CN110851797A - Block chain-based work creation method and device and electronic equipment - Google Patents
Block chain-based work creation method and device and electronic equipment Download PDFInfo
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Abstract
The specification provides a work creation method based on a blockchain. The method comprises the following steps: acquiring the work attribute of a work to be created input by a user; retrieving material information related to the product attribute, and performing intelligent analysis processing on the material information to generate creation auxiliary information; outputting an auxiliary creation prompt to the user based on the creation auxiliary information, and collecting key information of the user in the process of creating the content of the work; wherein the key information comprises information for determining that the user is an originator of the content of the work; and issuing the key information and the obtained work content to a block chain for evidence storage.
Description
Technical Field
One or more embodiments of the present disclosure relate to the field of blockchain technologies, and in particular, to a method and an apparatus for creating a work based on a blockchain, and an electronic device.
Background
The block chain technology, also called distributed ledger technology, is an emerging technology in which several computing devices participate in "accounting" together, and a complete distributed database is maintained together. The blockchain technology has been widely used in many fields due to its characteristics of decentralization, transparency, participation of each computing device in database records, and rapid data synchronization between computing devices.
Disclosure of Invention
According to a first aspect of the present specification, there is provided a method of blockchain-based composition creation, the method comprising:
acquiring the work attribute of a work to be created input by a user;
retrieving material information related to the product attribute, and performing intelligent analysis processing on the material information to generate creation auxiliary information;
outputting an auxiliary creation prompt to the user based on the creation auxiliary information, and acquiring the content of the work created by the user based on the auxiliary creation prompt;
collecting key information of a user in the process of creating the content of the work; wherein the key information comprises information for determining that the user is an originator of the content of the work;
and issuing the key information and the obtained work content to a block chain for evidence storage.
Optionally, the key information includes one or more of the following combinations:
the creation time of the work content, the identity information of the user, the creation operation type of the work content and the creation position corresponding to the creation operation of the work content.
Optionally, the work to be created is an original text; the material information is text material information; the intelligent analysis processing includes NLP natural language processing.
Optionally, the authoring auxiliary information includes:
performing NLP natural language processing on the text material information to obtain a knowledge index related to the work attribute; and/or the presence of a gas in the gas,
and performing NLP natural language processing on the text material information to obtain a typesetting structure related to the product attribute.
Optionally, before issuing the obtained work content to the blockchain for evidence storage, the method further includes:
inputting the obtained work content into a title generation model to perform title generation calculation, and generating a title for the work content; the title generation model is a machine learning model trained by using a plurality of work contents and titles as training samples.
According to a second aspect of the present specification, there is provided an apparatus for blockchain-based composition creation, the apparatus comprising:
the attribute acquisition unit is used for acquiring the product attribute of the to-be-created product input by the user;
the material retrieval unit is used for retrieving material information related to the product attribute and intelligently analyzing and processing the material information to generate creation auxiliary information;
a work acquisition unit which outputs an auxiliary creation prompt to the user based on the creation auxiliary information and acquires the content of a work created by the user based on the auxiliary creation prompt;
the information acquisition unit is used for acquiring key information of a user in the process of creating the content of the work; wherein the key information comprises information for determining that the user is an originator of the content of the work;
and the work evidence storing unit is used for releasing the key information and the obtained work content to a block chain for evidence storage.
Optionally, the key information includes one or more of the following combinations:
the creation time of the work content, the identity information of the user, the creation operation type of the work content and the creation position corresponding to the creation operation of the work content.
Optionally, the work to be created is an original text; the material information is text material information; the intelligent analysis processing includes NLP natural language processing.
Optionally, the authoring auxiliary information includes:
performing NLP natural language processing on the text material information to obtain a knowledge index related to the work attribute; and/or the presence of a gas in the gas,
and performing NLP natural language processing on the text material information to obtain a typesetting structure related to the product attribute.
Optionally, before the work evidence storing unit, the apparatus further includes:
the title generation unit is used for inputting the obtained work content into a title generation model to perform title generation calculation and generate a title for the work content; the title generation model is a machine learning model trained by using a plurality of work contents and titles as training samples.
