Environmental equity asset management method and device based on mapping knowledge domain

Abstract

The invention provides an environmental right and interest asset management method and device based on a knowledge graph, and the method comprises the steps: determining a first target node associated with a target user in a knowledge graph related to environmental right and interest assets according to the first information of the target user; according to a second target node connected with the first target node in the knowledge graph and attribute information of an edge between the first target node and the second target node, obtaining environment right asset data associated with the target user; inputting the environmental right and interest asset data into an asset evaluation model to obtain an evaluation result output by the asset evaluation model for the current environmental right and interest asset of the target user; and generating an asset management strategy of the target user according to the evaluation result. Therefore, the knowledge graph and the machine learning model can be combined to dynamically evaluate and accurately predict the value and risk of the environmental rights and interests assets, suggestions for asset management optimization can be provided, and the efficiency and income of asset management can be improved.

Description

Technical Field

[0001] The present application relates to the field of environmental rights and interests asset management, and in particular to a method and device for environmental rights and interests asset management based on knowledge graph. Background Art

[0002] As global climate change intensifies, strategic goals like carbon peak and carbon neutrality are increasingly on the agenda, and the importance of environmental equity asset management is becoming increasingly prominent. Environmental equity assets are tradable rights to use environmental capacity, acquired by companies through environmental governance investments or administrative allocations. These include carbon emission rights, energy rights, and water rights, and possess economic value and are tradable in the market.

[0003] The management significance of environmental rights and interests assets is reflected in multiple dimensions such as economy, environment, society and policy. It is conducive to driving green economic transformation, optimizing resource allocation and ecological protection, etc. Therefore, more efficient and accurate environmental rights and interests asset management methods are needed. Summary of the Invention

[0004] The present application aims to solve one of the technical problems in the related art at least to a certain extent.

[0005] To this end, the first purpose of this application is to propose an environmental rights and interests asset management method based on knowledge graph, so as to solve the problems of data dispersion, insufficient information correlation and lack of dynamic analysis capabilities in the existing environmental rights and interests asset management, and to integrate multi-source data, conduct unified analysis and dynamic evaluation, and improve asset management efficiency and decision-making accuracy.

[0006] The second purpose of this application is to propose an environmental rights and interests asset management device based on knowledge graph.

[0007] The third objective of this application is to provide an electronic device.

[0008] The fourth object of this application is to provide a computer-readable storage medium.

[0009] A fifth object of this application is to provide a computer program product.

[0010] To achieve the above objectives, the first embodiment of the present application proposes a method for managing environmental rights and interests assets based on a knowledge graph, including:

[0011] Determining, based on the first information of the target user, a first target node associated with the target user in a knowledge graph related to environmental equity assets;

[0012] Obtaining environmental equity asset data associated with the target user based on the second target node connected to the first target node in the knowledge graph and attribute information of the edge between the first target node and the second target node;

[0013] Inputting the environmental equity asset data into an asset evaluation model to obtain an evaluation result output by the asset evaluation model for the target user's current environmental equity assets;

[0014] An asset management policy for the target user is generated based on the evaluation result.

[0015] To achieve the above objectives, the second embodiment of the present application proposes an environmental rights and interests asset management device based on a knowledge graph, comprising:

[0016] a determination module, configured to determine, based on the first information of the target user, a first target node associated with the target user in a knowledge graph related to environmental equity assets;

[0017] An acquisition module, configured to obtain environmental equity asset data associated with the target user based on the second target node connected to the first target node in the knowledge graph and attribute information of the edge between the first target node and the second target node;

[0018] An evaluation module, configured to input the environmental equity asset data into an asset evaluation model to obtain an evaluation result output by the asset evaluation model for the target user's current environmental equity assets;

[0019] A policy module is used to generate an asset management policy for the target user based on the evaluation result.

[0020] To achieve the above-mentioned purpose, a third embodiment of the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0021] The memory stores computer-executable instructions;

[0022] The processor executes the computer-executable instructions stored in the memory to implement the environmental asset rights and interests management method based on the knowledge graph as described in the embodiment of the first aspect.

[0023] To achieve the above-mentioned purpose, the fourth embodiment of the present application proposes a computer-readable storage medium, which stores computer execution instructions. When the computer execution instructions are executed by the processor, they are used to implement the environmental asset rights and interests management method based on the knowledge graph as described in the first embodiment.

