Cultural network content management method supporting cross-platform collaboration
By generating decentralized digital identity identifiers and storing them on a consortium blockchain, combined with ontology knowledge graphs and smart contracts, the problems of multimodal content formats and data silos in cross-platform content management are solved, achieving consistency and security in cross-platform content management.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-12-29
- Publication Date
- 2026-04-14
AI Technical Summary
The current cross-platform collaborative management of cultural network content faces challenges such as the difficulty in accurately depicting the multimodal nature of content, the lack of a unified and reliable decision-making and sharing mechanism, and data security risks associated with centralized storage, leading to the repeated appearance of illegal content on different platforms.
The system uses decentralized digital identity identifiers to generate initial verifiable credentials for multimodal copyright identification. Combined with consortium blockchain notarization, cultural network content domain ontology knowledge graphs, and smart contracts, it achieves semantic normalization and automated collaborative processes for cross-platform content management.
It establishes the source and ownership of content, enables deep semantic retrieval and knowledge discovery across platforms, ensures a transparent and fair management process, prevents data tampering, and achieves ultimate consistency across systems.
Smart Images
Figure CN121859291A_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of cultural network content management technology, specifically relating to a method for managing cultural network content that supports cross-platform collaboration. Background Technology
[0002] With the rapid development of the internet content ecosystem, cultural online content has experienced explosive growth across various digital media such as short videos, social media platforms, news portals, and live streaming. To maintain a clean online environment, various content platforms have generally established independent content review and handling mechanisms to identify and address illegal content such as pornography, violence, and misinformation. However, current mainstream content management methods heavily rely on internal platform rules and localized models, lacking cross-platform information sharing and collaborative governance capabilities. When a platform makes a decision to remove, limit, or label specific content, this decision is often not effectively known or reused by other platforms, leading to the repeated appearance of the same or highly similar illegal content on different platforms, creating a governance blind spot where one violation leads to widespread dissemination.
[0003] Currently, cross-platform collaborative content management faces two core challenges: (1) Content forms are becoming increasingly multimodal, and single text or image features are difficult to accurately depict the essence of the content; (2) There is a lack of a unified, credible and traceable decision-making sharing mechanism.
[0004] Current solutions for cross-platform collaborative cultural network content management have attempted to introduce hash fingerprints, digital watermarks, or simple feature vectors for content comparison. However, these methods lack robustness when faced with common transformations such as content cropping, transcoding, filtering, or semantic rewriting, making them prone to missed or false positives. Furthermore, some solutions rely on centralized databases for storing and processing records, which poses risks of data tampering, lack of trust between platforms, and privacy breaches, making it difficult to support efficient collaboration across large-scale, high-concurrency, and heterogeneous platforms. Summary of the Invention
[0005] In view of this, in order to solve the problems mentioned in the background technology, a cultural network content management method that supports cross-platform collaboration is proposed.
[0006] The objective of this invention can be achieved through the following technical solution: This invention provides a method for managing cultural network content that supports cross-platform collaboration, comprising: generating decentralized digital identity identifiers for each cultural network content item to be managed and user entities participating in collaborative management, and generating an initial verifiable credential containing a multimodal copyright identifier based on the digital identity identifiers.
[0007] Based on the digital identity identifier, the initial verifiable credential, cultural network content metadata, and creation time information are uploaded to the consortium blockchain to build a cross-platform copyright storage and verification system.
[0008] By using a pre-constructed ontology knowledge graph of cultural network content domain, semantic normalization is performed on cultural network content carrying heterogeneous metadata obtained from different target platforms to generate a standardized set of semantic metadata.
[0009] For each cultural network content entry that has been identified and authenticated, a collaborative workflow smart contract is deployed on the distributed ledger of the consortium blockchain.
[0010] By connecting to different target platforms through cross-platform application programming interfaces, the network content of each target platform is scanned in real time to identify infringing content corresponding to multimodal copyright marks.
[0011] When infringement is detected, the rights protection function is automatically triggered, and a removal notice is automatically sent to the corresponding platform through the smart contract. At the same time, a compliance evidence chain containing consortium blockchain evidence information, infringement comparison results and audit logs is generated.