According to a third aspect of the present specification, there is provided an electronic apparatus comprising:
a processor;
a memory for storing processor-executable instructions;
and the processor executes the executable instructions to realize the work creation method based on the block chain.
By combining the blockchain technology with the artificial intelligence technology, the embodiment of the specification can provide related creation auxiliary information which accords with the desired created works of the user for the user in the creation process by utilizing the intelligent analysis technology so as to improve the creation efficiency; and the block chain non-tampering characteristic can be utilized to release the created work content and the key information in the process of creating the work content in the block chain for evidence preservation, so that the certified work content and the key information are used as original evidence when the infringement of the work is found.
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FIG. 1 is a schematic diagram of a process for creating an intelligent contract, as shown in an exemplary embodiment of the present description;
FIG. 2 is a schematic diagram of a call to an intelligent contract, shown in an exemplary embodiment of the present description;
FIG. 3 is a schematic diagram illustrating the creation of an intelligent contract and invocation of an intelligent contract in accordance with an exemplary embodiment of the present specification;
FIG. 4 is a flow diagram illustrating a method of blockchain-based composition creation in accordance with an exemplary embodiment of the present specification;
FIG. 5 is a diagram illustrating a hardware configuration of an electronic device in accordance with an exemplary embodiment of the present disclosure;
FIG. 6 is a block diagram of a blockchain-based work composition apparatus, as shown in an exemplary embodiment of the present specification.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with one or more embodiments of the present specification. Rather, they are merely examples of apparatus and methods consistent with certain aspects of one or more embodiments of the specification, as detailed in the claims which follow.
It should be noted that: in other embodiments, the steps of the corresponding methods are not necessarily performed in the order shown and described herein. In some other embodiments, the method may include more or fewer steps than those described herein. Moreover, a single step described in this specification may be broken down into multiple steps for description in other embodiments; multiple steps described in this specification may be combined into a single step in other embodiments.
The specification aims to provide a work creation scheme based on a block chain. The content creation platform can retrieve material information related to the product attribute based on the product attribute of the to-be-created product input by a user, and intelligently analyze and process the material information to generate creation auxiliary information; then outputting an auxiliary creation prompt to the user based on the creation auxiliary information, and acquiring the content of the work created by the user based on the auxiliary creation prompt; and finally, issuing the acquired work content and key information in the process of creating the work content to a block chain for evidence storage.
Therefore, the block chain technology is combined with the artificial intelligence technology, and the intelligent analysis technology can be utilized to provide related creation auxiliary information which accords with the desired created work for the user in the creation process so as to improve the creation efficiency; and the block chain non-tampering characteristic can be utilized to release the created work content and the key information in the process of creating the work content in the block chain for evidence preservation, so that the certified work content and the key information are used as original evidence when the infringement of the work is found.
Before describing the method for creating a work based on a blockchain provided by the present specification, the blockchain technique is briefly described.
Blockchains are generally divided into three types: public chain (Public Blockchain), private chain (PrivateBlockchain) and alliance chain (Consortium Blockchain). Furthermore, there may be a combination of the above types, such as private chain + federation chain, federation chain + public chain, and so on.
In practical applications, whether public, private, or alliance, it is possible to provide the functionality of a smart contract (Smartcontract). An intelligent contract on a blockchain is a contract on a blockchain that can be executed triggered by a transaction. An intelligent contract may be defined in the form of code.
Taking an Etherhouse as an example, a user is supported to create and call some complex logic in the Etherhouse network. The ethernet workshop is used as a programmable block chain, and the core of the ethernet workshop is an ethernet workshop virtual machine (EVM), and each ethernet workshop node can run the EVM. The EVM is a well-behaved virtual machine through which various complex logic can be implemented. The user issuing and invoking smart contracts in the etherhouse is running on the EVM. In fact, the EVM directly runs virtual machine code (virtual machine bytecode, hereinafter referred to as "bytecode"), so the intelligent contract deployed on the blockchain may be bytecode. As shown in FIG. 3, after Bob sends a Transaction (Transaction) containing information to create a smart contract to the Ethernet shop network, each node may execute the Transaction in the EVM. In fig. 1, the From field of the transaction is used To record the address of the account initiating the creation of the intelligent contract, the contract code stored in the field value of the Data field of the transaction may be byte code, and the field value of the To field of the transaction is a null account. After the nodes reach the agreement through the consensus mechanism, the intelligent contract is successfully created, and the follow-up user can call the intelligent contract.