[0024] To achieve the above-mentioned purpose, the fifth embodiment of the present application proposes a computer program product, including a computer program, which, when executed by a processor, implements the environmental asset rights and interests management method based on the knowledge graph as described in the first embodiment.

[0025] The knowledge graph-based environmental rights asset management method and device provided in this application, by combining the knowledge graph and the asset valuation model, dynamically evaluates and accurately predicts the value and risk of environmental rights assets, which is conducive to improving the accuracy of asset management decisions, and provides users with optimized management suggestions to improve the efficiency and benefits of asset management.

[0026] Additional aspects and advantages of the present application will be given in part in the description below, and in part will become apparent from the description below, or will be learned through practice of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The above and / or additional aspects and advantages of the present application will become apparent and easily understood from the following description of the embodiments in conjunction with the accompanying drawings, in which:

[0028] Figure 1 A flowchart of a method for managing environmental rights and interests assets based on a knowledge graph provided in an embodiment of the present application;

[0029] Figure 2 A schematic diagram of a process for constructing a knowledge graph provided in an embodiment of the present application;

[0030] Figure 3 A schematic diagram of a knowledge graph provided in an embodiment of the present application;

[0031] Figure 4 A flowchart of another method for managing environmental rights and interests assets based on a knowledge graph provided in an embodiment of the present application; and

[0032] Figure 5 A schematic structural diagram of an environmental rights and interests asset management device based on a knowledge graph provided in an embodiment of the present application. DETAILED DESCRIPTION

[0033] The following describes in detail embodiments of the present application, examples of which are shown in the accompanying drawings, wherein the same or similar reference numerals throughout represent the same or similar elements or elements having the same or similar functions. The embodiments described below with reference to the accompanying drawings are exemplary and are intended to be used to explain the present application, and should not be construed as limiting the present application.

[0034] The following describes the environmental rights and interests asset management method and device based on the knowledge graph in an embodiment of the present application with reference to the accompanying drawings.

[0035] Current environmental equity asset management methods fragment environmental equity asset data from diverse sources, such as transaction records, policies and regulations, and corporate emissions data, across multiple systems. This lack of unified integration and management results in low management efficiency. The lack of semantic associations between collected data limits the accuracy of asset valuation and management. Furthermore, current management methods often rely on static analysis, failing to consider the impact of factors such as market price fluctuations and policy changes on environmental equity assets. This makes it difficult to meet the needs of dynamic assessment and optimized management.

[0036] To address this issue, an embodiment of the present application provides an environmental rights and interests asset management method based on a knowledge graph, which uses the knowledge graph to construct a semantic association network between multi-source environmental rights and interests asset data, conducts data integration, and improves management efficiency. It also uses the constructed knowledge graph and asset valuation model to dynamically evaluate the asset value and risk of the enterprise, thereby improving the accuracy of asset management decisions.

[0037] It should be noted that the environmental rights asset management method based on knowledge graph provided in this application can be run on a cloud server, a local server or a terminal device (such as a computer, a smart phone, etc.), and stored in a computer-readable storage medium to implement the execution of the method in a programmed manner.

[0038] Figure 1 A flowchart of a knowledge graph-based environmental rights asset management method provided in an embodiment of the present application.

[0039] like Figure 1 As shown, the environmental rights and interests asset management method based on the knowledge graph includes the following steps:

[0040] Step 101: Determine a first target node associated with the target user in a knowledge graph related to environmental equity assets based on the first information of the target user.

[0041] Among them, target users refer to users who need to conduct value assessment and management of their own environmental rights and interests assets. Target users can be individuals or enterprises.

[0042] Among them, the first information of the target user refers to the data used to determine the user's specific environmental rights and interests assets, which may include a character string that can uniquely identify the user, such as the target user's name, identity document (ID), etc., as well as at least one item of information such as the asset type and quota quantity held by the target user.

[0043] In an embodiment of the present application, data related to environmental rights and interests assets can be collected in advance from multi-source data platforms such as carbon trading markets, monitoring agencies, and policy databases. The data collected in the carbon trading market can be transaction records of each user's assets, including transaction product types, prices, quantities, and times, etc. The data collected in the monitoring agency can be operational data of each user, such as emissions, production data, etc. The data collected in the policy database can be published policy documents and policy update logs. The relationships between entities and entities are then extracted from the collected data as nodes and edges in the knowledge graph to construct a knowledge graph related to environmental rights and interests assets. The constructed knowledge graph can then be used to manage environmental rights and interests assets for different users to predict asset value changes and risks.

