

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Mode for Carrying Out the Invention

[0013] Hereinafter, embodiments of the present disclosure will be described with reference to the drawings. Note that the following embodiments are examples for explaining the present disclosure, and the technical content of the description described in the claims is not limited to the following description.

[0014] In the printing services provided at convenience stores and the like, there is a function that allows users other than the poster to print and output the content by registering and sharing the content. Here, the content according to the present disclosure is intended to be valuable information that can be formed (printed) on a paper medium such as paper based on texts, photos, graphics, designs, etc., and output as a printed matter.

[0015] Generally, those who create content submit the content in pursuit of profit or fame. However, depending on the content submitted, the number of prints may increase or may not increase.

[0016] It is considered that the increase in the number of prints of the content is affected not only by the content itself but also by the fact that the content involves printed output. However, not all posters can fully utilize the functions provided by the printing service, and currently, posters are using it blindly.

[0017] In order to promote activation as an online service, there has been a demand for support means that gives posters opportunities to trial and error for improving the quality of content and can expect a significant increase in the number of prints of the content.

[0018] In the present disclosure, in a printing service in which other users than the poster can print and output the content submitted by the poster, an information processing apparatus and the like that can support improving the quality of the content to be submitted are realized in the following embodiments.

[0019] [1 First Embodiment] The first embodiment is in the form of an information processing apparatus that includes a submission unit that receives submissions of content and a processing unit that determines an evaluation value of the submitted content based on the collected data. The processing unit generates feedback information according to the determined evaluation value and outputs the generated feedback information together with the evaluation value to the poster of the content.

[0020] [1.1 Connection form of the information processing apparatus 10] FIG. 1 is a diagram for explaining an example of the connection form of the information processing apparatus 10 according to the first embodiment. The information processing apparatus 10 is connected so as to be communicable with the terminal device 30 via the network NW. Here, examples of the network NW include a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, a telephone line, a FAX line, etc. However, the information processing apparatus 10 may be communicably connected to the terminal device 30 by a short-range wireless communication technology such as Bluetooth (registered trademark), Wi-Fi (registered trademark), IrDA, etc.

[0021] In addition, the information processing apparatus 10 is connected to the Internet 50. The information processing apparatus 10 collects model learning data described later from an SNS (Social Network Service) or the like on the Internet 50, and acquires information (similar image information) of an image similar to the content.

[0022] Note that in FIG. 1, the information processing apparatus 10 is shown in a form connected to the terminal device 30 via the network NW, but the information processing apparatus 10 may be connected to the terminal device 30 via the Internet 50. The connection form of the information processing apparatus 10 is not particularly limited as long as it is a configuration capable of communicating between the terminal device 30 and an SNS or the like on the Internet 50.

[0023] In addition, an image forming apparatus such as a printer (not shown) that prints and outputs the posted content may be connected to the information processing apparatus 10.

[0024] [1.2 Functional configuration] [1.2.1 About the information processing apparatus 10] FIG. 2 is a diagram for explaining the functional configuration of the information processing apparatus 10. The information processing apparatus 10 functions as an NWP (Numerical Weather Prediction) server that performs hit prediction as an evaluation value in response to the transmission of content from the terminal device 30 (hereinafter, the transmission of content to the information processing apparatus 10 is referred to as "posting", and the person who operates the terminal device 30 to post content is referred to as the poster), and outputs feedback information corresponding to the hit prediction to the terminal device 30 together with the hit prediction. The information processing apparatus 10 can be configured as a computer that operates under the control of a specific OS (Operating System). Such an information processing apparatus 10 includes a control unit 11, an operation input unit 13, a communication unit 15, and a storage unit 17.

[0025] The control unit 11 controls the entire information processing apparatus 10. The control unit 11 is configured by, for example, one or a plurality of arithmetic devices (CPU (Central Processing Unit), SoC (System on a Chip), etc.). The control unit 11 realizes its functions by reading and executing various programs stored in the storage unit 17.

[0026] The operation input unit 13 is an input device that receives input of information by a user or the like. The operation input unit 13 can use, for example, input devices such as a keyboard, a mouse, and a touch panel.

[0027] The communication unit 15 includes, for example, a wired / wireless interface or both for communicating with other devices (such as the terminal device 30 and SNS on the Internet 50) via a LAN (Local Area Network), a WAN (Wide Area Network), the Internet, a telephone line, or the like. Note that the communication unit 15 may include an interface related to (short-range) wireless communication technologies such as Bluetooth (registered trademark), Wi-Fi (registered trademark), ZigBee (registered trademark), IrDA, and wireless USB.

