CN117633263A - Encoding method of digital asset based on big data - Google Patents
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Abstract
The application discloses a coding method of digital assets based on big data, which adopts a first code and a second code to characterize information carried by the digital assets in order to efficiently manage the digital assets and provide conditions for subsequent inquiry of the digital assets. On the one hand, coding of digital assets and querying based on the coded digital assets are achieved through data processing for management and supervision purposes. On the other hand, conditions are provided for further reducing the consumption of supervision and management resources.
Description
Technical Field
The present application relates to the field of data processing technology suitable for management, supervision or prediction purposes, and in particular to a method for encoding digital assets based on big data.
Background
With the development of information technology, digital assets carrying information have also exhibited a more dramatic increase. However, digital assets may contain multiple forms, such as literature, graphics, etc., which enrich the content and presentation of the digital asset on the one hand and increase the difficulty of utilizing the digital asset on the other hand. How to encode digital assets by technical means to facilitate subsequent searches is a challenge.
For example, publication (bulletin) number: CN112308551B, patent title: the digital asset information acquisition device and the digital asset information acquisition method (main classification number: G06Q 20/10) record digital asset information in the digital asset information source acquired by the information acquisition module as digital asset information of a user under the condition that the identity of the user and the authenticity of the used digital asset information source are determined. On the one hand, the data processing technology capable of explaining the purpose of supervision or prediction is quite available in the technical field related to digital asset processing; on the other hand, it can be stated that the technology mining in this field has a wide range of expansion prospects.
Disclosure of Invention
The embodiment of the application provides a digital asset coding method based on big data, so as to at least partially solve the technical problems.
The embodiment of the application adopts the following technical scheme:
in a first aspect, embodiments of the present application provide a method of encoding a digital asset based on big data, the method comprising:
carrying out semantic analysis on the digital asset to obtain a first code of the digital asset;
determining the definition of the semantics represented by the first encoded representation;
graphically encoding the digital asset to obtain a second encoding of the digital asset; the second code is for characterizing an amount of information provided by the digital asset when presented in a graphical state;
storing correspondence between the digital asset, the first encoding, the sharpness, and the second encoding;
when a digital asset query request is received, carrying out semantic analysis on the digital asset query request to obtain a semantic code;
if the number of dimensions contained in the semantic code exceeds a preset first number threshold, taking the digital assets corresponding to the specified number with the largest definition in the first code matched with the semantic code as first available digital assets;
ordering the first available digital assets from large to small in the amount of information represented by the second encoded representation to obtain displayable digital assets;
the exposable digital asset is presented.
In an alternative embodiment of the present specification, graphically encoding the digital asset to obtain a second encoding of the digital asset includes:
performing binarization processing on each pixel contained in the graphic file to which the digital asset belongs to obtain an available graphic file;
a second encoding of the digital asset is determined such that an amount of information corresponding to the second encoding is inversely related to a similarity between the available graphic file and a graphic file to which the digital asset belongs.
In an alternative embodiment of the present specification, the method further comprises:
and if the number of dimensions contained in the semantic code does not exceed the first number threshold, the first number of the information represented by the second code and the second number of the digital assets with the largest definition are used as the displayable digital assets in the first code matched with the semantic code.
In an alternative embodiment of the present specification, the method further comprises:
and if the amount of the information corresponding to any dimension of the semantic code is not greater than a preset information amount threshold, the first amount is greater than the second amount.
In an alternative embodiment of the present specification, the method further comprises:
if the amount of information of the semantic code corresponding to at least one dimension is greater than a preset information amount threshold, the first number is not greater than the second number.
In an alternative embodiment of the present specification, the method further comprises:
the specified number is inversely related to the number of dimensions contained in the semantic code.
In a second aspect, embodiments of the present application further provide an encoding apparatus for digital assets based on big data, the apparatus comprising:
a first code determination module configured to: carrying out semantic analysis on the digital asset to obtain a first code of the digital asset;
a sharpness determination module configured to: determining the definition of the semantics represented by the first encoded representation;
a second code determination module configured to: graphically encoding the digital asset to obtain a second encoding of the digital asset; the second code is for characterizing an amount of information provided by the digital asset when presented in a graphical state;
a storage module configured to: storing correspondence between the digital asset, the first encoding, the sharpness, and the second encoding;
a semantic code determination module configured to: when a digital asset query request is received, carrying out semantic analysis on the digital asset query request to obtain a semantic code;
a first available digital asset determination module configured to: if the number of dimensions contained in the semantic code exceeds a preset first number threshold, taking the digital assets corresponding to the specified number with the largest definition in the first code matched with the semantic code as first available digital assets;
a digital asset determination module may be presented configured to: ordering the first available digital assets from large to small in the amount of information represented by the second encoded representation to obtain displayable digital assets;
a display module configured to: the exposable digital asset is presented.