[0044] It should be noted that in this application, the data used to construct the knowledge graph can be data related to the environmental rights and interests of all users, so the knowledge graph can be used to manage assets for different users. Therefore, when managing assets for a specific user, it is necessary to determine the nodes associated with the user and the information corresponding to the nodes in the knowledge graph in order to conduct targeted evaluation and prediction of the user's assets and ensure the reliability of management. Alternatively, the knowledge graph can also be constructed using data related to a specific user. In this case, each node in the constructed knowledge graph can be the first target node associated with the target user.

[0045] In an embodiment of the present application, the first information of the target user who currently needs to perform asset management can be used to match the entity corresponding to each node in the knowledge graph, thereby determining the first target node associated with the target user in the knowledge graph. Each node in the knowledge graph can represent an entity, such as an asset, transaction, or policy. The first target node associated with the target user is the node in the knowledge graph that corresponds to the asset type owned by the target user, the record of the target user's transaction, and the policy that affects the target user's production.

[0046] For example, if the first information of the target user includes that the asset type held by the user is carbon emission rights, then the first target node associated with the target user can be the node representing the asset of carbon emission rights in the knowledge graph, as well as the node corresponding to the relevant policies of carbon emission rights, etc.

[0047] It should be noted that the first target node should be all nodes in the knowledge graph that can match the first information, and the number of first target nodes can be one or more.

[0048] Step 102: Obtain the environmental rights and interests asset data associated with the target user based on the second target node connected to the first target node in the knowledge graph and the attribute information of the edge between the first target node and the second target node.

[0049] The second target node is a node corresponding to another entity that has an association relationship with the entity of the first target node. In the knowledge graph, it is a node connected to the first target node by an edge. For different first target nodes, the second target nodes connected to them may be the same or different. The second target node connected to a first target node may be a different first target node.

[0050] In an embodiment of the present application, different nodes (i.e., entities) may have different association relationships, for example, "enterprises own assets", "policies affect transactions", etc. When constructing a knowledge graph, the association type between the entities represented by the two nodes can be determined by performing semantic analysis on the data, and then it can be saved in the knowledge graph as attribute information of the edge connecting the two nodes.

[0051] Therefore, in the embodiment of the present application. The second target node connected to the first target node can be determined based on the connection between each node in the knowledge graph, and then the association relationship between the first target node and the second target node can be determined based on the attribute information of the edge connecting the first target node and the second target node. This can clarify what information needs to be considered when evaluating and risk-forecasting the environmental rights and interests assets of the target user and what impact this information has on the environmental rights and interests assets, and obtain the environmental rights and interests asset data associated with the target user. For example, the environmental rights and interests asset data may include that the target user owns assets A and B, that the value of asset A increases due to the influence of policy a, that the number of market transactions of asset B increases due to the influence of policy b, and so on.

[0052] Step 103: Input the environmental equity asset data into the asset evaluation model to obtain the evaluation result output by the asset evaluation model for the target user's current environmental equity assets.

[0053] Among them, the asset valuation model can be a model that can evaluate and predict the future changing trend of the value of environmental equity assets after training any existing machine learning model.

[0054] In an embodiment of the present application, by inputting environmental equity asset data into an asset valuation model, the asset valuation model can automatically analyze the future trend of the environmental equity asset value and predict the asset risks that the target user may be exposed to based on the assets owned by the target user in the environmental equity asset data, market transaction records, and policies that affect the asset value, and output the valuation results.

[0055] It should be noted that the future value trend of the user's environmental equity assets in the evaluation results can be represented by charts such as line charts, and the factors that cause the value changes can be explained in the charts, so that users can obtain the current asset evaluation status more clearly and quickly, thereby improving the efficiency of asset management.

[0056] Step 104: Generate an asset management policy for the target user based on the evaluation result.

[0057] In this embodiment, an optimization algorithm can be applied to the assessment results to determine management methods that maximize asset value and minimize risk, generate strategies, and provide users with optimal asset management recommendations. For example, in the carbon trading market, users can be advised on the optimal trading time and volume based on the current asset value and predicted trends to maximize returns. This allows for optimized management recommendations based on the analysis of environmental equity asset-related data, improving asset management efficiency and profitability.