After the intelligent contract is established, a contract account corresponding to the intelligent contract appears on the block chain, and the block chain has a specific address; for example, "0 x68e12cf284 …" in each node in fig. 1 represents the address of the contract account created; the contract Code (Code) and account store (Storage) will be maintained in the account store for that contract account. The behavior of the intelligent contract is controlled by the contract code, while the account storage of the intelligent contract preserves the state of the contract. In other words, the intelligent contract causes a virtual account to be generated on the blockchain that contains the contract code and account storage.
As mentioned above, the Data field containing the transaction that created the intelligent contract may hold the byte code of the intelligent contract. A bytecode consists of a series of bytes, each of which can identify an operation. Based on the multiple considerations of development efficiency, readability and the like, a developer can select a high-level language to write intelligent contract codes instead of directly writing byte codes. For example, the high-level language may employ a language such as Solidity, Serpent, LLL, and the like. For intelligent contract code written in a high-level language, the intelligent contract code can be compiled by a compiler to generate byte codes which can be deployed on a blockchain.
Taking the Solidity language as an example, the contract code written by it is very similar to a Class (Class) in the object-oriented programming language, and various members including state variables, functions, function modifiers, events, etc. can be declared in one contract. A state variable is a value permanently stored in an account Storage (Storage) field of an intelligent contract to save the state of the contract.
As shown in FIG. 2, still taking the Etherhouse as an example, after Bob sends a transaction containing the information of the calling intelligent contract to the Etherhouse network, each node can execute the transaction in the EVM. In fig. 2, the From field of the transaction is used To record the address of the account initiating the intelligent contract invocation, the To field is used To record the address of the intelligent contract invocation, and the Data field of the transaction is used To record the method and parameters of the intelligent contract invocation. After invoking the smart contract, the account status of the contract account may change. Subsequently, a client may view the account status of the contract account through the accessed block link point (e.g., node 1 in fig. 2).
The intelligent contract can be independently executed at each node in the blockchain network in a specified mode, and all execution records and data are stored on the blockchain, so that after the transaction is executed, transaction certificates which cannot be tampered and lost are stored on the blockchain.
A schematic diagram of creating an intelligent contract and invoking the intelligent contract is shown in fig. 3. An intelligent contract is created in an Ethernet workshop and needs to be subjected to the processes of compiling the intelligent contract, changing the intelligent contract into byte codes, deploying the intelligent contract to a block chain and the like. The intelligent contract is called in the Ethernet workshop, a transaction pointing to the intelligent contract address is initiated, the EVM of each node can respectively execute the transaction, and the intelligent contract code is distributed and operated in the virtual machine of each node in the Ethernet workshop network.
The block chain technology is combined with the artificial intelligence technology, so that the artificial intelligence technology can be utilized to provide related creation auxiliary information which accords with the work to be created for the user in the creation process so as to improve the creation efficiency; and the created work content can be released in the blockchain for evidence preservation by utilizing the characteristic that the blockchain cannot be tampered, so that the verified work content can be used as the original evidence when the infringement is met.
After the above blockchain technique is introduced, a method for creating a work based on blockchain provided in the following description is introduced.
Referring to fig. 4, fig. 4 is a flowchart illustrating a method for creating a work based on a blockchain according to an exemplary embodiment. The method can be applied to a content creation platform, and specifically comprises the following steps:
step 402: and acquiring the work attribute of the work to be created input by the user.
A content authoring platform may refer to a platform for a user to author content of a work. When a user creates a work, the user can input the attributes of the work to be created in the client of the content creation platform.
