WO2019088867A1

WO2019088867A1 - Automatic importing of metadata of files between user accounts and data storage

Info

Publication number: WO2019088867A1
Application number: PCT/RU2017/000822
Authority: WO
Inventors: Максим Александрович АЗАРОВ
Original assignee: Общество С Ограниченной Ответственностью "Асд Технолоджиз"
Priority date: 2017-11-03
Filing date: 2017-11-03
Publication date: 2019-05-09

Abstract

The claimed solution relates to the field of processing and managing digital information, specifically data in social networks disseminated by users. The technical solution makes it possible to implement a mechanism of automatic context description for information stored in a personal data storage, which corresponds to information published in social networks or transmitted using messengers, making it possible to create a simple and convenient search index for information in a personal storage. A preferred embodiment of implementation of the claimed solution discloses a method of automatically importing the metadata of files between user accounts and personal data storage, comprising the following steps: detecting at least one first file in at least one information transmission channel associated with a user account; determining the metadata associated with said first file; searching in a personal data storage for a second file similar to said first file; and, when said second file is identified, importing the metadata which corresponds to said first file into the metadata of the second file.

Description

AUTOMATIC IMPORTATION OF METADATA FILES BETWEEN USER ACCOUNTS AND DATA STORAGE

TECHNICAL FIELD

[1] The claimed solution relates to the processing and management of digital information, in particular data on social networks, distributed by users.

BACKGROUND

[2] Today, with a wide development of social networks and ensuring the implementation of various information exchange functions, such as images, photos, music files, video clips, GIF-animations, etc., each network provides a set of its own protocols for exchanging information and essence its architectural placement. There are social networks of personal contacts, for example, Facebook, Vkontakte, Odnoklassniki. There are specialized social networks for the exchange of a certain type of data, for example, Instagram. Also, there are applications of instant messengers that implement the functions of exchanging a set of data types, for example, WhatsApp, Telegram.

[3] All the mentioned solutions implement a variety of information exchange channels and each of the channels allows for one or another approach to personalize the content laid out by users, by annotating it.

[4] While the main array of information is distributed through social networks and instant messengers, users have personal data storage facilities, for example, cloud storages (Google Drive, DropBox, Microsoft OneDrive, etc.). As a rule, such storage principles are implemented in order to provide private access to users' personal files, which in turn leads to the complexity of personalizing files and the need for manual annotation of the data array.

[5] In this part of the social network, they implement various approaches to search for the required information, for example, photos using hashtags (tags) or semantic search tools based on the information laid out in the social network.

[6] In this part, personal data stores are deprived of such a function and, as a rule, only the built-in manual annotation mechanisms are implemented. information, without the ability to quickly search for the required data, in particular photographs or video clips on their context (annotated) description.

SUMMARY OF INVENTION

[7] To solve the existing shortcomings, it is proposed to implement a mechanism for automated annotation of information stored in personal repositories of users, using information in social networks or instant messengers with their context description.

[8] The technical solution allows you to implement an automatic context description mechanism for information stored in personal data stores, which corresponds to information published in social networks or transmitted via instant messengers, which will allow you to create a simple and convenient search index for information in your personal storage.

[9] A preferred embodiment of the claimed solution discloses a method for automatically importing file metadata between user accounts and personal data storage, comprising the steps of:

- determine at least one first file in at least one channel of information transmission associated with the user account;

- determine the metadata associated with said first file;

- search in the personal data store of the second file, similar to the first file mentioned; and

- when identifying the said second file, the metadata corresponding to the first file is imported into the metadata of the second file.

[10] In the private embodiment of the claimed method, the files are graphic images and / or video files.

[1 1] In another particular embodiment of the claimed method, the metadata is selected from the group: annotation and / or comments and / or tags and / or location.

[12] In another particular embodiment of the claimed method, the data transmission channels are selected from the group: social network, instant messenger, or combinations thereof.

[13] In another particular embodiment of the claimed method, the personal file storage is fixed or cloud data storage.

[14] In another particular embodiment of the claimed method, when searching for a second file, the degree of similarity with the first file is estimated. [15] In another particular embodiment of the claimed method, at least one of the following parameters is determined when analyzing the degree of similarity: the first file is part of the second file, the first file is a compressed version of the second file, the first file is a scaled version of the second file, the first file is visual processing the second file.