[0058] In this embodiment, first, based on the first information of the target user, in the knowledge graph related to environmental rights and interests assets, the first target node associated with the target user is determined. Then, based on the second target node connected to the first target node in the knowledge graph, and the attribute information of the edge between the first target node and the second target node, the environmental rights and interests asset data associated with the target user is obtained. The environmental rights and interests asset data is then input into the asset valuation model to obtain the evaluation results of the asset valuation model for the target user's current environmental rights and interests assets. Then, based on the evaluation results, the asset management strategy of the target user is generated to achieve the management optimization of environmental rights and interests assets. By combining the knowledge graph and the asset valuation model, the value and risk of environmental rights and interests assets can be dynamically evaluated and accurately predicted, which is conducive to improving the decision-making accuracy of asset management, and providing users with optimized management suggestions to improve the efficiency and benefits of asset management.

[0059] It should be noted that when managing environmental rights and interests assets for different target users, the knowledge graph used can be the same, so the knowledge graph can be built and stored in advance, and then called each time asset management is needed. The knowledge graph construction process can be used as follows: Figure 2 To explain, Figure 2 A schematic diagram of the process of constructing a knowledge graph provided in an embodiment of the present application.

[0060] like Figure 2 As shown in the figure, the knowledge graph construction process can include the following steps:

[0061] Step 201: Acquire first data in a reference platform.

[0062] Among them, the reference platform refers to a website or platform that can provide data related to environmental rights and interests assets.

[0063] Among them, the first data is data associated with environmental rights and interests assets.

[0064] In an embodiment of the present application, there may be multiple reference platforms for obtaining the first data, and the knowledge graph constructed thereby may integrate multi-source data, so that the knowledge graph used for management can provide a more comprehensive and reliable evaluation basis, improve the accuracy of asset management, and eliminate information islands.

[0065] It should be noted that after obtaining the first data, the first data can also be cleaned and preprocessed, such as removing noise and erroneous data, cleaning redundant data, and unifying the data format, etc., to improve data quality and optimize the efficiency of knowledge graph construction.

[0066] Optionally, the reference platform may include at least one of a carbon trading market, a policy database, and an environmental monitoring agency.

[0067] In the embodiments of this application, a carbon trading market refers to a platform where enterprises can sell or purchase allowances due to surplus or shortage of equity assets. A carbon trading market can be a local carbon emissions exchange, and the first data obtained from the carbon trading market can include transaction records of environmental equity assets and the types of traded assets.

[0068] In an embodiment of the present application, the policy database is used to store policy documents issued by various policy-making departments. The first data obtained from the policy database may include policy documents and policy update logs. Policy documents may include laws, regulations, rules, policy interpretations, planning texts, speeches by leaders, government reports, etc. The policy update log may record the change history of policies, such as revisions and repeals.

[0069] In the embodiment of the present application, the environmental monitoring agency is an agency that monitors the emissions of enterprises. The first data obtained from the environmental monitoring agency may include the enterprise name, pollutant type, emission amount, emission concentration, emission method, etc.

[0070] Step 202: Perform semantic analysis on the first data to extract first entities and relationships between first entities in the first data.

[0071] In an embodiment of the present application, semantic analysis can be performed on the first data to identify all entities contained in the first data, such as enterprises, asset types, transaction records, emissions, policies and regulations, and the relationships between the entities, so as to obtain the first entities in the first data and the relationships between the first entities, thereby mining the potential relationships and influencing factors between assets, so that the knowledge graph can construct a huge semantic network based on the relationships between entities, and unify multi-source heterogeneous data into structured knowledge.

[0072] Step 203: Taking the first entity as a node, and based on the association relationship between the first entities, determining the edges between the nodes corresponding to the first entity, so as to construct a knowledge graph related to environmental equity assets.

[0073] In an embodiment of the present application, each first entity can be regarded as a node in the knowledge graph, and then every two first entities with an association relationship can be connected by using edges to connect their corresponding nodes, so that a knowledge graph related to environmental equity assets can be obtained.

[0074] It should be noted that in the knowledge graph, the specific content of the entity corresponding to each node can be stored in the node, so that when different users use the knowledge graph for asset management, they can determine which nodes are related to the users through data matching.