[0012] Compared with existing technologies, the beneficial effects of the present invention are as follows: 1. By assigning decentralized digital identities to each cultural content item and participant and generating verifiable credentials, the present invention establishes the source, ownership and initial state of the content from the root, constructs a credible traceability chain that runs through the entire content lifecycle, and solves the problems of difficulty in guaranteeing the authenticity of traditional online content and unclear ownership.
[0013] 2. This invention utilizes a domain ontology knowledge graph to perform semantic normalization processing on heterogeneous metadata from different platforms, transforming platform-specific, unstructured descriptions into standardized, machine-understandable semantic information, completely breaking down data silos, and realizing deep semantic retrieval, association analysis, and knowledge discovery of cross-platform cultural content.
[0014] 3. This invention introduces smart contracts to solidify and automatically execute collaborative workflows, defining management processes such as review, release, and version control in code form on a distributed ledger. This ensures the transparency, fairness, and immutability of the management process, avoiding the uncertainty and operational risks associated with human intervention or internal strategies in traditional centralized systems.
[0015] 4. This invention designs an event-driven cross-platform state synchronization mechanism. Through the platform adapter module, the changes in the logical state on the chain are accurately and timely reflected in the actual display of each front-end platform, thus constructing a logically unified and physically distributed collaborative management system. Without changing the existing platform infrastructure, it achieves eventual consistency of data and state across systems. Attached Figure Description
[0016] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.
[0017] Figure 1 This is a schematic diagram illustrating the implementation steps of the method of the present invention. Detailed Implementation
[0018] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0019] Please see Figure 1 As shown, the present invention provides a method for managing cultural network content that supports cross-platform collaboration. The specific steps are as follows: S1, generate decentralized digital identity identifiers for each cultural network content item to be managed and the user entities participating in collaborative management, and generate an initial verifiable credential containing a multimodal copyright identifier based on the digital identity identifiers.
[0020] It should be noted that the decentralized digital identity identifier serves as a unified trust foundation for cross-platform copyright registration, collaborative workflow control, and infringement protection.
[0021] One specific example is that the cultural network content includes, but is not limited to, digital content with cultural dissemination or preservation value, such as core categories of cultural heritage, works of art, and historical events, as well as their creators, dates, geographical origins, and core attributes of the materials used.
[0022] In one feasible embodiment of the present invention, the specific process of generating decentralized digital identity identifiers includes: using an elliptic curve digital signature algorithm to generate asymmetric key pairs for each cultural network content entry and the user entities participating in collaborative management.
[0023] The public key is processed by the secure hash algorithm SHA-384, and then converted into a string conforming to the Uniform Resource Name (URI) format using the Uniform Resource Name encoding rules conforming to RFC 3986, which serves as a decentralized digital identity identifier.
[0024] It should be noted that the specific reason for specifying the use of SHA-384 in this invention is as follows: compared with SHA-25, SHA-384 has a longer hash value and stronger collision resistance, meaning it is more difficult to find two different contents that generate the same hash; compared with SHA-512, SHA-384 has higher computational efficiency and sufficient security, avoiding the impact of slow computation on the efficiency of generating credentials for a large amount of cultural content.
[0025] An identifier document containing a public key, cryptographic algorithm identifier, and service endpoint information is constructed and uploaded to a distributed storage network. The hash value of the identifier document content and the decentralized digital identity identifier are then anchored together on the distributed ledger of the consortium blockchain.
[0026] In one feasible embodiment of the present invention, the initial verifiable credential encapsulation content includes initial metadata and creation timestamp, and embeds a multimodal copyright identifier.
[0027] It should be noted that the initial metadata is specifically defined as the initial data describing the basic attributes of cultural network content, such as the subject-predicate-object triples mentioned later in this invention.
[0028] For example, a specific example of the subject-predicate-object triple could be: "Along the River During the Qingming Festival" - Creator - Zhang Zeduan.
[0029] The creation timestamp is specifically defined as a precise record of the time of content creation and digital completion to prevent time tampering.