The product attributes may include a user-determined type of the product to be created, a distribution channel, content keywords, and the like. The product attributes are merely exemplary and are not specifically limited. In practical application, the attributes of the works can be flexibly configured.
And the type of the work is used for indicating the expression form of the work to be created. The following exemplifies several common work types, such as novel, prose, news, current comments, entertainment. The type of work is only exemplified here, and is not particularly limited.
The publishing channel is used for indicating a propagation path after the creation of the work is completed, namely, the platform to which the work needs to be published. With the continuous launch of mobile applications, information dissemination is increasing. Besides traditional newspaper periodicals and broadcast televisions, the system can also comprise a publishing channel based on internet application, such as a microblog, a WeChat friend circle, a public number, a self-media platform and the like. Here, the distribution channel is only exemplified and not particularly limited.
The content key words are used for indicating the main content of the works to be created. The following exemplifies several common content keywords such as people, places, times, etc. Here, the content keyword is merely exemplified and not particularly limited.
Step 404: and retrieving material information related to the product attribute, and performing intelligent analysis processing on the material information to generate creation auxiliary information.
After receiving the work attribute input by the user, the content creation platform can search based on the work attribute, so as to obtain the material information related to the work attribute.
For example, if the work to be authored is an image, filters commonly used for the type of the image may be automatically retrieved. For example, searching cutout and beauty filters for human images, searching filters with brightness and color adjustment functions for landscape images, and the like.
As another example, if the work to be authored is text, textual content associated with the text type may be automatically retrieved. Such as recent hot events, historical allusions, vocabularies, idioms, etc. The material is described here by way of example only and is not intended to be limited in any way.
When implemented, the content authoring platform can retrieve in a pre-set data source. The data source may be a predetermined network. And the content creation platform searches in the preset network after taking the product attribute as a search keyword.
In addition, the content creation platform may periodically crawl web page information from the preset network by using a web crawler technology, and store the web page information in a database. In this way, the content authoring platform may also retrieve material information associated with the product attributes from this database.
Although material information related to the attributes of the work can be obtained through the search, the material information may not be directly used by the user, and most of the material information may be useless information which does not help the user to create. For this reason, the content creation platform also needs to perform intelligent analysis processing on the material information to generate useful information that can be referred to by the user when creating the work. These useful information are called authoring assistance information.
In an exemplary embodiment, the work to be authored is original text; the material information is text material information; the intelligent analysis processing comprises NLP (Natural Language processing) natural Language processing; the authoring assistance information includes:
performing NLP natural language processing on the text material information to obtain a knowledge index related to the work attribute; and/or the presence of a gas in the gas,
and performing NLP natural language processing on the text material information to obtain a typesetting structure related to the product attribute.
Wherein, useful material information related to the works to be created is provided for users by constructing a knowledge index. The typesetting structure can be a content structure of the work.
When the method is realized, the contents of the works with high popularity or click rate are marked; and recommending the typesetting structure adopted by the works with high similarity to the user according to the similarity between the content of the marked works and the attributes of the works to be created. By adopting a good typesetting structure, the quality of the work can be improved, and readers have better experience.
Step 406: and outputting an auxiliary creation prompt to the user based on the creation auxiliary information, and acquiring the content of the work created by the user based on the auxiliary creation prompt.
The content authoring platform may recommend the authoring assistance information to the user after determining it. Because the creation auxiliary information is related to the to-be-created work of the user, the user can create with reference to the creation auxiliary prompt in the creation process, and therefore creation efficiency is improved.
The content creation platform can acquire the content of the work created by the user when receiving the uplink certificate storing instruction triggered by the user.
Step 408: collecting key information of a user in the process of creating the content of the work; wherein the key information includes information for determining that the user is an originator of the content of the work.
Wherein the key information comprises one or more of the following:
the creation time of the work content, the identity information of the user, the creation operation type of the work content and the creation position corresponding to the creation operation of the work content. Here, the key information is merely exemplified and not particularly limited.
Wherein, the creation time of the work content refers to: the time at which the content of the work is created, modified or deleted.
