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

Abstract

In an information processing device according to the present invention, a reception unit receives information designated by a user from a client terminal, a search unit searches for content stored in a database on the basis of the information received by the reception unit, and when there is content to which a tag is assigned in a search result of the search unit, an assignment unit assigns the tag of the content to content to which no tag is assigned.

Description

Information Processing Apparatus, Information Processing Method, and Information Processing Program

[0001] The present disclosure relates to an information processing apparatus, an information processing method, and an information processing program.

[0002] Japanese Patent Application Laid-Open No. 2016-62162 discloses a storage unit that records by associating accumulated image data accumulated in the past and accumulated tag data for displaying the accumulated image data, a feature generation unit that generates feature data indicating features of input image data, and a storage unit that extracts accumulated tag data associated with accumulated image data having the same or similar features as the feature data, and a tag generation unit that generates tag data for displaying the image data using this accumulated tag data. An automatic tag generation device is disclosed.

[0003] Japanese Patent No. 7004125 discloses a similar image search unit that searches a knowledge database for a drawing image similar to an input drawing image, an image correspondence detection unit that detects which of the object shown in the drawing image and / or the component constituting the object corresponds to the object and / or the component shown in the drawing image searched by the similar image search unit, and an attribute output unit that extracts attribute information corresponding to the corresponding points detected by the image correspondence detection unit from the knowledge database and outputs it as the attribute information of the drawing image. An image analysis apparatus to which a drawing image corresponding to the drawing data is input is disclosed.

[0004] Japanese Patent Application Laid-Open No. 2022-180959 discloses a first assignment unit that assigns an attribute label to a similar image similar to an object image including an object for which an attribute label indicating an attribute related to the object imaged in the object image is assigned, and a generation unit that generates a labeling rule for assigning an attribute label to an unknown object image by image-analyzing the similar image to which the attribute label has been assigned by the first assignment unit. An information processing apparatus is disclosed.

[0005] Japanese Patent Publication No. 2016-162423 discloses an object recognition device comprising: an acquisition means for acquiring a target image to be recognized; a search means for searching for similar images similar to the target image from an image database that stores multiple image data associated with tag information; and a recognition means for recognizing objects included in the target image based on tag information associated with the similar images obtained by the search means.

[0006] In services that store and share content, if attribute information is not assigned to each piece of content, it becomes difficult to easily search for that content. Therefore, it is necessary to assign attribute information to each piece of content, but this process requires a significant amount of effort.

[0007] Therefore, this disclosure aims to provide an information processing device, an information processing method, and an information processing program that can eliminate the effort required to assign attribute information to content stored in a service for storing and sharing content.

[0008] To achieve the above objective, the information processing device according to the first aspect of this disclosure includes a processor, which processes, if any content with attribute information is present in the search results obtained by searching for content using specified information from among the content stored in a service that stores and shares content, to add such attribute information to at least some of the content included in the search results that does not have attribute information.

[0009] The information processing apparatus according to the second aspect of this disclosure, in the information processing apparatus according to the first aspect, has a processor that uses AI to perform processing to apply to at least some of the content.

[0010] An information processing device according to a third aspect of this disclosure, in an information processing device according to a first aspect, includes a processor that receives reactions to content included in search results, and if attribute information is attached to the content that has received a reaction, attaches said attribute information to at least some of the content included in the search results that does not have attribute information attached.

[0011] The information processing device according to the fourth aspect of this disclosure, in the information processing device according to the third aspect, includes a processor that groups the content that has received a reaction, and if there is content in the grouped content to which attribute information has been assigned, it assigns said attribute information to the content in the group that does not have attribute information assigned.

[0012] The information processing device according to the fifth aspect of this disclosure, in the information processing device according to the first aspect, includes a processor that acquires a predetermined amount of search results corresponding to a predetermined period or a predetermined number of times, and uses the attribute information of content to which attribute information has been assigned among the content included in the predetermined amount of search results as candidates for attribute information to be assigned to content to which attribute information has not been assigned among the content included in the predetermined amount of search results, and assigns the attribute information of the candidate to the content to which attribute information has not been assigned if the candidate satisfies predetermined conditions.