[16] In another particular embodiment of the claimed method, visual processing of a file is a color correction and / or filter overlay and / or special effects overlay.

[17] In another particular embodiment of the claimed method, when importing a text description into the personal storage, files are analyzed in the storage having a similar description.

[18] In another particular embodiment of the claimed method, files with a similar description are combined into a group.

[19] In another particular embodiment of the claimed method, the step of determining the first type of files is carried out when new files are detected in the information transmission channel associated with the user account.

[20] In another preferred embodiment of the claimed solution, a device is proposed for automatically importing file metadata between user accounts and personal data storage, containing

- at least one processor;

- at least one memory device that contains machine-readable instructions that, when executed by the processor, induce the latter

- determine at least one first file in at least one information channel associated with a user account;

- determine the metadata associated with said first file;

- when identifying the said second file, import the metadata corresponding to the first file mentioned into the metadata of the second file.

[21] In the private implementation of the device is a smartphone, tablet, game console, personal computer or laptop.

[22] In another private implementation, personal storage is stored in the device’s memory or is a cloud storage on the Internet.

[23] In another private implementation, the connection to the cloud storage is through wired or wireless communication. [24] In another preferred embodiment, the claimed solution is a system for automatically importing file metadata between user accounts and a personal data repository, containing

- computing module designed for data processing;

- memory module;

- module for detecting metadata of the first file in the user information channel;

- personal data storage containing user files;

- a module for comparing the first file and the second file, which is contained in said personal data storage;

- module for importing the metadata of the first file into the metadata of the second file in the user data store when similar files are detected.

[25] In a particular embodiment of the system, the comparison module performs analysis of the similarity of the second file in the user's storage with the first file in the information transmission channel.

[26] In a particular embodiment of the system, the degree of similarity is determined by at least one of the following parameters: the first file is part of the second file, the first file is a compressed version of the second file, the first file is a scaled version of the second file, the first file is a visual processing of the second file.

[27] In the private embodiment of the system, the files are graphic images and / or video files.

[28] In a particular embodiment of the system, the metadata is selected from the group: annotation and / or comments and / or tags and / or location.

[29] In the private embodiment of the system, personal data storage is a local storage in a memory module and / or is a cloud storage on the Internet.

[30] In the private embodiment of the system, the comparison module analyzes similar files in the local and cloud storage of user data simultaneously. DESCRIPTION OF THE DRAWINGS

[31] FIG. 1 illustrates the sequence of steps of the claimed method.

[32] FIG. 2 illustrates a general view of the system implementing the method.

[33] FIG. 3 illustrates an example of information in the social network for its search in the personal data repository. [34] FIG. 4 illustrates an example of matching images in a personal information store with the import of a narrative.

[35] FIG. 5 illustrates a general scheme of a device suitable for performing the claimed method. IMPLEMENTATION OF THE INVENTION

[36] The main advantage of the claimed solution is the implementation of the function of attaching user-related accounts to this personal information store in third-party data exchange channels, in particular, social networks and instant messengers, thus forming a unified, connected data exchange system.

[37] Accounts can be paired with a personal data repository using an API that will exchange information flows to locate, process and compare data in the user's connected channels to search for relevant data and organize the import of metadata.

[38] As shown in FIG. 1, the claimed method of importing metadata (100) is to implement successive steps. At step (101), at least one data exchange channel, for example, Facebook, detects a post (post) containing an image file or a video file. Next, an analysis is performed on the availability of metadata for this file (102), which contain contextual information. If data is detected, then (103) the algorithm for searching for a similar second file in the personal data store of the user is activated. When a similar second file is found in the storage (104), metadata (105) presented in the first file data exchange channel is imported into the personal information storage structure (index) for the purpose of generating a search index, in particular, into the metadata of the said second file.

[39] To implement step (103), various image analysis algorithms and / or sequences of video frames can be used to search for and detect similar data.

[40] To implement the system of interaction of elements of the system, ensuring the implementation of the claimed solution in FIG. 2 presents its main elements.

[41] In general, the system includes a user device (200) that generates data in communication channels. The user device (200) is connected by means of an information network with one or more channels. data exchange (300), for example, social network, as well as personal data storage (400).