In a third aspect, embodiments of the present application further provide an electronic device, including:
a processor; and
a memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method steps of the first aspect.
In a fourth aspect, embodiments of the present application also provide a computer-readable storage medium storing one or more programs, which when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform the method steps of the first aspect.
The above-mentioned at least one technical scheme that this application embodiment adopted can reach following beneficial effect:
the digital assets can be characterized in the forms of characters, figures and the like, so that on one hand, the information content of the digital assets is enriched, and on the other hand, the test is put forward for the management mode of the digital assets. In order to efficiently manage the digital assets, the method in the specification adopts the first code and the second code to characterize the information carried by the digital assets, and provides conditions for subsequent inquiry of the digital assets. On the one hand, coding of digital assets and querying based on the coded digital assets are achieved through data processing for management and supervision purposes. On the other hand, conditions are provided for further reducing the consumption of supervision and management resources.
Drawings
The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiments of the application and together with the description serve to explain the application and do not constitute an undue limitation to the application. In the drawings:
FIG. 1 is a process schematic diagram of a method for encoding digital assets based on big data provided in an embodiment of the present disclosure;
fig. 2 is a schematic structural diagram of an electronic device according to an embodiment of the present disclosure.
Detailed Description
The invention will be described in further detail below with reference to the drawings by means of specific embodiments. Wherein like elements in different embodiments are numbered alike in association. In the following embodiments, numerous specific details are set forth in order to provide a better understanding of the present application. However, one skilled in the art will readily recognize that some of the features may be omitted, or replaced by other elements, materials, or methods in different situations. In some instances, some operations associated with the present application have not been shown or described in the specification to avoid obscuring the core portions of the present application, and may not be necessary for a person skilled in the art to describe in detail the relevant operations based on the description herein and the general knowledge of one skilled in the art.
Furthermore, the described features, operations, or characteristics of the description may be combined in any suitable manner in various embodiments. Also, various steps or acts in the method descriptions may be interchanged or modified in a manner apparent to those of ordinary skill in the art. Thus, the various orders in the description and drawings are for clarity of description of only certain embodiments, and are not meant to be required orders unless otherwise indicated.
The numbering of the components itself, e.g. "first", "second", etc., is used herein merely to distinguish between the described objects and does not have any sequential or technical meaning. The terms "coupled" and "connected," as used herein, are intended to encompass both direct and indirect coupling (coupling), unless otherwise indicated.
The following describes in detail the technical solutions provided by the embodiments of the present application with reference to the accompanying drawings.
As shown in fig. 1, the encoding method of the digital asset based on big data in the present specification comprises the following steps:
s100: and carrying out semantic analysis on the digital asset to obtain a first code of the digital asset.
The digital assets in this specification may be in the form of text, pictures, etc. The source of the digital asset is not particularly limited, and may be obtained by processing a web page by a crawler or the like, for example.
In the related art, the technical means capable of realizing semantic analysis of digital assets are applicable to the specification under the condition of permission. The objective of semantic parsing is to generalize the information conveyed by the digital asset, and the generalized result can be embodied in a keyword manner. Illustratively, if a digital asset is a character drawing, the resulting first encoding may be: "painting," "woman," "movie theatre," that is, the content of the painting is that the woman is in the theatre.
S102: determining the definition of the semantics represented by the first encoded representation.
Definition is the degree of specificity of the semantic meaning, and the higher the degree of specificity is, the lower the information of the characterization is, the higher the definition is. Continuing with the previous example, if the first encoding is: "drawing", "female singer opening three", "a certain way a certain cinema", the definition is higher. In the related art, the technical means capable of implementing definition determination are suitable for the specification, and in alternative embodiments, definition may be determined based on manual experience.
S104: and carrying out graphic encoding on the digital asset to obtain a second encoding of the digital asset.
The second code in this specification is used to characterize the amount of information that the digital asset provides when presented in a graphical state. For example, the painting is typically displayed in a graphical state, and the content of the painting may be displayed directly to the user, such as where the person wearing the green garment may be visually seen. For another example, an article is typically presented in the form of characters, rather than graphics, which are significant to a person or machine that can recognize the character, and if the character cannot be recognized as graphics, the information available is almost zero.