[0030] The multimodal copyright identifier includes an explicit identifier containing author information and scope of authorization, as well as an implicit watermark embedded in the cultural network content data using anti-tampering and anti-compression technologies.
[0031] It should be further added that the hidden watermark has been processed to resist compression, cropping, and noise interference, ensuring that copyright can still be traced even if the cultural network content is tampered with.
[0032] In one specific example, the author information may be the creator's name, organization name, or decentralized digital identity ID; the scope of authorization may specifically allow educational platforms to reproduce the content for non-commercial purposes only or prohibit secondary editing.
[0033] The specific definition of embedding anti-tampering and anti-compression technologies into cultural network content data means that even if the cultural network content is cropped, compressed, or slightly edited, it can still be extracted by the watermark detection engine.
[0034] It should be noted that the implicit watermark embedded in cultural network content data using anti-tampering and anti-compression technology specifically includes the following steps: obtaining the original features of the cultural network content data, and extracting the image features, audio features, and text features respectively.
[0035] Based on the extracted image features, audio features, and text features, corresponding implicit watermark data are generated.
[0036] The generated implicit watermark data is embedded into the cultural network content data according to the preset fusion rules to form a multimodal fusion implicit watermark.
[0037] We perform anti-tampering and anti-compression processing on cultural network content data embedded with multimodal fusion implicit watermarks to ensure that the implicit watermarks maintain their integrity during data transmission and processing.
[0038] Verify whether the cultural network content data after embedding the hidden watermark meets the preset anti-tampering and anti-compression standards. If it does not meet the standards, readjust the embedding parameters of the hidden watermark and repeat the above steps.
[0039] It should also be noted that the anti-tampering and anti-compression processing specifically includes the following steps: obtaining cultural network content data after embedding multimodal fusion implicit watermarks, and analyzing its data distribution characteristics in the dimensions of image, audio and text features.
[0040] For each feature dimension, anti-tampering and anti-compression algorithms are designed, and these algorithms are applied to cultural network content data to generate processed enhanced content data.
[0041] It should also be explained that the algorithm includes an image feature protection mechanism based on discrete cosine transform, an audio feature protection mechanism based on spectrum analysis, and a text feature protection mechanism based on semantic embedding.
[0042] Simulated attack tests were conducted on the enhanced cultural network content data to verify the integrity and detectability of the hidden watermark. If the hidden watermark failed the integrity verification in the simulated attack test, the parameters of the anti-tampering and anti-compression algorithms were adjusted, and the above steps were repeated until the preset standards were met.
[0043] It should also be explained that the simulated attacks include data compression, cropping, and noise interference.
[0044] It should also be further explained that the image feature protection mechanism based on discrete cosine transform includes the following steps: obtaining image features from cultural network content data, extracting their pixel matrix and performing discrete cosine transform on 8×8 pixel blocks to generate a frequency domain representation.
[0045] The first 10% of low-frequency coefficients in the frequency domain are selected as the location for embedding the hidden watermark to ensure that the embedded hidden watermark has compression resistance.
[0046] The implicit watermark data is embedded into the selected low-frequency region according to preset rules to generate a frequency domain image with the implicit watermark.
[0047] It should be added that the specific content of the preset rules includes: (1) converting the implicit watermark data generated based on the original features of the image into a numerical format that is compatible with the low-frequency coefficients; (2) using a low-intensity weighted superposition method to embed the implicit watermark data into the selected low-frequency coefficients, such as making a slight adjustment to the low-frequency coefficients instead of directly replacing them, which ensures that the watermark can be extracted by the detection engine and avoids visual distortion of the image due to excessive coefficient changes.
[0048] It should also be added that the embedding position should avoid coefficients that are critical to the image structure in the low-frequency region, such as a few coefficients around the DC component, in order to prevent the watermark data and the core features of the image from being damaged at the same time during subsequent anti-cropping and anti-noise interference processing.