[0013] The information processing device according to the sixth aspect of this disclosure, in the information processing device according to the fifth aspect, has a processor that, as a predetermined condition, assigns attribute information of content that has attribute information to it to content that does not have attribute information to it, when the value representing the accuracy of a candidate is equal to or greater than a predetermined threshold.

[0014] The information processing device according to the seventh aspect of this disclosure is an information processing device according to the sixth aspect, in which the threshold value is a value determined according to the number of attribute information of the content stored in the service.

[0015] The information processing device according to the eighth aspect of this disclosure, in the information processing device according to the sixth aspect, corrects a value representing the accuracy of a candidate for content if there is content for which a reaction has been received among a predetermined amount of search results.

[0016] An information processing device according to the ninth aspect of this disclosure, in an information processing device according to the first aspect, wherein the content is an image of at least one of a still image and a video, and the processor searches for the content by similarity search, which searches for similar images using a specified image.

[0017] The information processing apparatus according to the tenth aspect of this disclosure, in the information processing apparatus according to the ninth aspect, provides that when the processor provides attribute information to content, it also provides said attribute information to a specified image.

[0018] The information processing device according to the eleventh aspect of this disclosure, in the information processing device according to the first aspect, adds attribute information to content that does not have attribute information by copying, reusing, sharing, or creating new attribute information from content that does have attribute information.

[0019] The information processing method according to the twelfth aspect of this disclosure involves a computer performing a process to add attribute information to at least some of the content included in the search results that does not have attribute information, if such content is included in the search results that are obtained by searching for content using specified information from among the content stored in a service that stores and shares content.

[0020] The information processing program according to the 13th aspect of this disclosure causes a computer to perform a process in which, if there is content to which attribute information is attached among the content included in the search results obtained by searching for content using specified information from among the content stored in a service that stores and shares content, said attribute information is attached to at least some of the content included in the search results that does not have attribute information attached.

[0021] According to this disclosure, it is possible to provide an information processing device, an information processing method, and an information processing program that can eliminate the effort required to assign attribute information to content stored in a service for storing and sharing content.

[0022] This figure shows an example of the schematic configuration of the information processing system according to this embodiment. This block diagram shows the main electrical components of the client terminal and cloud server of the information processing system according to this embodiment. This is a functional block diagram showing the functional configuration of the cloud server in the information processing system according to this embodiment. This figure is for explaining the specific processing performed by the cloud server of the information processing system according to this embodiment. This flowchart shows an example of the processing flow performed by the cloud server of the information processing system according to this embodiment. This flowchart shows a modified example of the processing flow performed by the cloud server of the information processing system according to this embodiment. This figure is for explaining an example of assigning tags after accumulating a certain amount of search history. This figure shows an example of the number of tags for each subcategory tag. This figure is for explaining an example of correcting the number of occurrences (points) according to the user's reaction. This figure shows a general-purpose personal computer.

[0023] Hereinafter, an example of an embodiment of the present invention will be described in detail with reference to the drawings. Note that this embodiment is not limiting to the present invention. Figure 1 is a diagram showing a schematic configuration example of an information processing system according to this embodiment.

[0024] As shown in Figure 1, the information processing system 10 according to this embodiment includes a client terminal 12 and a cloud server 14. The client terminal 12 and the cloud server 14 are each connected to a communication line 16 and are able to communicate with each other via the communication line 16.

[0025] Examples of communication lines 16 include the Internet, LAN (Local Area Network), and WAN (Wide Area Network). Note that in Figure 1,

[0026] The following example shows a configuration with multiple client terminals 12 (two in Figure 1), but the client terminal 12

[0027] There may be one or three or more. Furthermore, the client terminal 12 may be a personal computer, a tablet, and / or a mobile device such as a smartphone.