That is, the amount of information provided by the characters and graphics is different under certain conditions, and the technical solution in this specification is to use this difference to implement management of digital assets.
In an alternative embodiment of the present description, the process of determining the second code is: the pixels included in the graphic file to which the digital asset belongs are binarized (i.e., the colors represented by the pixels are replaced with 0 and 1. For a digital asset in character form, it is converted into a graphic) to obtain an available graphic file. A second encoding of the digital asset is determined such that an amount of information corresponding to the second encoding is inversely related to a similarity between the available graphic file and a graphic file to which the digital asset belongs. For example, the original color of the digital asset is lost after the binarization processing, the amount of carried information is reduced, the value of the second code is larger, and the digital asset is better displayed as a graph; for example, alphanumeric assets, which have little color certainty after binarization, carry little information, and the second code will have a smaller value, thereby distinguishing graphics from characters. However, in actual use, graphic and character doped digital assets are often present, which can also be quantified by the methods in this specification.
In the related art, the technical means for determining the similarity are applicable to the present specification, as conditions allow.
S106: storing a correspondence between the digital asset, the first encoding, the sharpness, and the second encoding.
S108: and when receiving the digital asset query request, carrying out semantic analysis on the digital asset query request to obtain semantic codes.
The technical means adopted by the semantic parsing in this step may be the same as the semantic parsing referred to in the previous step.
The digital asset query request may represent certain characteristics of the digital asset to be queried for.
S110: and if the number of the dimensions contained in the semantic code exceeds a preset first number threshold, taking the digital assets corresponding to the specified number with the maximum definition in the first code matched with the semantic code as first available digital assets.
A dimension may be an angle that is employed when characterizing something (e.g., a digital asset). For example, where a digital asset is a drawing, the angle at which it is characterized may be: the size of the drawing, the time of creation, the style of the drawing (character drawing, landscape drawing, etc.), the information contained in the drawing (e.g., female in the drawing, the scene is a movie theater).
The semantic code contains a large number of dimensions, which indicates that the inquirer knows what is wanted clearly and can describe the required digital assets more accurately. At this point, it should be dominated to match the user's needs as much as possible, rather than to provide more relevant digital assets to the user to increase interest. In an alternative embodiment of the present description, the specified number is inversely related to the number of dimensions comprised by the semantic code.
Wherein the first number threshold may be an empirical value.
In the related art, the technical means for determining the degree of matching is applicable to the present specification, as the conditions allow.
S112: the first available digital assets are ordered from large to small in the amount of information represented by the second encoded representation to obtain displayable digital assets.
The larger the information content of the second code representation, the more graphic content is indicated, the more the user is likely to acquire the information in an intuitive form, the more the user is facilitated to acquire the information, the more the digital resource is popular with the user, and the digital asset is preferentially displayed.
S114: the exposable digital asset is presented.
The digital assets can be characterized in the forms of characters, figures and the like, so that on one hand, the information content of the digital assets is enriched, and on the other hand, the test is put forward for the management mode of the digital assets. In order to efficiently manage the digital assets, the method in the specification adopts the first code and the second code to characterize the information carried by the digital assets, and provides conditions for subsequent inquiry of the digital assets. On the one hand, coding of digital assets and querying based on the coded digital assets are achieved through data processing for management and supervision purposes. On the other hand, conditions are provided for further reducing the consumption of supervision and management resources.
In an alternative example of the present specification, if the number of dimensions included in the semantic code does not exceed the first number threshold (indicating that the querier does not know what is specifically, then the first code that matches the semantic code, the second code, together, represents a first number of the largest amount of information (by graphically providing more information to the user in a faster way to guide the user to define his needs) and a second number of the largest amount of the digital assets (the higher the definition, the more the information conveyed by the querier is to be in favor of the user to define his needs) as the presentable digital asset.
In a further alternative embodiment, the first quantity is greater than the second quantity (increasing the duty cycle of the digital asset in graphical form to help the user to clarify its needs as soon as possible) if the amount of semantically encoded information corresponding to either dimension is not greater than a preset information amount threshold (the information amount threshold may be an empirical value indicating that the querier cannot express the digital asset.
Furthermore, if the amount of information of the semantic code corresponding to at least one dimension is greater than a preset information amount threshold (indicating that the user has an explicit goal), the first number is not greater than the second number to increase the duty cycle of the digital asset for which the information is explicit, so that the user finds the desired digital asset as soon as possible.