The identity information of the user is as follows: identity information of a user creating the content of the work, such as an account number of the user on the content creation platform, an identification number of the user, a name of the user, physiological information of the user (such as a fingerprint of the user, iris information, etc.), which is only exemplary and not particularly limited.
The creation operation types of the work content may include: the addition operation to the work content, the deletion operation to the work content, the modification operation to the work content, and the like are only exemplary illustrations of the creation operation type, and are not particularly limited thereto.
The creation position of the work content refers to: the location of the created work content in the entire work. For example, assuming that the work content is image content, the position of the created image content in the entire image work is created.
The above-described work content and key information are explained in detail below by a specific example.
For example, suppose user 1 adds a sentence "month is hometown Ming" to the end of the first section on page 3 of work 1 authored by user 1 on the content authoring platform at 00: 3, month 3, 16, 12 in 2019.
The content of the user-created work acquired by the content creation platform is 'moon is hometown ming'. The creation time of the content of the work collected by the content creation platform is 3 and 16 in 2019 and 12 in 12 hours and 00 minutes.
The identity information of the user collected by the content creation platform comprises: user 1's account number on the content authoring platform, user 1's name, user 1's identification number, and so on.
The creation operation type of the user collected by the content creation platform is an adding operation.
The creation positions of the work content collected by the content creation platform are as follows: page 3, first end of segment of work 1.
In brief, the content of the work and the key information for creating the content of the work can reflect the creation process of the content of the work by the user and reflect that the user is the originator of the content of the work, thereby providing strong evidence for the certainty of the work to which the subsequent content of the work belongs.
Step 410: and issuing the key information and the obtained work content to a block chain for evidence storage.
And (4) issuing the created work content in the blockchain for evidence storage by utilizing the characteristic that the blockchain cannot be tampered. When the infringement of the works is met, the release time and the content of the works of the user can be traced through the block chain, and whether the infringement exists can be judged after the infringement is compared with the infringement works, so that the rights and interests of the original works are guaranteed. In addition, since key information in the process of creating the work by the user is also linked up at the same time, the originality of the work is more favorably proved by the key information. For example, the originators of the works can be defined through the identity information in the key information; the creation time of the work may specify the time of completion of the work, etc.
When implemented in an embodiment of the present specification, the retrieval process of step 404 described above may be performed on a blockchain. The content authoring platform may be a node device of a blockchain. And intelligent contracts for retrieval are deployed on the blockchain.
The client side of the blockchain can issue a command for retrieving the attribute of the work, and the content creation platform responds to the command for retrieving the attribute of the work issued by the client side, calls a retrieval logic in the intelligent contract deployed on the blockchain and retrieves material information related to the attribute of the work; and intelligently analyzing and processing the material information to generate the creation auxiliary information.
When the retrieval process is executed on the blockchain, the blockchain has the property of being not tampered, which is equivalent to chain-crediting the retrieval process of the work. The retrieval process is in concert with the creation process, and the creation materials, the typesetting structure and the like adopted in the creation process can be inquired in the retrieval process, so that the authenticity of the creation process is further enhanced.
The above instruction may be a transaction issued by the client to the blockchain, and the instruction is only exemplary and is not specifically limited.
Generally, works need to have a title. The title is a brief sentence that identifies the content of the work. Good titles may increase the number of clicks on the work. The present specification also provides a function of automatically generating a title from the content of a work.
Specifically, the content creation platform may parse the content of the work based on semantic analysis and generate a title corresponding to the content of the work.
This mode is described below by steps a1 through a 2.
Step A1: the content creation platform can adopt a preset word segmentation technology to perform word segmentation processing on the content of the work to obtain a plurality of words.
The preset word segmentation technology may include: a word segmentation method based on dictionary and word bank matching, a word segmentation method based on word frequency statistics, a word segmentation method based on rules and the like.