[42] The user's device (200) may be a computer, laptop, tablet, smartphone, game console, television, etc.

[43] As a data exchange channel (300), as mentioned above, a social network, application messengers, specialized data exchange applications (Instagram), etc. can be used.

[44] The data storage (400) can be a cloud storage of information, for example, Google Drive, OneDrive, etc. In a particular implementation example, it is also possible that the storage is a local storage device, for example, an HDD or SSD and is connected via a data network to a user device (200).

[45] Also, the storage (400) may be a memory module embedded in the device (200), which provides permanent storage of data with which information obtained from said communication channels will be compared.

[46] The principle of communication between elements of the system may be different. In particular, wired communication between a user device (200) and a data storage (400) can be used, for example, LAN, Ethernet, USB, RJ45, etc. Wireless network access can be used, for example, via the Internet, Wi-Fi, WAN, GSM (2G / 3G / LTE / 5G), Bluetooth, etc.

[47] Access to communication channels (300) requires a network connection via the Internet, access to which can be organized in various ways.

[48] FIG. 3 shows an example of analyzing information in a social network (300), in particular a user record containing a graphic image (301) with corresponding metadata (302) of a descriptive nature.

[49] In this solution, the term metadata can use a wide range of information, for example: contextual description, tags, comments, annotation, location data, data showing the number of posts on other accounts of a user record (repost), statistical data showing the score of the record by others users (like) or combinations thereof.

[50] The information placed on the data exchange channel (301) may be of a different nature, for example, an image, a video file, a GIF animation, etc.

[51] FIG. 4 shows an example of analyzing a file (301) from a social network (300) with data stored in a user's personal storage (400). [52] Analysis of similar files in storage (400) can be performed using the algorithm for comparing the similarity of graphic images. The image (301) from the social network (300) is compared with the image (401) in the repository (400). If a similar file (image) is detected, the metadata (302) is imported from the social network channel (300) into the metadata (402) corresponding to the file (401). Based on the generated metadata (402), a search index is generated for search purposes or structured storage of files in the repository (400).

[53] Based on the obtained index, the data (files) can be divided into categories if there is similar information in the file metadata that can form a group.

[54] When analyzing graphic data in the repository (400), it is also taken into account that the information placed on the social network channel (300) may differ from its form in the repository (400). For example, data can be processed using graphic filters, additional effects, cropped, using color correction, etc. Thus, it checks that the first file is part of the second file, the first file is a compressed version of the second file, the first file is a scaled version of the second file, the first file is a visual processing of the second file, and so on.

[55] If the file (301) is a video, then when searching for a similar file (401) in the repository (400), it may be taken into account that the file (301) is part of the file (401), or a compressed / processed version of the file (401). Also, it can be verified that the file (301) has been processed in terms of adding effects to it.

[56] FIG. 4 shows an example when the file (301) from the social network channel (300) is part of the file (401) stored in the storage (400). In this case, when detecting a similar part of the file (403) in the repository (400), the algorithm establishes the compliance of the identified information and generates the metadata (402) by importing the metadata (302).

[57] As mentioned above, various types of metadata can be imported for the corresponding files in the storage (400). In particular, comments and chat correspondence from social networks and instant messengers can also be imported.

[58] In order to build an accurate search index, storage files (400) with generated metadata can be divided into relevant categories with the assignment of a weighting factor to each category. In particular, descriptive metadata will have more weight than comments or hashtags. For files received from instant messengers, information placed directly after placing the file from which descriptive information was imported into the storage metadata (400) will have more weight than messages preceding this file.

[59] To identify files in storage (400) with imported meta information, various display styles can be used, for example, the imposition of the most relevant metadata on image files or group storage icons, etc.

[60] FIG. 5 shows a general view of the device (200) implementing the claimed solution. Device (200) contains one or more processors (201), RAM (202), common data storage (203), information input / output interfaces (204), I / O data (205) integrated by the common system bus (210) and one or more networking tools (206).

[61] As mentioned above, the device (200) can be a computer, tablet, laptop, etc.

[62] The processor (201) is a main computing module and implements the implementation of a software algorithm that is executed based on machine-readable instructions stored in RAM (202).