Further, the present specification also provides an encoding apparatus for digital assets based on big data, the apparatus comprising:
a first code determination module configured to: carrying out semantic analysis on the digital asset to obtain a first code of the digital asset;
a sharpness determination module configured to: determining the definition of the semantics represented by the first encoded representation;
a second code determination module configured to: graphically encoding the digital asset to obtain a second encoding of the digital asset; the second code is for characterizing an amount of information provided by the digital asset when presented in a graphical state;
a storage module configured to: storing correspondence between the digital asset, the first encoding, the sharpness, and the second encoding;
a semantic code determination module configured to: when a digital asset query request is received, carrying out semantic analysis on the digital asset query request to obtain a semantic code;
a first available digital asset determination module configured to: if the number of dimensions contained in the semantic code exceeds a preset first number threshold, taking the digital assets corresponding to the specified number with the largest definition in the first code matched with the semantic code as first available digital assets;
a digital asset determination module may be presented configured to: ordering the first available digital assets from large to small in the amount of information represented by the second encoded representation to obtain displayable digital assets;
a display module configured to: the exposable digital asset is presented.
The apparatus can perform the method in any of the foregoing embodiments, and can obtain the same or similar technical effects, which are not described herein.
Fig. 2 is a schematic structural diagram of an electronic device according to an embodiment of the present application. Referring to fig. 2, at the hardware level, the electronic device includes a processor, and optionally an internal bus, a network interface, and a memory. The Memory may include a Memory, such as a Random-Access Memory (RAM), and may further include a non-volatile Memory (non-volatile Memory), such as at least 1 disk Memory. Of course, the electronic device may also include hardware required for other services.
The processor, network interface, and memory may be interconnected by an internal bus, which may be an ISA (Industry Standard Architecture ) bus, a PCI (Peripheral Component Interconnect, peripheral component interconnect standard) bus, or EISA (Extended Industry Standard Architecture ) bus, among others. The buses may be classified as address buses, data buses, control buses, etc. For ease of illustration, only one bi-directional arrow is shown in FIG. 2, but not only one bus or type of bus.
And the memory is used for storing programs. In particular, the program may include program code including computer-operating instructions. The memory may include memory and non-volatile storage and provide instructions and data to the processor.
The processor reads the corresponding computer program from the nonvolatile memory into the memory and then runs the computer program to form a coding device of the digital asset based on big data on a logic level. And the processor is used for executing the programs stored in the memory and particularly used for executing any one of the encoding methods of the digital assets based on big data.
The encoding method of the digital asset based on big data disclosed in the embodiment shown in fig. 1 of the present application can be applied to a processor or implemented by the processor. The processor may be an integrated circuit chip having signal processing capabilities. In implementation, the steps of the above method may be performed by integrated logic circuits of hardware in a processor or by instructions in the form of software. The processor may be a general-purpose processor, including a central processing unit (Central Processing Unit, CPU), a network processor (Network Processor, NP), etc.; but also digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), field programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. The disclosed methods, steps, and logic blocks in the embodiments of the present application may be implemented or performed. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like. The steps of a method disclosed in connection with the embodiments of the present application may be embodied directly in hardware, in a decoded processor, or in a combination of hardware and software modules in a decoded processor. The software modules may be located in a random access memory, flash memory, read only memory, programmable read only memory, or electrically erasable programmable memory, registers, etc. as well known in the art. The storage medium is located in a memory, and the processor reads the information in the memory and, in combination with its hardware, performs the steps of the above method.
The electronic device may also execute a method for encoding a digital asset based on big data in fig. 1, and implement the functions of the embodiment shown in fig. 1, which is not described herein.
The present embodiments also provide a computer readable storage medium storing one or more programs, the one or more programs comprising instructions, which when executed by an electronic device comprising a plurality of application programs, perform any of the foregoing methods of encoding digital assets based on big data.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The present application is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the application. It will be understood that each flow and/or block of the flowchart illustrations and/or block diagrams, and combinations of flows and/or blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable memory that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer-readable memory produce an article of manufacture including instruction means which implement the function specified in the flowchart flow or flows and/or block diagram block or blocks.
These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
In one typical configuration, a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include volatile memory in a computer-readable medium, random Access Memory (RAM) and/or nonvolatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of computer-readable media.