[0028] In this embodiment, the information processing system 10 provides a service, as an example of a service for storing and sharing content, where the cloud server 14 provides a service for managing corporate assets such as images, videos, drawings, and / or documents online. The cloud service provided by the cloud server 14 may include cloud services such as Amazon® Web Services, Microsoft® Azure, and Google® Cloud.

[0029] Figure 2 is a block diagram showing the main electrical components of the client terminal 12 and cloud server 14 of the information processing system 10 according to this embodiment. Since the client terminal 12 and cloud server 14 have a typical computer configuration, the cloud server 14 will be described as a representative example below.

[0030] The cloud server 14 includes a CPU (Central Processing Unit) 14A as an example of a processor, a ROM (Read Only Memory) 14B, a RAM (Random Access Memory) 14C, storage 14D, an operation unit 14E, a display unit 14F, and a communication interface unit 14G. The CPU 14A controls the overall operation of the cloud server 14. The ROM 14B stores various control programs and parameters in advance. The RAM 14C is used as a work area when various programs are executed by the CPU 14A. The storage 14D stores various data and application programs. The operation unit 14E is used to input various information. The display unit 14F is used to display various information. The communication interface unit 14G can connect to external devices and transmits and receives various data with external devices. The above parts of the client terminal 12 are electrically interconnected by a system bus 14H. In this embodiment, the cloud server 14 uses storage 14D as the storage unit, but it is not limited to this, and other non-volatile storage units such as hard disks and / or flash memory may be used.

[0031] With the above configuration, the cloud server 14 according to this embodiment uses the CPU 14A to access the ROM 14B, RAM 14C, and storage 14D, acquire various data via the operation unit 14E, and display various information on the display unit 14F. The cloud server 14 also uses the CPU 14A to control the transmission and reception of various data via the communication interface unit 14G. In this embodiment, a database (DB) 26 (see Figure 3) for storing content such as images, videos, drawings, and / or documents is constructed in the storage 14D.

[0032] By the way, the information processing system 10 according to this embodiment provides a service for storing and sharing content, which makes it possible to store, centralize, and / or share various types of content. However, if each stored content is not tagged, it is not easy to search for the content. Therefore, it is necessary to tag each piece of content, but tagging requires a great deal of effort. Furthermore, tags must be assigned in a way that avoids inconsistency.

[0033] Therefore, in this embodiment, if the cloud server 14 searches for content using specified information from among the content stored in a service that stores and shares content, and if there is content with tags among the content included in the search results, it performs a process to add the tags to at least some of the content included in the search results that does not have tags.

[0034] Specifically, the CPU 14A of the cloud server 14 loads an information processing program pre-stored in ROM 14B into RAM 14C and executes it, thereby realizing the functions shown in Figure 3. Figure 3 is a functional block diagram showing the functional configuration of the cloud server 14 in the information processing system 10 according to this embodiment.

[0035] As shown in Figure 3, the cloud server 14 in the information processing system 10 according to this embodiment has the functions of a reception unit 20, a search unit 22, and an assignment unit 24.

[0036] The reception unit 20 receives information specified by the user from the client terminal 12. For example, the reception unit 20 may receive text such as search words and / or keywords to search for content stored in the database 26 built on the storage 14D, or it may receive source images for similar image searches as specified information. Images used for similar image searches can be at least one of still images and videos.

[0037] The search unit 22 searches the database 26 for content based on the information received by the reception unit 20. For example, if the search unit 22 receives text such as search words and / or keywords, it searches the database 26 for content related to the text received by the reception unit 20. Also, if the reception unit 20 receives a source image for searching for similar images, the search unit 22 searches the database 26 for images similar to the source image received by the reception unit 20.

[0038] The tagging unit 24, if it finds content with tags in the search results of the search unit 22, assigns the tags of that content to content that does not have tags. Tags are attribute information such as information for searching for content and / or information related to the content. Tags are assigned to content that does not have tags by duplicating, reusing, sharing, or creating new tags from content that does have tags.

[0039] Figure 4 is a diagram illustrating the specific processing performed by the cloud server 14 of the information processing system 10 according to this embodiment. Figure 4 illustrates the case when the reception unit 20 receives a source image for searching for similar images.