[0049] Furthermore, the embedding strength of the watermark data needs to be preset with a dynamically adjustable threshold: if subsequent simulated attack tests, such as 50% compression rate or edge cropping, show insufficient watermark integrity, the embedding strength will be automatically increased and the embedding process will be re-executed to ensure that the implicit watermark meets the document requirements. Even if the cultural network content is cropped, compressed, or slightly edited, it can still be extracted by the watermark detection engine.
[0050] The frequency domain image with embedded implicit watermark is subjected to inverse discrete cosine transform to restore it to a spatial domain image.
[0051] The recovered spatial domain image is subjected to compression resistance test to verify the detectability of the hidden watermark under compression conditions. If the test fails, the embedding position is reselected or the embedding rules are adjusted.
[0052] The audio feature protection mechanism based on spectrum analysis includes the following steps: acquiring audio features from cultural network content data, extracting their time-domain signals and performing fast Fourier transform to generate a spectrum representation.
[0053] The frequency range with low sensitivity to human hearing is selected as the embedding location for the hidden watermark in the spectrum, ensuring that the embedded hidden watermark has anti-tampering capabilities.
[0054] One specific example of the frequency range where the human ear has low sensitivity is: (1) mid-high frequencies such as 1kHz-4kHz sounds; (2) low frequencies such as near infrasound below 20Hz; (3) high-frequency edges such as near ultrasound above 16kHz sounds.
[0055] The implicit watermark data is embedded into the selected frequency range according to preset rules to generate spectral audio with embedded implicit watermark.
[0056] The spectral audio with embedded implicit watermark is subjected to inverse fast Fourier transform to recover the time-domain signal.
[0057] The recovered time-domain signal is subjected to anti-tampering tests to verify the detectability of the hidden watermark under cropping and noise interference conditions. If the test fails, the embedding position is reselected or the embedding rules are adjusted.
[0058] The text feature protection mechanism based on semantic embedding includes the following steps: acquiring text features from cultural network content data, extracting their semantic vector representations and performing word segmentation to generate a word sequence.
[0059] Words with high semantic redundancy are selected from the word sequence as the embedding positions for the implicit watermark to ensure that the embedded implicit watermark has anti-tampering capabilities.
[0060] The implicit watermark data is embedded into the selected word positions according to preset rules to generate semantically enhanced text with embedded implicit watermarks.
[0061] Perform semantic consistency verification on semantically enhanced text with embedded implicit watermarks to ensure that it does not undergo significant changes at the semantic level.
[0062] Perform anti-tampering tests on the text that passes semantic consistency verification to verify the detectability of the hidden watermark under text editing and format conversion conditions. If the test fails, reselect the embedding position or adjust the embedding rules.
[0063] In one feasible embodiment of the present invention, the specific process of generating the initial verifiable credential includes: constructing a credential subject field according to the verifiable credential data model specification, wherein the subject field includes the decentralized digital identity identifier of the user entity and the content entry, the SHA-384 hash digest value of the content data, the timestamp, and the initial metadata.
[0064] It should be noted that the core of the Verifiable Credentials Data Model specification is the W3C's "Verifiable Credentials Data Model," which defines the structured format, essential attributes, trust mechanisms, and security requirements of verifiable credentials, ensuring that verifiable credentials are machine-verifiable, tamper-proof, and cross-platform compatible.
[0065] The verifiable credentials are specifically a set of structured statements issued by the issuing entity, such as an individual or content item, such as "The creator of a certain cultural content is XX" or "The creation time of a certain intangible cultural heritage resource is XX". They must include encrypted proof, such as a digital signature, to ensure the authenticity and completeness of the statements.
[0066] The user entity uses its private key to digitally sign the credential body field and embeds the signature result into the credential proof field.
[0067] Submit complete, initial, verifiable credentials to the distributed ledger for archiving.
[0068] This invention establishes the source, ownership, and initial state of content from the root by assigning decentralized digital identities to each cultural content item and participant and generating verifiable credentials. It constructs a credible traceability chain that runs through the entire content lifecycle, solving the problems of difficulty in guaranteeing the authenticity of traditional online content and unclear ownership.