Computer readable media, including both non-transitory and non-transitory, removable and non-removable media, may implement information storage by any method or technology. The information may be computer readable instructions, data structures, modules of a program, or other data. Examples of storage media for a computer include, but are not limited to, phase change memory (PRAM), static Random Access Memory (SRAM), dynamic Random Access Memory (DRAM), other types of Random Access Memory (RAM), read Only Memory (ROM), electrically Erasable Programmable Read Only Memory (EEPROM), flash memory or other memory technology, compact disc read only memory (CD-ROM), digital Versatile Discs (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices, or any other non-transmission medium, which can be used to store information that can be accessed by a computing device. Computer-readable media, as defined herein, does not include transitory computer-readable media (transmission media), such as modulated data signals and carrier waves.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises the element.
It will be appreciated by those skilled in the art that embodiments of the present application may be provided as a method, system, or computer program product. Accordingly, the present application may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, the present application may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and the like) having computer-usable program code embodied therein.
The foregoing is merely exemplary of the present application and is not intended to limit the present application. Various modifications and changes may be made to the present application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc. which are within the spirit and principles of the present application are intended to be included within the scope of the claims of the present application.
Claims (9)
1. A method of encoding a digital asset based on big data, the method comprising:
carrying out semantic analysis on the digital asset to obtain a first code of the digital asset;
determining the definition of the semantics represented by the first encoded representation;
graphically encoding the digital asset to obtain a second encoding of the digital asset; the second code is for characterizing an amount of information provided by the digital asset when presented in a graphical state;
storing correspondence between the digital asset, the first encoding, the sharpness, and the second encoding;
when a digital asset query request is received, carrying out semantic analysis on the digital asset query request to obtain a semantic code;
if the number of dimensions contained in the semantic code exceeds a preset first number threshold, taking the digital assets corresponding to the specified number with the largest definition in the first code matched with the semantic code as first available digital assets;
ordering the first available digital assets from large to small in the amount of information represented by the second encoded representation to obtain displayable digital assets;
the exposable digital asset is presented.
2. The method of claim 1, wherein graphically encoding the digital asset results in a second encoding of the digital asset, comprising:
performing binarization processing on each pixel contained in the graphic file to which the digital asset belongs to obtain an available graphic file;
a second encoding of the digital asset is determined such that an amount of information corresponding to the second encoding is inversely related to a similarity between the available graphic file and a graphic file to which the digital asset belongs.
3. The method of claim 1, wherein the method further comprises:
and if the number of dimensions contained in the semantic code does not exceed the first number threshold, the first number of the information represented by the second code and the second number of the digital assets with the largest definition are used as the displayable digital assets in the first code matched with the semantic code.
4. A method as claimed in claim 3, wherein the method further comprises:
and if the amount of the information corresponding to any dimension of the semantic code is not greater than a preset information amount threshold, the first amount is greater than the second amount.
5. A method as claimed in claim 3, wherein the method further comprises:
if the amount of information of the semantic code corresponding to at least one dimension is greater than a preset information amount threshold, the first number is not greater than the second number.
6. The method of claim 1, wherein the method further comprises:
the specified number is inversely related to the number of dimensions contained in the semantic code.
7. An apparatus for encoding a digital asset based on big data, the apparatus comprising:
a first code determination module configured to: carrying out semantic analysis on the digital asset to obtain a first code of the digital asset;
a sharpness determination module configured to: determining the definition of the semantics represented by the first encoded representation;
a second code determination module configured to: graphically encoding the digital asset to obtain a second encoding of the digital asset; the second code is for characterizing an amount of information provided by the digital asset when presented in a graphical state;
a storage module configured to: storing correspondence between the digital asset, the first encoding, the sharpness, and the second encoding;
a semantic code determination module configured to: when a digital asset query request is received, carrying out semantic analysis on the digital asset query request to obtain a semantic code;
a first available digital asset determination module configured to: if the number of dimensions contained in the semantic code exceeds a preset first number threshold, taking the digital assets corresponding to the specified number with the largest definition in the first code matched with the semantic code as first available digital assets;
a digital asset determination module may be presented configured to: ordering the first available digital assets from large to small in the amount of information represented by the second encoded representation to obtain displayable digital assets;
a display module configured to: the exposable digital asset is presented.
8. An electronic device, comprising:
a processor; and
a memory arranged to store computer executable instructions which, when executed, cause the processor to perform the method of any of claims 1 to 6.
9. A computer readable storage medium storing one or more programs, which when executed by an electronic device comprising a plurality of application programs, cause the electronic device to perform the method of any of claims 1-6.
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