The word segmentation method based on dictionary and word bank matching comprises the following steps: the method comprises the steps of segmenting a text into a plurality of character strings according to a preset strategy, matching each character string with a dictionary or a word bank, and if matching is successful, determining a word in the dictionary or the word bank matched with the character string as a recognized word segmentation. The word segmentation method based on dictionary and word bank matching can comprise the following steps: MM (Maximum positive Matching Method), RMM (reverse Maximum Matching Method), minimum cut Method, two-way Matching Method, and the like.
The word segmentation method based on word frequency statistics does not depend on a dictionary or a word bank, but counts the frequency of simultaneous occurrence of any two words in a text. The higher the frequency of simultaneous occurrence of two words, the greater the probability that the two words constitute a word. Specifically, the text may be fully segmented, then the frequency of occurrence of adjacent words is counted on the basis of the full segmentation, and the text is segmented based on the frequency. The model for implementing the word segmentation method based on word frequency statistics can comprise the following steps: an N-gram (N-gram), a hidden markov model, and the like, and the model is only exemplary and not particularly limited.
The word segmentation method based on the rules is mainly based on syntax and grammar analysis, combines semantic analysis, and defines words through analysis of information provided by context content, thereby achieving the purpose of word segmentation.
The above is only an exemplary illustration of the word segmentation method, and in practical applications, the content creation platform may also adopt other word segmentation methods, and the word segmentation method is not specifically limited herein.
And step A2, the content creation platform can screen out a plurality of participles expressing the content characteristics of the work from the obtained participles and organize the participles into a sentence smooth title.
For example, the content creation platform may count the occurrence frequency of each participle in the content of the work, and select the participle with the occurrence frequency higher than a preset threshold value as a keyword, as a plurality of participles expressing the characteristics of the original work. Here, the description is given only by way of example of "a plurality of phrases expressing the characteristics of the content of the work are selected from the obtained plurality of phrases", and the phrase is not particularly limited thereto.
In another mode, the content creation platform may input the obtained work content into a title generation model to perform title generation calculation, so as to generate a title for the work content.
The title generation model is a machine learning model trained by using a plurality of work contents and titles as training samples. The training samples are all high click-through rate work content and title pairs.
In implementation, the title generation model may be built by a Light Gradient boosting Machine (Light-weight Gradient boosting Machine), and of course, the title generation model may also be built by a classification model of a Back Propagation (BP) network, a Support Vector Machine (SVM), a logistic regression model, and a random forest, which is not specifically limited herein.
In implementation, the title generation model may output a plurality of titles, recommend the plurality of titles to a user, and select one title from the plurality of titles as a final title of the work.
In one embodiment, the header generation process described above may be performed on a blockchain. The content authoring platform may be a node device of a blockchain. Intelligent contracts generated by titles are deployed on the blockchain. The triggering mode of the title generation can be divided into two types.
The first mode is as follows: the title generation process is actively triggered by the user.
Specifically, a client of the blockchain may issue an instruction for title generation of the work content, and the content creation platform invokes a title generation logic in the intelligent contract deployed on the blockchain in response to the instruction for title generation of the work content issued by the client, analyzes the work content of the work to be issued based on semantic analysis, and generates a title of the work to be issued.
The second mode is as follows: whether the content of the work needs to be generated into a title or not is automatically identified by the blockchain.
Specifically, a client of the blockchain issues an instruction for chaining the content of the work, the content creation platform responds to the instruction for chaining the content of the work issued by the client and calls the evidence saving logic in the intelligent contract deployed on the blockchain, and if the content of the work has a title, the evidence saving logic in the intelligent contract stores the content of the work in the blockchain.
If the work to be issued lacks a title, further calling title generation logic in the intelligent contract deployed on the blockchain, analyzing the content of the work based on semantic analysis, and generating a title corresponding to the content of the work; and the evidence storage logic in the intelligent contract stores the work content and the title in a blockchain.
When the title generation process is executed on the blockchain, since the blockchain has the property of being not tampered, it is equivalent to chain-crediting the title generation process of the work. The title generation process corresponds to the work creation process, and the title adopted in the work creation process can be inquired in the title generation process, so that the authenticity of the creation process is further enhanced.