[0040] When a searcher inputs a source image to search for similar images by operating the client terminal 12, the reception unit 20 of the cloud server 14 receives the source image.

[0041] When the reception unit 20 receives the search source image, the search unit 22 searches for an image similar to the search source image from the contents stored in the database 26.

[0042] Here, the assignment unit 24 determines whether there is an image with a tag among the search result images. When there is an image with a tag, the assignment unit 24 assigns the tag of the image with the tag to the images without the tag included in the search results. For example, in the search result image of FIG. 4, three images are searched as search results, and among them, one image has a tag. Therefore, an example is shown in which the tag is assigned to the two images without the tag and the search source image. This makes it possible to automatically assign tags to content without tags every time a search is performed.

[0043] Next, a specific process performed by the information processing system according to the present embodiment configured as described above will be described. FIG. 5 is a flowchart showing an example of the flow of processing performed by the cloud server 14 of the information processing system 10 according to the present embodiment. The processing in FIG. 5 starts, for example, when the cloud server 14 receives specified information such as a search source image in order to search for the content stored in the database 26 from the client terminal 12.

[0044] In step 100, the CPU 14A receives the information specified from the client terminal 12 and proceeds to step 102. That is, the reception unit 20 receives, as specified information, a search word for searching the content stored in the database 26 and / or a search source image for searching for similar images.

[0045] In step 102, the CPU 14A performs a search based on the specified information and proceeds to step 104. That is, the search unit 22 searches for the content stored in the database 26 based on the information received by the reception unit 20. For example, when the reception unit 20 receives a search source image for searching for similar images, the search unit 22 searches for an image similar to the search source image received by the reception unit 20 from the content stored in the database 26.

[0046] In step 104, the CPU 14A determines whether there is any content with a tag among the search results. That is, the attaching unit 24 determines whether there is any content with a tag attached to the search results of the search unit 22. If the determination in step 104 is affirmative, the process proceeds to step 106. If the determination in step 104 is negative, the series of processes ends.

[0047] In step 106, the CPU 14A determines whether there is any content without a tag. If the determination in step 106 is affirmative, the process proceeds to step 108. If the determination in step 106 is negative, the series of processes ends.

[0048] In step 108, the CPU 14A attaches the tag of the content with a tag in the search results to the content without a tag and ends the series of processes. As a result, tags are automatically attached to the content without tags, so the labor of attaching tags to the content can be saved.

[0049] By having the cloud server 14 perform the process in this way, tags can be automatically attached to the content without tags in the search results, and the man-hours for tagging can be reduced.

[0050] Also, since tags are attached to the related content of the search results, the dispersion of tags can be suppressed.

[0051] (Modification) Next, the information processing system 10 according to the modification will be described. Note that the modification is different in the process performed by the cloud server 14, and the configuration itself is the same as that of the above embodiment. Therefore, the detailed description will be omitted below, and only the differences will be described with the same reference numerals.

[0052] In the modified version, the reception unit 20 further receives reactions to the content stored in the database 26 and stores the content in the database 26 in a way that indicates that a reaction has been received. Examples of reactions include liking the content, selecting the content, applying to use the content, downloading the content, and / or viewing the content.

[0053] Furthermore, the search unit 22 searches the content stored in the database 26 based on the information received by the reception unit 20, similar to the embodiment described above.

[0054] The tagging unit 24 then groups the content that has received a reaction to the search results from the search unit 22, and if there is content with a tag attached within the grouped content, it attaches that tag to the content within the group that does not have a tag attached. This makes it possible to attach more appropriate tags to the content than in the above embodiment.

[0055] Furthermore, if tags are assigned to content that has received reactions without being grouped, those tags may also be assigned to other content in the search results that does not have tags.

[0056] Next, a modified example of the processing performed by the cloud server 14 will be described. Figure 6 is a flowchart showing a modified example of the processing flow performed by the cloud server 14 of the information processing system 10 according to this embodiment. Processes common to Figure 5 will be denoted by the same reference numerals and described accordingly.