[0028] The storage unit 17 is one or more storage devices that store various programs and various data necessary for the operation of the information processing apparatus 10. The storage unit 17 can be configured by storage devices such as a RAM (Random Access Memory), an HDD (Hard disk Drive), an SSD (Solid State Drive), and a ROM (Read Only Memory), for example.

[0029] In the first embodiment, the storage unit 17 stores a control program 171, a processing program 173, and a posting processing program 175, and secures a history information storage area 177 and a user information storage area 179.

[0030] The control program 171 is a program read by the control unit 11 when comprehensively controlling the information processing apparatus 10. The control unit 11 that has read the control program 171 functions as an OS, and controls the driving of hardware such as the operation input unit 13 and the communication unit 15, performs startup processing and termination processing of applications operating on the OS, and manages files.

[0031] The processing program 173 is a program read by the control unit 11 when predicting hits of posted content, collecting information (feature amounts) for the hit prediction, and analyzing a printed image related to the content. The control unit 11 that has read the processing program 173 functions as a processing unit. Such a processing program 173 includes a hit prediction program 1731, an information collection program 1733, and a printed image analysis program 1735.

[0032] The hit prediction program 1731 is a program that the control unit 11 reads when predicting the hit of the posted content. The control unit 11 that has read the hit prediction program 1731 generates a hit prediction value using a hit prediction model that uses the collected information (feature amount) for hit prediction as learning data. As the hit prediction model, logistic regression, SVM (Support-Vector Machine), decision tree, etc. can be used. However, it is also possible to generate a hit prediction value by ensemble learning such as bagging (random forest) or boosting that combines these hit prediction models, deep learning, etc.

[0033] The information collection program 1733 is a program that the control unit 11 reads when collecting learning data used in the hit prediction model. The control unit 11 that has read the information collection program 1733 collects the features of the content, the usage history of past content, and posting information and search information (hereinafter sometimes referred to as Internet information) on the SNS on the Internet 50.

[0034] The printed image analysis program 1735 is a program that the control unit 11 reads when analyzing a printed image related to the posted content, a printed image related to past hit old content, or a printed image related to similar content similar to the posted content described later.

[0035] The posting process program 175 is a program that the control unit 11 reads when performing reception of the posted content and output processing of the hit prediction value and feedback information for the posted content. The control unit 11 that has read the posting process program 175 functions as a posting unit by controlling the communication unit 15 and the like.

[0036] The history information storage area 177 is a storage area that stores history information such as registration information and usage history of content posted in the past.

[0037] The user information storage area 179 is a storage area that stores user information about the poster, login information, corporate information, etc.

[0038] [1.2.2 Regarding the terminal device 30] Figure 3 is a diagram for explaining the functional configuration of the terminal device 30. The terminal device 30 is a terminal device used for a user to post content and to obtain a hit prediction value, feedback information, etc. output from the information processing device 10. The terminal device 30 can be configured as a computer that operates under the control of a specific OS. Such a terminal device 30 includes a control unit 31, a display unit 33, an operation input unit 35, a communication unit 37, and a storage unit 39.

[0039] The control unit 31 controls the entire terminal device 30. The control unit 31 is composed of, for example, one or more arithmetic devices (CPU, SoC, etc.). The control unit 31 realizes its functions by reading and executing various programs stored in the storage unit 39.

[0040] The display unit 33 is a display device that displays various information to a user or the like. The display unit 33 can be configured by, for example, an LCD, an organic EL display, or the like.

[0041] The operation input unit 35 is an input device that receives input of information by a user or the like. The operation input unit 35 can use, for example, input devices such as a keyboard, a mouse, and a touch panel.

[0042] The communication unit 37 includes, for example, a wired / wireless interface or both for communicating with other devices (such as the information processing device 10) via a LAN, a WAN, the Internet, a telephone line, or the like. Note that the communication unit 37 may include an interface related to (short-range) wireless communication technologies such as Bluetooth (registered trademark), Wi-Fi (registered trademark), ZigBee (registered trademark), IrDA, and wireless USB.