[0069] S2. Based on the digital identity identifier, the initial verifiable credential, cultural network content metadata, and creation time information are uploaded to the consortium blockchain to build a cross-platform copyright storage and verification system.
[0070] S3. Using a pre-constructed cultural network content domain ontology knowledge graph, semantic normalization is performed on cultural network content carrying heterogeneous metadata obtained from different target platforms to generate a standardized semantic metadata set.
[0071] In one feasible embodiment of the present invention, the specific pre-construction process of the cultural network content domain ontology knowledge graph includes: defining the core categories and core attributes of cultural network content using a network ontology language, and building the skeleton of the cultural network content domain ontology knowledge graph.
[0072] It should be explained that the network ontology semantics specifically refers to the international standard language of the Semantic Web, which can accurately describe the categories and attributes of cultural network content and avoid vague expressions.
[0073] Establish inheritance relationships between classes and subclasses, attributes and sub-attributes, and relationships between entities to form a strongly typed semantic network;
[0074] One specific example is that the relationships include, but are not limited to, creation relationships, inheritance relationships, collection relationships, and derivative relationships.
[0075] The natural language processing model is trained by using a cultural domain corpus to obtain a trained natural language processing model.
[0076] In one specific example, the natural language processing model may consist of a stack of twelve encoder layers, each layer integrating a multi-head self-attention mechanism, pre-trained with a large-scale cultural corpus and fine-tuned with digitized texts from museum collections, intangible cultural heritage projects, and ancient books.
[0077] The cultural network content domain ontology knowledge graph is constructed by combining the skeleton of the cultural network content domain ontology knowledge graph, the strongly typed semantic network, and the natural language processing model.
[0078] In one feasible embodiment of the present invention, the specific process of generating a standardized semantic data set includes: classifying cultural network content carrying heterogeneous metadata obtained from different target platforms to obtain cultural network content with structured heterogeneous metadata and unstructured heterogeneous metadata.
[0079] The cultural network content field of the structured heterogeneous metadata is aligned with the standard attributes in the cultural network content domain ontology knowledge graph to obtain the structured heterogeneous metadata mapping result.
[0080] The unstructured heterogeneous metadata cultural network content is used as input to import the natural language processing model in the ontology knowledge graph of the cultural network content domain, and the entity fragments labeled with ontology concept tags and their confidence scores are output to obtain the unstructured heterogeneous metadata mapping results.
[0081] By integrating the mapping results of structured heterogeneous metadata and unstructured heterogeneous metadata, a set of semantic metadata triples consisting of subject, predicate, and object is generated and serialized into a resource description framework format, thereby generating a standardized set of semantic metadata.
[0082] This invention utilizes a domain ontology knowledge graph to semantically normalize heterogeneous metadata from different platforms, transforming platform-specific, unstructured descriptions into standardized, machine-understandable semantic information. This completely breaks down data silos and enables deep semantic retrieval, association analysis, and knowledge discovery of cross-platform cultural content.
[0083] S4. Deploy a collaborative workflow smart contract on the distributed ledger of the consortium blockchain for each cultural network content entry that has been identified and certified.
[0084] In one feasible embodiment of the present invention, the smart contract defines the content lifecycle states of draft, under review, published, archived, and revoked, and the corresponding state transition functions.
[0085] The state transition function incorporates access control logic and copyright verification rules based on decentralized digital identity identifiers, allowing only authorized user entities to trigger state changes, and all operation records are written to the distributed ledger to form an audit log.
[0086] The state transition functions include version update functions and ownership change functions.
[0087] The version update function allows content owners to submit new versions of content in either draft or archived state, calculates a hash digest value of the new content to replace the current version, stores the old hash value in the history array, and resets the state to draft.
[0088] The ownership change function will only take effect after being jointly confirmed by the current owner and the newly designated owner.
[0089] In one feasible embodiment of the present invention, the specific process of deploying the collaborative workflow smart contract includes: declaring a dynamic array for storing historical version content hash digest values, an address array for maintaining a list of decentralized digital identity identifiers of authorized reviewers, and a mapping structure for recording review voting results.