[0057] In step 100, the CPU 14A receives the information specified by the client terminal 12 and proceeds to step 102. Specifically, the receiving unit 20 receives the search words for searching the content stored in the database 26, and / or the source images for similar image searches, as the specified information.

[0058] In step 102, the CPU 14A performs a search based on the specified information and proceeds to step 103. That is, the search unit 22 searches the content stored in the database 26 based on the information received by the reception unit 20. For example, if the reception unit 20 receives a source image for searching for similar images, the search unit 22 searches the content stored in the database 26 for images similar to the source image received by the reception unit 20.

[0059] In step 103, the CPU 14A determines whether or not there is any content in the search results that has received a reaction. In step 103, the reception unit 20 receives reactions to content stored in the database 26 so that it is possible to determine whether or not a reaction has been received, and the CPU 14A determines whether or not there is any content in the search results that has received a reaction. If the determination in step 103 is negative, the process proceeds to step 104; if the determination in step 103 is positive, the process proceeds to step 110.

[0060] In step 104, the CPU 14A determines whether or not there is tagged content in the search results. That is, the tagging unit 24 determines whether or not there is tagged content in the search results of the search unit 22. If the determination in step 104 is affirmative, the process proceeds to step 106; if the determination in step 104 is negative, the series of processes ends.

[0061] In step 106, the CPU 14A determines whether or not there is content that has not been tagged. If the determination in step 106 is positive, the process proceeds to step 108; if the determination in step 106 is negative, the series of processes ends.

[0062] In step 108, CPU 14A assigns tags from tagged content in the search results to content that does not have tags, thus ending the series of processes. This automatically assigns tags to content that does not have tags, saving the effort of manually assigning tags to content.

[0063] Meanwhile, in step 110, the CPU 14A groups the reacted content and proceeds to step 112.

[0064] In step 112, the CPU 14A determines whether there is any tagged content within the grouped group. If the determination in step 112 is positive, the process proceeds to step 114; if the determination in step 112 is negative, the series of processes ends.

[0065] In step 114, the CPU 14A determines whether or not there is any content in the grouped group that does not have a tag. If the determination in step 114 is positive, the process proceeds to step 116; if the determination in step 114 is negative, the series of processes ends.

[0066] In step 116, the CPU 14A assigns the tags of the tagged content within the group to the content within the group that does not have tags, and then completes the series of processes.

[0067] In this way, by having the cloud server 14 perform the processing, the amount of work required for tagging can be reduced and variations in tags can be suppressed, similar to the embodiment described above.

[0068] Furthermore, in the modified version, in addition to system-based similarity judgment, the system also takes into account the subjective input of users by grouping content with reactions, thereby improving the accuracy of grouping during tagging.

[0069] In the above embodiments and modifications, the decision of whether or not to tag the content may be left to AI (Artificial Intelligence). Alternatively, the decision of whether or not to tag may be left to the AI ​​using a threshold and / or count. For example, a trained AI, which has been trained by the generating AI to learn about past search results and whether or not tags should have been added at that time, may make the decision of whether or not to tag.

[0070] Furthermore, while the above embodiments and modifications describe an example in which tags are added to content that does not have tags as attribute information each time a search is performed, the timing of tagging is not limited to this. For example, tags may be added after accumulating a certain amount of search history by obtaining a predetermined amount of search results corresponding to a predetermined period or a predetermined number of times. Here, with reference to Figure 7, a specific example of adding tags after accumulating a certain amount of search history will be explained. Figure 7 is a diagram illustrating an example of adding tags after accumulating a certain amount of search history. As a premise, the tags in this case are assumed to be two types: major category (target image saved) and subcategory (target image not held). Also, the number in parentheses next to "candidate" represents points (here, the number of occurrences as an example) as an example of a value representing the probability of the "candidate".