[0043] The storage unit 39 is one or more storage devices that store various programs and various data necessary for the operation of the terminal device 30. The storage unit 39 can be configured by storage devices such as a RAM, an HDD, an SSD, a ROM, etc., for example.

[0044] In the first embodiment, the storage unit 39 stores a control program 391 and a posting process program 393, and secures a content storage area 395.

[0045] The control program 391 is a program that the control unit 31 reads out when comprehensively controlling the terminal device 30. The control unit 31 that has read out the control program 391 functions as an OS, controls the driving of hardware such as the display unit 33, the operation input unit 35, and the communication unit 37, performs startup processing and termination processing of applications operating on the OS, and file management, etc.

[0046] The posting process program 393 is a program that the control unit 11 reads out when posting content. The control unit 31 that has read out the posting process program 393 performs content posting processing on the information processing device 10.

[0047] The content storage area 395 is a storage area that stores content to be posted to the information processing device 10.

[0048] [1.2.3 About the Internet 50] The Internet 50 according to the present disclosure can use a known configuration as long as it can acquire Internet information, etc. from an SNS, etc. in response to a request by the information processing device 10. Therefore, the description of the functional configuration of the Internet 50 is omitted.

[0049] [1.3 Flow of processing] Next, the processing flow according to the first embodiment will be described. FIG. 4 is a sequence diagram for explaining the exchange of information (commands) among the user, the terminal device 30, the information processing device 10, and the Internet 50. In FIG. 4, it is described assuming that the content is posted to the information processing device 10 by the user via the terminal device 30.

[0050] The information processing device 10 collects learning data for the hit prediction model (hit prediction model learning data) from the Internet 50 according to an arbitrary learning period (S10).

[0051] When the hit prediction model learning data is collected (S20), the information processing device 10 generates a hit prediction learning model. If a hit prediction model has already been generated, the generated hit prediction model may be updated using the collected hit prediction model learning data.

[0052] When a request operation for a hit prediction value is performed on the terminal device 30 by the user, for example, by selecting a hit prediction button or the like on a setting screen (not shown) (S30), the terminal device 30 makes a request to the information processing device 10 for obtaining hit prediction information and illegal information (S40).

[0053] Upon receiving the request for obtaining hit prediction information and illegal information, the information processing device 10 performs a search for similar image information on the Internet 50 (S50).

[0054] Here, the search for similar image information can be performed using, as an index, the image recognition result between the registered content described later and the content to be searched. In this case, for example, the search for similar image information may be performed by comparing the luminance distribution, color appearance rate, edges, etc. obtained by image recognition such as SIFT (Scale-Invariant Feature Transform) or HOG (Histograms of Oriented Gradients) processing.

[0055] When similar image information is acquired (S60), the information processing apparatus 10 determines whether the similarity is equal to or greater than a predetermined threshold as the second threshold, and outputs the determination result as illegal information. Here, when the similarity is equal to or greater than the predetermined threshold as the second threshold, the content submitted and the content to be searched for are the same content, and the submitted content is likely to be an imitation or plagiarism. In this case, the information processing apparatus 10 generates illegal information including that fact as the notification content.

[0056] The information processing apparatus 10 outputs to the terminal device 30 the hit prediction information including the hit prediction value generated by the hit prediction model and the illegal information (S70). Then, the terminal device 30 displays the input hit prediction information and illegal information to the user (S80).

[0057] Next, the process related to the generation of the hit prediction value will be described with reference to FIGS. 5 and 6, starting from the generation (update) of the hit prediction model by the information processing apparatus 10. Note that the process described with reference to FIG. 5 is a process executed by the control unit 11 of the information processing apparatus 10 reading a processing program 173 or the like.

[0058] When starting the process, the control unit 11 determines whether the learning period for generating the hit prediction model has arrived (step S100). Note that the learning period is not particularly limited, and it may be determined that the learning period has arrived based on a predetermined date and time, a predetermined date and time interval, or an input of a generation / update instruction by the user. When it is determined that the learning period has arrived, the control unit 11 acquires the characteristics of the content, the usage history of past content, and Internet information as learning data (step S100; Yes → step S110). On the other hand, when it is determined that the learning period has not arrived, the control unit 11 waits until the learning period arrives (step S100; No).

[0059] The control unit 11 extracts feature quantities related to the generation of a hit prediction model from the features of the registered content, past usage history, Internet information, etc. (step S120). Here, an example of the feature quantities for generating the hit prediction model will be described with reference to FIG. 6.