Corresponding to the above method embodiments, the present specification also provides an embodiment of a composition creation apparatus based on a blockchain.
The embodiment of the block chain-based hierarchical storage device of the present specification can be applied to an electronic device. The device embodiments may be implemented by software, or by hardware, or by a combination of hardware and software. Taking a software implementation as an example, as a logical device, the device is formed by reading, by a processor of the electronic device where the device is located, a corresponding computer program instruction in the nonvolatile memory into the memory for operation.
From a hardware aspect, as shown in fig. 5, the hardware structure diagram of the electronic device in which the block chain-based work creation apparatus of this specification is located is shown in fig. 5, except for the processor, the memory, the network interface, and the nonvolatile memory shown in fig. 5, the electronic device in which the apparatus is located in the embodiment may also include other hardware according to the actual function of the electronic device, which is not described again.
FIG. 6 is a block diagram of a blockchain-based work composition apparatus, as shown in an exemplary embodiment of the present specification. The device can be applied to electronic equipment and can comprise:
an attribute obtaining unit 502 for obtaining the product attribute of the to-be-created product input by the user;
a material retrieval unit 504, which retrieves material information related to the product attribute, and intelligently analyzes and processes the material information to generate creation auxiliary information;
a work acquisition unit 506 that outputs an auxiliary authoring prompt to the user based on the authoring auxiliary information and acquires content of a work created by the user based on the auxiliary authoring prompt;
an information acquisition unit 508, which acquires key information of a user in the process of creating the content of the work; wherein the key information comprises information for determining that the user is an originator of the content of the work;
and the work evidence storing unit 510 is used for issuing the key information and the obtained work content to the block chain for evidence storage.
Optionally, the key information includes one or more of the following combinations:
the creation time of the work content, the identity information of the user, the creation operation type of the work content and the creation position corresponding to the creation operation of the work content.
Optionally, the work to be created is an original text; the material information is text material information; the intelligent analysis processing includes NLP natural language processing.
Optionally, the authoring auxiliary information includes:
performing NLP natural language processing on the text material information to obtain a knowledge index related to the work attribute; and/or the presence of a gas in the gas,
and performing NLP natural language processing on the text material information to obtain a typesetting structure related to the product attribute.
Optionally, before the work evidence storing unit 510, the apparatus further includes:
the title generation unit is used for inputting the obtained work content into a title generation model to perform title generation calculation and generate a title for the work content; the title generation model is a machine learning model trained by using a plurality of work contents and titles as training samples.
The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. A typical implementation device is a computer, which may take the form of a personal computer, laptop computer, cellular telephone, camera phone, smart phone, personal digital assistant, media player, navigation device, email messaging device, game console, tablet computer, wearable device, or a combination of any of these devices.
In a typical configuration, a computer includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
The memory may include forms of volatile memory in a computer readable medium, Random Access Memory (RAM) and/or non-volatile memory, such as Read Only Memory (ROM) or flash memory (flash RAM). Memory is an example of a computer-readable medium.
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 computer storage media 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 disk storage, quantum memory, graphene-based storage media or other magnetic storage devices, or any other non-transmission medium that can be used to store information that can be accessed by a computing device. As defined herein, a computer readable medium does not include a transitory computer readable medium such as a modulated data signal and a carrier wave.
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 an … …" does not exclude the presence of other like elements in a process, method, article, or apparatus that comprises the element.
The foregoing description has been directed to specific embodiments of this disclosure. Other embodiments are within the scope of the following claims. In some cases, the actions or steps recited in the claims may be performed in a different order than in the embodiments and still achieve desirable results. In addition, the processes depicted in the accompanying figures do not necessarily require the particular order shown, or sequential order, to achieve desirable results. In some embodiments, multitasking and parallel processing may also be possible or may be advantageous.
The terminology used in the description of the one or more embodiments is for the purpose of describing the particular embodiments only and is not intended to be limiting of the description of the one or more embodiments. As used in one or more embodiments of the present specification and the appended claims, the singular forms "a," "an," and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It should also be understood that the term "and/or" as used herein refers to and encompasses any and all possible combinations of one or more of the associated listed items.