[0071] Specifically, as shown in Figure 7, tags corresponding to "candidates (examples)" are registered according to the user's search results. Then, if a candidate meets a predetermined condition (in this case, the number of occurrences is equal to or greater than a predetermined threshold (for example, 2)), that "candidate" is registered as a tag.

[0072] In Figure 7, assume that when person A performs a search, the results include images tagged with the major category "Food" but without a subcategory, and images tagged with the major category "Food" but with the subcategory "Chocolate". In this case, the tag candidate to be assigned to the content without a tag is registered as candidate 1, which is chocolate (1).

[0073] Next, let's assume that when person B performs a search, they find images tagged with the major category "food" but without a subcategory, and images tagged with the major category "food" but with the subcategory "cake". In this case, the candidate tags to be assigned to the content without tags would be registered as candidate 1: chocolate (1) and candidate 2: cake (1).

[0074] Next, let's assume that Person A or another person performs a search and finds images tagged with the major category "food" but without a subcategory, and images tagged with the major category "food" but with the subcategory "chocolate". Here, since the number of occurrences of "chocolate" is 2 or more, candidate 1, "chocolate" (2), is registered as the subcategory for the content that does not have a subcategory tag.

[0075] In the example in Figure 7, an example was shown where the threshold for occurrence was set as a constant, "2," but the threshold is not limited to a constant. If there is a bias in the tags within database 26, it is not advisable to set the threshold as a constant, so the threshold may be a variable. For example, the threshold may be a value determined according to the number of tags in the content stored in database 26. Specifically, by sloping the threshold, such as to half the number of existing tags, the influence of the bias in tags within database 26 can be reduced. In the example in Figure 8, the number of tags for chocolate is 100, so the threshold for chocolate is 50; the number of tags for cake is 50, so the threshold for cake is 25; the number of tags for ice cream is 120, so the threshold for ice cream is 60; and the number of tags for snacks is 200, so the threshold for snacks is 100. Figure 8 is a diagram showing an example of the number of tags for each subcategory.

[0076] Furthermore, in the example shown in Figure 7, the number of occurrences, which are points for "candidates," are registered for each search. However, user reactions such as "likes" may contain more important information than simply "finding a hit in a search." Therefore, if content that has received a reaction exists within a predetermined amount of search results, the value representing the likelihood of that content being a candidate may be adjusted. In other words, the number of occurrences corresponding to the value representing the likelihood of a "candidate" may be adjusted according to the user's reaction. For example, by sloping the way in which the number of occurrences, which are points, are assigned, tags with higher likelihood can be added. Here, we will explain a specific example of adjusting the number of occurrences (points) according to the user's reaction. Figure 9 is a diagram illustrating an example of adjusting the number of occurrences (points) according to the user's reaction.

[0077] Specifically, as shown in Figure 9, one point is awarded for each instance of appearance in the search results. In the example in Figure 9, four content items are shown as search results. One of the four search results is content with a tag that has the major category "food" but no subcategories. Another search result is content with a tag that has the major category "food" and the subcategories "chocolate". Yet another search result is content with a tag that has the major category "food" and the subcategories "snacks". Yet another search result is content with a tag that has the major category "food" and the subcategories "snacks". For content without subcategories, the candidate tags are chocolate (1), snacks (1), and cake (1).

[0078] Here, we show an example where, after viewing the details screen of content without a subcategory tag (referred to as the target image in Figure 9) and other images (content with the subcategory attribute "cake" in Figure 9), the points for candidate 3 are corrected and 10 points are added.

[0079] Furthermore, if there are "likes" on content that does not have a subcategory tag (referred to as the target image in Figure 9) and other images (content with the subcategory attribute "Snacks" in Figure 9), an example is shown where the points for Candidate 2 are adjusted and 30 points are added.

[0080] Thus, if content that has received reactions exists in the search results, adjusting the number of tags associated with that content allows for the assignment of tags with a higher degree of accuracy.

[0081] In the embodiments and modifications described above, examples of adding tags to content that does not have tags have been explained. However, the target of tagging may be at least some of the content that does not have tags. That is, tags may be added to all content that does not have tags, or to some of the content. When adding tags to some content, for example, tags may be added to a predetermined number of top-ranking content in the search results that does not have tags.