[0090] The submission review function verifies whether the caller is the content owner. If so, it changes the status from draft to review and broadcasts the review request event.
[0091] The approval function checks whether the caller is in the list of authorized reviewers, records the votes of approval, and changes the status to published when the number of votes of approval reaches a preset threshold, triggering a content publication event.
[0092] This invention introduces smart contracts to solidify and automatically execute collaborative workflows. It defines management processes such as review, release, and version control in code form on a distributed ledger, ensuring the transparency, fairness, and immutability of the management process. This avoids the uncertainty and operational risks brought about by human intervention or internal strategies in traditional centralized systems.
[0093] S5. By connecting to different target platforms through cross-platform application programming interfaces, it performs real-time scanning of network content on each target platform and identifies infringing content corresponding to multimodal copyright marks.
[0094] It should be further added that, specifically, the connection to each target platform through the cross-platform application programming interface involves broadcasting a named state change event after the collaborative workflow smart contract executes the state transition function. This event is then listened to and parsed by the platform adapter module of each platform, which calls the native application programming interface of the target platform to synchronously update the local content state, standardized semantic metadata, and access permissions, thereby achieving cross-platform state consistency.
[0095] The platform adapter module includes an event listener, a transaction parser, and a platform executor.
[0096] The event listener establishes a long connection with the full node of the distributed ledger through a remote procedure call interface and subscribes to logs related to the smart contract address of the collaborative workflow.
[0097] The transaction parser decodes the original logs according to the smart contract application binary interface specification, restoring the structured event names and parameters.
[0098] The platform executor is pre-set with the target platform application interface authentication token and request template, dynamically constructs requests based on event parameters, and calls the platform interface to perform status update, metadata overwrite, or cache clearing operations.
[0099] S6. When infringement is detected, the rights protection function is automatically triggered, and a removal notice is automatically sent to the corresponding platform through the smart contract. At the same time, a compliance evidence chain containing consortium blockchain evidence information, infringement comparison results and audit logs is generated.
[0100] In one feasible embodiment of the present invention, the specific process of identifying infringing content corresponding to the multimodal copyright mark includes: acquiring network content data of the target platform and parsing the image, audio and text information in the network content data.
[0101] The watermark detection engine is invoked to perform multimodal copyright mark detection on the parsed image, audio, and text information.
[0102] The detection results are compared with the multimodal copyright identifier features stored in the consortium blockchain to determine whether there is infringing content.
[0103] If infringing content is detected, the system records the characteristics of the infringing content and the identification information of the target platform, and transmits them to the smart contract module to automatically trigger the rights protection function.
[0104] It should be noted that the rights protection function is a core functional module that is automatically executed by the smart contract module after infringing content is detected. It is used to achieve automated rights protection and compliant evidence solidification. Its specific content revolves around two core objectives: infringement handling notification and compliant evidence chain generation.
[0105] In one feasible embodiment of the present invention, the specific process of generating a compliance evidence chain containing consortium blockchain evidence information, infringement comparison results and audit logs includes: obtaining multimodal copyright identification features of detected infringing content, extracting author information and authorization scope from explicit identifiers and unique identifier information from implicit watermarks.
[0106] The extracted multimodal copyright identifier features are compared with the original copyright information stored in the consortium blockchain to generate an infringement comparison result. The infringement comparison result includes the calculation process of the matching degree threshold and the final matching degree value.
[0107] Based on the comparison results, and combined with the detection time, target platform identification information, and characteristic information of the infringing content, an initial chain of evidence for compliance is constructed.
[0108] The initial compliance evidence chain is formatted to ensure that it meets the requirements of the preset evidence chain template, which includes a timestamp field, an infringing content feature field, and a comparison result field.
[0109] The formatted, compliant evidence chain is uploaded to the consortium blockchain and synchronized with the relevant copyright management agency to support subsequent legal proceedings. At the same time, the upload time and operation log are recorded to ensure the immutability and traceability of the evidence chain.