[0060] FIG. 6 is a table summarizing an example of the feature quantities for generating the prediction model. In the present disclosure, the features of the content, the past usage history of the content, Internet information, and the achievements of the poster are targeted as the feature quantities. Here, the content ID is an identifier for uniquely identifying the content registered in the information processing apparatus 10. Content features 1, 2, 3,... are parameters of the printed image of the content identified by the content ID, and represent, for example, the image size (feature 1), aspect ratio (feature 2), resolution (feature 3),... etc. Usage history 1, 2, 3,... is the usage history of the content identified by the content ID, and represents, for example, the number of uses (usage history 1), the number of printed sheets (usage history 2), hit (whether it was hit)? (usage history 3),... etc. Internet information 1, 2, 3,... is the search result of the keywords included in the content identified by the content ID, and represents, for example, the search word (Internet information 1), the number of occurrences (Internet information 2), the number of search sites (Internet information 3),... etc. Poster A achievements 1, 2, 3,... are the posting achievements of poster A who posted the content identified by the content ID, and represent, for example, the number of postings (poster achievement 1), the posting date and time (poster achievement 2), the number of hits (poster achievement 3),... etc. The evaluation value represents the hit prediction value (evaluation value) in the hit prediction model of the content identified by the content ID.

[0061] In the example shown in Figure 6, for example, the characteristics of the content identified by content ID "0020" are content features (image size (210x297mm), aspect ratio (5:7), resolution (600 dpi),...), usage history (number of uses (110), number of prints (200), hits? (Yes),...), Internet information (search word (final), number of occurrences (55), number of search sites (50),...), and poster A's track record (number of posts (0), posting date and time (0), number of hits (0),...).

[0062] Note that FIG. 6 shows an example of feature amounts as learning data for a hit prediction model according to the present disclosure, and the types and dimensions of feature amounts to be collected can be changed as appropriate depending on the hit prediction model to be generated.

[0063] Returning to FIG. 5, after extracting the feature amounts, the control unit 11 generates or updates a hit prediction model (step S130).

[0064] Next, the control unit 11 determines whether or not a hit prediction instruction input has been received from the user (terminal device 30) (step S140). If it is determined that a hit prediction instruction input has been received, the control unit 11 generates a hit prediction value using the hit prediction model generated or updated in step S130 (step S140; Yes → step S150).

[0065] For example, as an example of a hit prediction model, a first hit prediction value can be determined as a first evaluation value based on a comparison between a predetermined number of frequently appearing keywords included in either or both of SNS posting information and internet search information and keywords included in the posted content using a hit prediction model that uses feature amounts (internet information) as learning data. In this case, it is also possible to weight the feature amounts (poster performance 1, 2, 3, ...) of the poster as a registrant and the first hit prediction value to determine a hit prediction value (third hit prediction value as a third evaluation value).

[0066] Also, for example, as another example of the hit prediction model, by using a hit prediction model that uses feature quantities (usage history) as learning data, old content that has hit in the past is specified, and the similarity between the posted content and the specified old content can be determined as a second hit prediction value.

[0067] Note that when it is determined that the hit prediction instruction input has not been received, the control unit 11 waits until the instruction input is received (step S140; No).

[0068] Next, the generation process of the feedback information will be described using the flowchart of FIG. 7. The process described in FIG. 7 is also a process executed by the control unit 11 reading a processing program 173 or the like.

[0069] When starting the process, the control unit 11 specifies old content that is related to the registered content and has hit in the past (step S200).

[0070] Next, the control unit 11 determines the similarity between the posted content and the old content (step S210). The similarity determined in step S210 is a second hit prediction value using as an index whether the posted content is optimal for the printing settings, resolution of the printed image, aspect ratio, frequently printed settings, etc. adopted by the hit old content.

[0071] Then, the control unit 11 determines whether the second hit prediction value is lower than a predetermined threshold value as the first threshold value (step S220). When it is determined that the second hit prediction value is lower than the first threshold value, the control unit 11 generates information related to the difference between the second evaluation value and the first threshold value as feedback information (step S220; Yes → step S230).

[0072] The control unit 11 generates, as feedback information, any one of information regarding the printed image of the posted content, information regarding the print settings of the printed image, or information regarding the release timing of the posted content. Here, when the information related to the difference between the second evaluation value and the first threshold value is the information regarding the release timing of the posted content, the control unit 11 can determine the release timing of the posted content based on, for example, the frequency trend of the keywords included in either one or both of the SNS posting information and the search information on the Internet and the keywords included in the posted content.