[0082] Furthermore, although the above embodiment was described as an information processing system 10 including a client terminal 12 and a cloud server 14, as shown in Figure 10, a single device such as a general-purpose personal computer 50 equipped with a display unit 50H and an operation unit 50S such as a keyboard and / or mouse may be used as the information processing system. When a personal computer 50 is used, by providing the cloud server 14 functionality to an application that manages content such as files, it becomes possible to automatically assign tags to the content.

[0083] Furthermore, the various processes that the CPU executes by running software (programs) in the above embodiment may be executed by a computer equipped with various processors other than the CPU. In this case, the processor may be an FPGA (field-programmable gate array), etc.

[0084] Examples include dedicated electrical circuits, which are processors with circuit configurations specifically designed to perform particular processing, such as PLDs (Programmable Logic Devices) whose circuit configurations can be changed after manufacturing, and ASICs (Application Specific Integrated Circuits). Furthermore, the above various processing may be performed by one of these various processors, or by a combination of two or more processors of the same or different types (for example, multiple FPGAs, and a combination of a CPU and an FPGA). More specifically, the hardware structure of these various processors is an electrical circuit that combines circuit elements such as semiconductor elements.

[0085] Furthermore, although the above embodiment describes a configuration in which various programs are pre-stored (installed) in ROM 20B, the invention is not limited to this configuration. The various programs may be provided in the form of recordings on recording media such as CD-ROM (Compact Disk Read Only Memory), DVD-ROM (Digital Versatile Disk Read Only Memory), and USB (Universal Serial Bus) memory. Alternatively, the various programs may be provided in the form of downloads from external information processing devices, etc., via a network.

[0086] Furthermore, the program described herein can be provided as a program product. A program product includes any form of product for providing the program. For example, a program product includes a program provided via a network such as the Internet, and non-temporary computer-readable recording media such as CD-ROMs and DVDs on which the program is stored.

[0087] Furthermore, the configuration and operation of the information processing system 10 described in the above embodiments are merely examples and can be modified as needed without departing from the spirit of this disclosure.

[0088] The following further notes are disclosed regarding the above embodiments. (Note 1) An information processing device comprising a processor, wherein the processor performs the process of adding attribute information to at least some of the content included in the search results that does not have attribute information, when there is content to which attribute information has been added among the content included in the search results that is searched using specified information from among the content stored in a service that stores and shares content.

[0089] (Note 2) The information processing apparatus described in Note 1, wherein the processor performs processing to be applied to at least some of the content using AI.

[0090] (Note 3) The information processing apparatus according to Note 1, wherein the processor receives a reaction to the content included in the search results, and if attribute information is attached to the content to which the reaction was received, attaches said attribute information to at least some of the content included in the search results that does not have attribute information attached.

[0091] (Note 4) The information processing device according to Note 3, wherein the processor groups the content that has received the reaction, and if there is content in the grouped content to which attribute information has been assigned, it assigns said attribute information to the content in the group that does not have attribute information assigned.

[0092] (Note 5) The information processing device according to any one of Notes 1 to 4, wherein the processor acquires a predetermined amount of the search results corresponding to a predetermined period or a predetermined number of times, and uses the attribute information of content to which attribute information has been assigned among the content included in the predetermined amount of the search results as a candidate for attribute information to be assigned to content included in the predetermined amount of the search results that does not have attribute information, and if the candidate satisfies predetermined conditions, assigns the attribute information of the candidate to the content that does not have attribute information.

[0093] (Note 6) The information processing apparatus according to Note 5, wherein the processor, as a predetermined condition, adds attribute information of content to which attribute information has been added among the content included in the search results, to content to which attribute information has not been added, when the value representing the accuracy of the candidate is equal to or greater than a predetermined threshold.

[0094] (Note 7) The information processing device described in Note 6, wherein the threshold value is determined according to the number of attribute information items of the content stored in the service.