[0110] This invention designs an event-driven cross-platform state synchronization mechanism. Through the platform adapter module, changes in the logical state on the chain are accurately and timely reflected in the actual display of each front-end platform, thus constructing a logically unified and physically distributed collaborative management system. Without changing the existing platform infrastructure, it achieves eventual consistency of data and state across systems.
[0111] The above embodiments can be implemented, in whole or in part, by software, hardware, firmware, or any other combination thereof. When implemented using software, the above embodiments can be implemented, in whole or in part, in the form of a computer program product.
[0112] Those skilled in the art will recognize that the algorithmic steps of the various examples described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are implemented in hardware or software depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementations should not be considered beyond the scope of this application.
[0113] In addition, the functional modules in the various embodiments of this application can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module.
[0114] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.
[0115] Finally, the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.
Claims
1. A method for managing cultural network content that supports cross-platform collaboration, characterized in that: include: A decentralized digital identity identifier is generated for each cultural network content item to be managed and the user entity participating in collaborative management, and an initial verifiable credential containing a multimodal copyright identifier is generated based on the digital identity identifier. Based on the digital identity identifier, the initial verifiable credential, cultural network content metadata, and creation time information are uploaded to the consortium blockchain to build a cross-platform copyright storage and verification system. By using a pre-constructed ontology knowledge graph of cultural network content domain, semantic normalization is performed on cultural network content carrying heterogeneous metadata obtained from different target platforms to generate a standardized set of semantic metadata. Deploy collaborative workflow smart contracts on the distributed ledger of the consortium blockchain for each cultural network content entry that has been identified and certified. By connecting to different target platforms through cross-platform application programming interfaces, the network content of each target platform is scanned in real time to identify infringing content corresponding to multimodal copyright marks; When infringement is detected, the rights protection function is automatically triggered, and a removal notice is automatically sent to the corresponding platform through the smart contract. At the same time, a compliance evidence chain containing consortium blockchain evidence information, infringement comparison results and audit logs is generated.
2. The method for managing cultural network content that supports cross-platform collaboration according to claim 1, characterized in that: The specific process for generating decentralized digital identity identifiers includes: An elliptic curve digital signature algorithm is used to generate asymmetric key pairs for each cultural network content entry and the user entities participating in collaborative management. The public key is processed by the secure hash algorithm SHA-384, and then converted into a string conforming to the Uniform Resource Name (URI) format using the Uniform Resource Name (URI) encoding rules conforming to RFC 3986, which serves as a decentralized digital identity identifier. An identifier document containing a public key, cryptographic algorithm identifier, and service endpoint information is constructed and uploaded to a distributed storage network. The hash value of the identifier document content and the decentralized digital identity identifier are then anchored together on the distributed ledger of the consortium blockchain.
3. The method for managing cultural network content that supports cross-platform collaboration according to claim 2, characterized in that: The initial verifiable credential encapsulation includes initial metadata and a creation timestamp, and embeds a multimodal copyright identifier; The multimodal copyright identifier includes an explicit identifier containing author information and scope of authorization, as well as an implicit watermark embedded in the cultural network content data using anti-tampering and anti-compression technologies.
4. The method for managing cultural network content that supports cross-platform collaboration according to claim 3, characterized in that: The specific process for generating the initial verifiable credential includes: The credential body field is constructed according to the verifiable credential data model specification. The body field includes the decentralized digital identity identifier of the user entity and the content item, the SHA-384 hash digest value of the content data, the timestamp and the initial metadata. The user entity uses its private key to digitally sign the credential body field and embeds the signature result into the credential proof field. The document subject field and the document proof field are collectively referred to as the initial verifiable document, and the initial verifiable document is submitted to the distributed ledger for storage.
5. A method for managing cultural network content that supports cross-platform collaboration according to claim 1, characterized in that: The specific pre-construction process of the cultural network content domain ontology knowledge graph includes: Define the core categories and core attributes of cultural network content using the network ontology language, and build the framework of the ontology knowledge graph of cultural network content domain; Establish inheritance relationships between classes and subclasses, attributes and sub-attributes, and relationships between entities to form a strongly typed semantic network; The natural language processing model is trained by using a cultural domain corpus to obtain a trained natural language processing model. The cultural network content domain ontology knowledge graph is constructed by combining the skeleton of the cultural network content domain ontology knowledge graph, the strongly typed semantic network, and the natural language processing model.