[0073] The control unit 11 outputs the generated feedback information together with the second hit prediction value and ends the process (step S240). If it is determined that the second hit prediction value is not lower than the first threshold value, the control unit 11 omits the processes related to step S230 and step S240 and ends the process (step S220; No).

[0074] [1.4 Operation Example] Next, an operation example according to the first embodiment will be described. FIG. 8 is an example of a display configuration of a display screen W10 that displays the hit prediction value output from the information processing apparatus 10, the feedback information, and the illegal information. The display screen W10 is displayed on the display unit 33 of the terminal device 30. By checking the display content of the display screen W10, the user can improve the quality of the content posted as the poster.

[0075] Such a display screen W10 includes an illegal information display area R10, feedback information display areas R12A and R12B, and a hit prediction value graph display area R20.

[0076] The illegal information display area R10 is a display area that displays the similarity determination result between the posted content (aaa.jpg) and the content related to the similar image information. FIG. 8 is an example in which "No similar images were found." is notified (displayed) as the illegal information.

[0077] The feedback information display areas R12A and R12B are display areas for displaying the feedback information generated in the process according to step S230 of FIG. 7. FIG. 8 shows, as feedback information, the release timing (R12A) of the posted content such as "It seems more likely to resonate than last time. The recommended diffusion date on SNS is tomorrow.", and an example of displaying the recommended quality (R12B) for printing of the posted content such as "Recommended quality: It seems to be even better if you increase the font size.".

[0078] The hit prediction value graph display area R20 is a graph content in which the hit prediction value (hit rate: vertical axis) generated in step S150 of FIG. 5 is plotted against the SNS diffusion date (horizontal axis). As shown in the example in FIG. 8, in addition to the prediction value in the case of the current registration settings, the hit prediction value in the case where the printing settings with the recommended quality displayed in the feedback information display area R12B are applied is also displayed, so that the user can easily grasp the hit rate and diffusion date that can be expected when the recommended quality is applied.

[0079] FIG. 9 is an example of the display configuration of the display screen W20 in which the display content of the illegal information display area R10 is different. FIG. 9 shows that the posted content and the content to be searched are the same content, and there is a high possibility that the posted content is an imitation or plagiarism, and an example of notifying (displaying) in the illegal information display area R10 "Similar images have been found online. Please confirm that there is no problem with the copyright before using."

[0080] As described above, in the first embodiment, the user can obtain the hit prediction value for the posted content and the feedback information corresponding to the hit prediction value. According to the first embodiment, since the hit rate and diffusion date that can be expected when the recommended quality is applied can be easily grasped, the quality of the content to be posted can be improved.

[0081] [2 Second Embodiment] The second embodiment provides a selection means (checkbox) for receiving a selection as to whether to execute hit prediction for the setting screen, and when the execution of the hit prediction is effective, executes hit prediction for images related to all content at the time of content registration.

[0082] Since the functional configuration of the information processing apparatus 10 and the like according to the second embodiment can be made substantially the same as that of the first embodiment, the description thereof is omitted here.

[0083] [2.1 Flow of Processing] FIG. 10 is a sequence diagram for explaining the exchange of information (commands) among the user, the terminal device 30, the information processing apparatus 10, and the Internet 50 according to the second embodiment. For the same exchanges as those described in FIG. 4, the same reference numerals are given and the description thereof is omitted.

[0084] The user registers content to be posted to the terminal device 30 (S90). When the content is registered, the terminal device 30 transmits the content to the information processing apparatus 10 (S100).

[0085] When the information processing apparatus 10 receives the content, it requests the Internet 50 to search for similar image information (S50). When receiving the similar image information, the information processing apparatus 10 transmits a content registration completion notification to the terminal device 30 (S110). The terminal device 30 that has received the content registration completion notification notifies the user of the completion of content registration (S120).

[0086] Then, when a request operation for a hit prediction value is performed on the terminal device 30 by selecting a hit prediction button or the like on the setting screen described later (S30), the exchanges related to S40, S70, and S80 are performed between the terminal device 30 and the information processing apparatus 10.