[0095] (Note 8) The information processing device according to Note 6, wherein the processor corrects a value representing the accuracy of the candidate for the content if there is content for which a reaction has been received among the predetermined amount of search results.

[0096] (Note 9) An information processing device according to any one of Notes 1 to 8, wherein the content is an image of at least one of a still image and a video, and the processor searches for the content by similarity search, which searches for similar images using a specified image.

[0097] (Note 10) The information processing apparatus according to Note 9, wherein when the processor assigns attribute information to content, the specified image also assigns the attribute information.

[0098] (Note 11) An information processing device as described in any one of Notes 1 to 10, which adds attribute information to content that does not have attribute information by copying, reusing, sharing, or creating new attribute information from content that does have attribute information.

[0099] (Note 12) An information processing method in which, when a computer searches for content using specified information from among the content stored in a service for storing and sharing content, and there is content with attribute information attached to it among the content included in the search results, the computer performs the process of attaching said attribute information to at least some of the content included in the search results that does not have attribute information attached.

[0100] (Note 13) An information processing program for causing a computer to perform the process of adding attribute information to at least some of the content included in the search results that does not have attribute information, when such content is included in the search results that are obtained by searching for content using specified information from among the content stored in a service that stores and shares content.

Claims

1. An information processing device comprising a processor, wherein the processor, when content with attribute information is present among the content included in the search results obtained by searching for content using specified information from among the content stored in a service for storing and sharing content, adds said attribute information to at least some of the content included in the search results that does not have attribute information.

2. The information processing apparatus according to claim 1, wherein the processor performs processing to be applied to at least some of the content using AI.

3. The information processing apparatus according to claim 1, wherein the processor receives a reaction to the content included in the search results, and if attribute information is assigned to the content to which the reaction was received, the processor assigns the attribute information to at least some of the content included in the search results that does not have attribute information assigned to it.

4. The information processing apparatus according to claim 3, wherein the processor groups the content that has received the reaction, and if there is content in the grouped content to which attribute information has been assigned, the attribute information is assigned to the content in the group that does not have attribute information assigned.

5. The information processing apparatus according to claim 1, wherein the processor obtains a predetermined amount of the search results corresponding to a predetermined period or a predetermined number of times, the attribute information of content to which attribute information has been assigned among the content included in the predetermined amount of the search results is used as a candidate for attribute information to be assigned to content included in the predetermined amount of the search results that does not have attribute information, and if the candidate satisfies predetermined conditions, the attribute information of the candidate is assigned to the content that does not have attribute information.

6. The information processing apparatus according to claim 5, wherein the processor, as a predetermined condition, assigns attribute information of content to which attribute information has been assigned among the content included in the search results, to content to which attribute information has not been assigned, when the value representing the accuracy of the candidate is equal to or greater than a predetermined threshold.

7. The information processing apparatus according to claim 6, wherein the threshold is a value determined according to the number of attribute information of the content stored in the service.

8. The information processing apparatus according to claim 6, wherein the processor corrects a value representing the accuracy of the candidate for the content if there is content for which a reaction has been received among the predetermined amount of search results.

9. The information processing apparatus according to claim 1, wherein the content is at least one of still images and video images, and the processor searches for the content by similarity search using a specified image.

10. The information processing apparatus according to claim 9, wherein when the processor assigns attribute information to content, the processor also assigns the attribute information to the specified image.

11. The information processing apparatus according to claim 1, wherein attribute information is added to content that does not have attribute information by copying, reusing, sharing, or creating new attribute information from content that does have attribute information.

12. An information processing method that includes, when content stored in a service for storing and sharing content is searched using specified information, and some of the content included in the search results has attribute information attached to it, attaching said attribute information to at least some of the content included in the search results that does not have attribute information attached.

13. An information processing program for a computer that, when content is found in a search result obtained by searching for content using specified information from content stored in a service for storing and sharing content, includes content to which attribute information has been assigned, and the program performs a process that includes assigning said attribute information to at least some of the content included in the search result that does not have attribute information assigned.

Images