It should be understood that although the terms first, second, third, etc. may be used in one or more embodiments of the present description to describe various information, such information should not be limited to these terms. These terms are only used to distinguish one type of information from another. For example, first information may also be referred to as second information, and similarly, second information may also be referred to as first information, without departing from the scope of one or more embodiments herein. The word "if" as used herein may be interpreted as "at … …" or "when … …" or "in response to a determination", depending on the context.
The above description is only for the purpose of illustrating the preferred embodiments of the one or more embodiments of the present disclosure, and is not intended to limit the scope of the one or more embodiments of the present disclosure, and any modifications, equivalent substitutions, improvements, etc. made within the spirit and principle of the one or more embodiments of the present disclosure should be included in the scope of the one or more embodiments of the present disclosure.
Claims (11)
1. A method of blockchain-based work creation, the method comprising:
acquiring the work attribute of a work to be created input by a user;
retrieving material information related to the product attribute, and performing intelligent analysis processing on the material information to generate creation auxiliary information;
outputting an auxiliary creation prompt to the user based on the creation auxiliary information, and acquiring the content of the work created by the user based on the auxiliary creation prompt;
collecting key information of a user in the process of creating the content of the work; wherein the key information comprises information for determining that the user is an originator of the content of the work;
and issuing the key information and the obtained work content to a block chain for evidence storage.
2. The method of claim 1, the key information comprising a combination of one or more of:
the creation time of the work content, the identity information of the user, the creation operation type of the work content and the creation position corresponding to the creation operation of the work content.
3. The method of claim 1, wherein the work to be authored is creative text; the material information is text material information; the intelligent analysis processing includes NLP natural language processing.
4. The method of claim 3, the authoring assistance information comprising:
performing NLP natural language processing on the text material information to obtain a knowledge index related to the work attribute; and/or the presence of a gas in the gas,
and performing NLP natural language processing on the text material information to obtain a typesetting structure related to the product attribute.
5. The method of claim 1, wherein prior to issuing the key information and the obtained work content to a blockchain for credentialing, the method further comprises:
inputting the obtained work content into a title generation model to perform title generation calculation, and generating a title for the work content; the title generation model is a machine learning model trained by using a plurality of work contents and titles as training samples.
6. An apparatus for authoring a blockchain work, the apparatus comprising:
the attribute acquisition unit is used for acquiring the product attribute of the to-be-created product input by the user;
the material retrieval unit is used for retrieving material information related to the product attribute and intelligently analyzing and processing the material information to generate creation auxiliary information;
a work acquisition unit which outputs an auxiliary creation prompt to the user based on the creation auxiliary information and acquires the content of a work created by the user based on the auxiliary creation prompt;
the information acquisition unit is used for acquiring key information of a user in the process of creating the content of the work; wherein the key information comprises information for determining that the user is an originator of the content of the work;
and the work evidence storing unit is used for releasing the key information and the obtained work content to a block chain for evidence storage.
7. The apparatus of claim 6, the key information comprising a combination of one or more of:
the creation time of the work content, the identity information of the user, the creation operation type of the work content and the creation position corresponding to the creation operation of the work content.
8. The apparatus of claim 6, the work to be authored being original text; the material information is text material information; the intelligent analysis processing includes NLP natural language processing.
9. The apparatus of claim 8, the authoring assistance information comprising:
performing NLP natural language processing on the text material information to obtain a knowledge index related to the work attribute; and/or the presence of a gas in the gas,
and performing NLP natural language processing on the text material information to obtain a typesetting structure related to the product attribute.
10. The apparatus of claim 6, prior to the composition credentialing unit, the apparatus further comprising:
the title generation unit is used for inputting the obtained work content into a title generation model to perform title generation calculation and generate a title for the work content; the title generation model is a machine learning model trained by using a plurality of work contents and titles as training samples.
11. An electronic device, comprising:
a processor;
a memory for storing processor-executable instructions;
wherein the processor implements the method of any one of claims 1-5 by executing the executable instructions.
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