[0087] [2.2 Operation Example] FIG. 11 is an example of a display configuration of a setting screen W30 provided with a check box T10 for receiving a selection as to whether to execute hit prediction. When the user checks the check box T10, a hit prediction button B10 illustrated in FIG. 12 is displayed on the setting screen W30, and a request for a hit prediction value becomes possible. Note that when the check box T10 shown in FIG. 11 is not checked, the hit prediction button B10 is not displayed on the setting screen W30.

[0088] As illustrated in FIG. 12, while hit prediction is being executed by selecting the hit prediction button B10, the display of the hit prediction button B10 is changed to "Hit prediction in progress" until the hit prediction is completed. Then, when the hit prediction is completed, the display of the hit prediction button B10 returns to "Hit prediction button".

[0089] As described above, according to the second embodiment, in addition to the effects of the first embodiment, by checking the check box T10 on the setting screen W30 in advance, hit prediction becomes effective, and the user can execute hit prediction for a printed image related to the content without performing a special operation just by posting the content.

[0090] [3 Third Embodiment] The third embodiment is a form in which the information processing apparatus 10 according to the first embodiment or the second embodiment is applied to an image forming apparatus.

[0091] The image forming apparatus can be configured as a multifunction machine 100 capable of realizing various types of jobs such as a print job, a copy job, a scan job, a fax job, and an image transmission job in one housing, for example.

[0092] In addition to the configuration of the information processing apparatus 10, the multifunction machine 100 includes an image processing unit 19. The image processing unit 19 includes an image forming unit 191 and an image input unit 193. The image forming unit 191 feeds paper from a paper feeding unit (not shown), forms an image based on image data on the paper, and then discharges the paper to a paper discharging unit (not shown). The image forming unit 191 can be configured by, for example, a laser printer or the like that employs an electrophotographic method. In this case, the image forming unit 191 forms an image using toner supplied from a toner cartridge (not shown) corresponding to toner colors (for example, cyan, magenta, yellow, black).

[0093] The image input unit 193 generates image data by scanning a document. The image input unit 193 can be configured as, for example, an image sensor such as a CCD (Charge Coupled Device) or a CIS (Contact Image Sensor), in addition to an automatic document feeder (ADF) or a scanner device having a flatbed for placing and reading a document. The image input unit 193 is not particularly limited in its configuration as long as it can generate image data by reading a reflected light image from a document image with an image sensor. Note that the image input unit 193 can also be configured as an interface capable of acquiring image data stored in a storage medium such as a USB memory or image data transmitted from an external terminal device (not shown). Note that the image processing unit 19 may be configured to generate image data for image transmission by performing, for example, shading correction or density correction on the image data input from the image input unit 193.

[0094] As described above, according to the third embodiment, in addition to the effects according to the first embodiment or the second embodiment, since it is possible to output a printed image related to the content posted in the image processing unit 19, the convenience for the user can be further improved.

[0095] The present disclosure is not limited to the above-described embodiments, and various modifications are possible. That is, embodiments obtained by appropriately combining technical means modified within the scope not departing from the gist of the present disclosure are also included in the technical scope of the present disclosure.

[0096] In addition, although the above-described embodiments have parts that are separately described for convenience of explanation, it goes without saying that they may be combined and executed within a technically possible range.

[0097] Also, the programs that operate in each device in the embodiment are programs that control a CPU or the like (programs that function a computer) so as to realize the functions of the above-described embodiments. And the information handled by these devices is temporarily stored in a temporary storage device (for example, RAM) during its processing, and then stored in a storage device such as various ROMs (Read Only Memory) or HDDs, and read by the CPU as necessary for correction and writing.

[0098] Here, the computer-readable non-transitory recording medium on which the program in the information processing apparatus is recorded may be any of a semiconductor medium (for example, ROM, non-volatile memory card, etc.), an optical recording medium, a magneto-optical recording medium (for example, DVD (Digital Versatile Disc), MO (Magneto Optical Disc), MD (Mini Disc), CD (Compact Disc), BD (Blu-ray (registered trademark) Disc, etc.)), a magnetic recording medium (for example, magnetic tape, flexible disk, etc.). In this case, the program recorded on the recording medium is read by the computer of the information processing apparatus and executed by the computer, whereby not only the functions of the above-described embodiments are realized, but also the functions of the present disclosure are realized by processing in cooperation with an operating system or other application programs based on the instructions of the program.