[63] The RAM (202) can be any suitable type of random access memory, depending on the implementation of the device (200), for example, DIMM, SIMM, DDR, etc.

[64] Various ROMs can be used as storage media (203), in particular: flash memory (NAND, EEPROM, SD, etc.), HDD, SSD, or combinations thereof.

[65] I / O Interfaces (204) can be USB, USB-C, PS / 2, Lightning, FireWire, RJ45, RS232, COM, or combinations thereof, depending on the device implementation (200).

[66] I / O tools (205) can represent: a display, a touch display, a vibration motor, a buzzer, a light pen, a keyboard, a mouse, a joystick, a touchpad, speakers, a projector, a pico projector, etc.

[67] The network interaction tool (206) is selected from a number of means, providing the transmission and reception of information between several devices integrated into a single network, for example, Ethernet card, Wi-Fi module, Bluetooth module, NFC module, IrDa, GSM modem, and t .P.

[68] With the help of the device (200), the execution of software modules that implement the functions of analyzing information exchange channels (300) to identify first file type and search for relevant data in the information storage (400) of the user.

[69] The presented materials, disclosing the essence of the declared solution, describe the preferred implementation options and should not be used as limiting other, private implementation options of the stated solution that are within the scope of the requested legal protection and are obvious to specialists in this field of technology.

Claims

CLAIM

1. A method of automatically importing file metadata between user accounts and a personal data repository, comprising the steps of:

- determine the metadata associated with said first file;

- search in the personal data store of the second file, similar to the first file mentioned;

2. The method according to claim 1, characterized in that the files are graphic images and / or video files.

3. The method according to claim 1, characterized in that the metadata is selected from the group: annotation and / or comments and / or tags and / or location.

4. The method according to claim 1, characterized in that the data transmission channels are selected from the group: social network, instant messenger or a combination of both.

5. The method according to claim 1, characterized in that the personal file storage is a fixed or cloud data storage.

6. The method according to claim 1, characterized in that when searching for the second file, the degree of similarity with the first file is estimated.

7. The method according to claim 6, characterized in that the analysis of the degree of similarity determines at least one of the following parameters: the first file is part of the second file, the first file is a compressed version of the second file, the first file is a scaled version of the second file, the first file is a visual processing of the second file.

8. The method according to claim 7, characterized in that the visual processing of the file is a color correction and / or filter overlay and / or special effects overlay.

9. The method according to claim 1, characterized in that when importing a text description into the personal storage, the files are analyzed in the storage having a similar description.

10. The method according to claim 9, characterized in that the files with a similar description are combined into a group.

1 1. The method according to claim 1, characterized in that the step of determining the first type of files is carried out when new files are detected in the information transmission channel associated with the user account.

12. Device for automatic import of file metadata between user accounts and personal data storage, containing

- at least one processor;

at least one memory means which contains machine-readable instructions that, when executed by the processor, induce the latter

- determine the metadata associated with said first file;

13. The device according to item 12, characterized by the fact that it is a smartphone, tablet, game console, phablet, personal computer or laptop.

14. The device according to item 12, characterized in that the personal storage is contained in the device's memory or is a cloud storage on the Internet.

15. The device according to 14, characterized in that the connection with the cloud storage is carried out using wired or wireless communication.

16. System for automatic import of file metadata between user accounts and personal data storage, containing - computing module designed for data processing;

- memory module;

- module for detecting metadata of the first file in the user information channel; - personal data storage containing user files;

17. The system of clause 16, characterized in that the comparison module performs an analysis of the similarity of the second file in the user's store with the first file in the information transmission channel.

18. The system of claim 17, characterized in that the degree of similarity is determined by at least one of the following parameters: the first file is part of the second file, the first file is a compressed version of the second file, the first file is a scaled version of the second file, the first file is visual processing the second file.

19. The system of claim 16, characterized in that the files are graphic images and / or video files.

20. The system of claim 16, characterized in that the metadata is selected from the group: annotation and / or comments and / or tags and / or location.

21. The system of claim 16, characterized in that the personal data storage is a local storage in the memory module and / or is a cloud storage on the Internet.

22. The system according to claim 21, characterized in that the comparison module performs the analysis of similar files simultaneously in the local and cloud storage of user data.