6. A method for managing cultural network content that supports cross-platform collaboration according to claim 5, characterized in that: The specific process for generating the standardized semantic metadata set includes: The cultural network content carrying heterogeneous metadata obtained from different target platforms is classified to obtain cultural network content with structured heterogeneous metadata and unstructured heterogeneous metadata. The cultural network content field of the structured heterogeneous metadata is aligned with the standard attributes in the cultural network content domain ontology knowledge graph to obtain the structured heterogeneous metadata mapping result; The unstructured heterogeneous metadata cultural network content is used as input to import the natural language processing model in the cultural network content domain ontology knowledge graph, and the entity fragments labeled with ontology concept tags and their confidence scores are output to obtain the unstructured heterogeneous metadata mapping results. By integrating the mapping results of structured heterogeneous metadata and unstructured heterogeneous metadata, a set of semantic metadata triples consisting of subject, predicate, and object is generated and serialized into a resource description framework format, thereby generating a standardized set of semantic metadata.
7. A method for managing cultural network content that supports cross-platform collaboration according to claim 1, characterized in that: The smart contract defines the content lifecycle states of draft, under review, published, archived, and revoked, as well as the corresponding state transition functions; The state transition function has built-in access control logic and copyright verification rules based on decentralized digital identity identifiers. It only allows authorized user entities to trigger state changes, and all operation records are written to the distributed ledger to form an audit log. The state transition functions include version update functions and ownership change functions; The version update function allows the content owner to submit a new version of the content in either draft or archived state, calculates the hash digest value of the new content to replace the current version, stores the old hash value in the history array, and resets the state to draft state. The ownership change function will only take effect after being jointly confirmed by the current owner and the newly designated owner.
8. A method for managing cultural network content that supports cross-platform collaboration according to claim 7, characterized in that: The specific process of deploying the collaborative workflow smart contract includes: The declaration includes a dynamic array for storing hash digests of historical versions, an address array for maintaining a list of decentralized digital identifiers for authorized reviewers, and a mapping structure for recording review voting results. The submission review function verifies whether the caller is the content owner. If so, the status is changed from draft to review and a review request event is broadcast. The approval function checks whether the caller is in the list of authorized reviewers, records the votes of approval, and changes the status to published when the number of votes of approval reaches a preset threshold, triggering a content publication event.
9. A method for managing cultural network content that supports cross-platform collaboration according to claim 1, characterized in that: The specific process for identifying infringing content corresponding to multimodal copyright marks includes: Acquire network content data from the target platform and parse the image, audio, and text information within the network content data; The watermark detection engine is invoked to perform multimodal copyright mark detection on the parsed image, audio, and text information; The detection results are compared with the multimodal copyright identifier features stored in the consortium blockchain to determine whether infringing content exists. If infringing content is detected, the system records the characteristics of the infringing content and the identification information of the target platform, and transmits them to the smart contract module to automatically trigger the rights protection function.
10. A method for managing cultural network content that supports cross-platform collaboration according to claim 9, characterized in that: The specific process for generating a compliant chain of evidence includes: Obtain multimodal copyright identification features of detected infringing content, and extract author information and scope of authorization from explicit identifiers and unique identifier information from implicit watermarks; The extracted multimodal copyright identifier features are compared with the original copyright information stored in the consortium blockchain to generate an infringement comparison result. The infringement comparison result includes the calculation process of the matching degree threshold and the final matching degree value. Based on the comparison results, combined with the detection time, target platform identification information, and characteristic information of the infringing content, an initial chain of compliance evidence is constructed. The initial compliance evidence chain is formatted to ensure that it meets the requirements of the preset evidence chain template, which includes a timestamp field, an infringing content feature field, and a comparison result field. The formatted compliance evidence chain is uploaded to the consortium blockchain and synchronized with the relevant copyright management agency.