[0099] When distributing to the market, the program can be stored on a portable recording medium for distribution, or transferred to a server computer connected via a network such as the Internet. In this case, the storage device of the server computer is of course also included in the present disclosure.

[0100] In addition, each functional block or various features of the devices used in the above-described embodiments can also be implemented and executed by an electric circuit, for example, an integrated circuit or a plurality of integrated circuits. The electric circuit designed to realize the functions described in this specification may include a general-purpose use processor, a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field programmable gate array (FPGA), or other programmable logic devices, discrete gates or transistor logic, discrete hardware components, or a combination thereof. The general-purpose use processor may be a microprocessor, or may be a conventional type processor, controller, microcontroller, or state machine. The aforementioned electric circuit may be composed of a digital circuit or an analog circuit. Also, when an integrated circuit technology that replaces the current integrated circuit appears due to the progress of semiconductor technology, one or more aspects of the present disclosure can also use a new integrated circuit by such technology.

Description of Reference Numerals

[0101] 10 Information processing apparatus 11 Control unit 13 Operation input unit 15 Communication unit 17 Storage unit 171 Control program 173 Processing program 1731 Hit prediction program 1733 Information collection program 1735 Printed image analysis program 175 Submission processing program 177 History information storage area 179 User information storage area 30 Terminal device 31 Control unit 33 Display unit 35 Operation input unit 37 Communication unit 39 Memory unit 391 Control program 393 Submission processing program 395 Content storage area 50 Internet 100 Multifunction device 19 Image processing unit 191 Image forming unit 193 Image input unit

Claims

1. A posting unit that receives content submissions, and A processing unit that determines an evaluation value of the submitted content based on the collected data, The processing unit Generates feedback information according to the determined evaluation value, and outputs the generated feedback information together with the evaluation value to the submitter of the content. An information processing apparatus characterized by this.

2. The processing unit Generates information regarding at least one of the release time of the submitted content, an image based on the submitted content, and a print setting of the image as the feedback information. The information processing apparatus according to claim 1, characterized by this.

3. The processing unit Determines the evaluation value of the content based on the data regarding at least one of the characteristics of the submitted content, the usage history of past content, information on the Internet, and the achievements of the submitter. The information processing apparatus according to claim 2, characterized by this.

4. The information on the Internet Includes information regarding at least one of SNS posting information and search information on the Internet. The information processing apparatus according to claim 3, characterized by this.

5. The processing unit Determines the release time of the submitted content based on the frequency trend of keywords included in either one or both of the SNS posting information and the search information on the Internet, and the keywords included in the submitted content. The information processing apparatus according to claim 4, characterized by this.

6. The processing unit Determines a first evaluation value based on a comparison between a predetermined number of keywords with high frequency of occurrence among the keywords included in either one or both of the SNS posting information and the search information on the Internet, and the keywords included in the submitted content. The information processing apparatus according to claim 4, characterized by this.

7. The processing unit Identifies old content that is related to the registered content and was hit in the past from the usage history of past content, determines the similarity between the submitted content and the identified old content as a second evaluation value, and when the second evaluation value is lower than a first threshold value, generates the information related to the difference between the second evaluation value and the first threshold value as the feedback information. The information processing apparatus according to claim 2, characterized by this.

8. The processing unit The information processing apparatus according to claim 6, characterized in that it identifies a registrant, weights the achievements of the registrant and the first evaluation value, and determines a third evaluation value.

9. The processing unit identifies similar content similar to the registered content, and when the similarity between the posted content and the identified similar content is equal to or greater than a second threshold value, outputs information indicating that there is a high possibility that they are the same content. The information processing apparatus according to claim 3.

10. The evaluation value is a hit prediction value that represents the possibility of the posted content hitting, The processing unit outputs graph content representing the correlation between the feedback information and the hit prediction value. The information processing apparatus according to claim 1.

11. A posting unit that receives a content posting, a processing unit that determines an evaluation value of the posted content based on the collected data, and an image forming unit that forms an image of the content, The processing unit generates feedback information corresponding to the determined evaluation value, and outputs the generated feedback information together with the evaluation value to the content poster. An image forming apparatus characterized by the above.

12. Receives a content posting, A content evaluation method that determines an evaluation value of the posted content based on the collected data, characterized in that it generates feedback information corresponding to the determined evaluation value, and outputs the generated feedback information together with the evaluation value to the content poster. A content evaluation method characterized by the above.

Images