[0075] In the embodiment of the present application, since the association relationships between the first entities corresponding to different nodes may be different, for example, the impact of policy a on asset A is an increase in market value, but the impact of policy a on asset B is a decrease in market value, etc., in this case, only using edges in the knowledge graph to represent the association between the two nodes cannot reflect the specific impact mode during value assessment, resulting in inaccurate management. Therefore, the specific association type between nodes can be stored as attribute information of the corresponding edge in the knowledge graph, so that the impact mode between entities can be quickly determined through the knowledge graph, further improving the accuracy of data analysis based on the knowledge graph.

[0076] Optionally, attribute information of the edge between the nodes corresponding to the two first entities can be determined according to the type of the association relationship between the two first entities, and the attribute information can be stored in the knowledge graph.

[0077] The type of the association relationship between the first entities can be of different types according to actual needs, such as an ownership relationship, a relationship that causes price fluctuations (increase or decrease), a relationship that causes quota increases or decreases, etc.

[0078] It should be noted that edges between nodes in a knowledge graph can be directed lines, with the arrow pointing in the direction of the affected entity. Edges between nodes can be undirected if the entities corresponding to the two nodes connected by the edge have no affiliation or causal relationship.

[0079] For example, when the first data contains the first entity A, the first entity B and the first entity C, and the first entity A owns the first entity B, and the value of the first entity B increases due to the influence of the first entity C, the first entity A, the first entity B and the first entity C can be represented as corresponding nodes A, B and C respectively, and then node A is connected to node B, the direction of the edge is from node A to node B, and the attribute information of the edge is the ownership relationship, and node B is connected to node C, the direction of the edge is from node C to node B, and the attribute information of the edge is the price increase, then the construction of the knowledge graph can be completed, and the knowledge graph can be as follows: Figure 3 shown.

[0080] In this embodiment, by collecting environmental rights and interests asset-related data from different platforms to construct a knowledge graph related to environmental rights and interests assets, effective integration and semantic association of environmental rights and interests asset data from different sources are achieved, solving the problem of excessive data dispersion in asset management and eliminating information islands.

[0081] It should be noted that in the embodiment of the present application, after the knowledge graph is constructed, since policies are constantly improved and modified, and the production conditions of various enterprises are also constantly developing, the market prices of environmental rights assets may be affected by policy updates, supply and demand relationships, etc. and are volatile. Therefore, the knowledge graph used for asset management also needs to use new data from various platforms to achieve dynamic updates, ensure the accuracy of asset management, and enhance the adaptability of the knowledge graph.

[0082] Alternatively, the second data can be obtained from the reference platform. Semantic analysis can then be performed on the second data to obtain the second entities and the relationships between them. The second entities can then be matched with the first entities corresponding to each node in the knowledge graph to determine the reference nodes that match the second entities. The knowledge graph can then be updated based on the reference nodes, the second entities, and the relationships between them.

[0083] The second data is data associated with environmental equity assets in the reference platform and is different from the first data.

[0084] In an embodiment of the present application, after the data in the reference platform is updated, second data different from the first data used to construct the knowledge graph can be obtained, and the relationship between the second entity and the second entity can be extracted to complete the dynamic update of the knowledge graph.

[0085] In this application, when matching the second entity with the first entity corresponding to each node in the knowledge graph, not only can the node corresponding to the first entity be determined as the reference node when the second entity and the first entity are the same entity, but also the node corresponding to the first entity can be determined as the reference node when the second entity is an iteration of the first entity. For example, the policy of the second entity is a new policy obtained by revising the policy of the first entity, so the second entity is an iteration of the first entity, and the node corresponding to the first entity needs to be modified using the second entity when updating the knowledge graph.

[0086] In an embodiment of the present application, when the second entity extracted from the second data is the same entity as the first entity corresponding to a node in the current knowledge graph, there is no need to add a new node in the knowledge graph. Instead, the incremental update of the knowledge graph can be completed by adding new edges and associated nodes to the reference node corresponding to the successfully matched first entity based on other second entities associated with the second entity and the association relationship between the two.

[0087] It should be noted that in this application, the conditions for triggering the knowledge graph update can be set according to the needs of asset management in different scenarios, so as to ensure that the knowledge graph can be updated in a timely manner and control the update frequency of the knowledge graph.

[0088] Optionally, based on a preset update cycle, newly added information in the reference platform during the current update cycle may be obtained as the second data.

[0089] Among them, the preset update cycle can be set according to the policy update time, the monitoring frequency of the environmental monitoring agency, or the real-time requirements of asset management, etc. This application does not limit this.

[0090] Alternatively, when any reference platform receives a data update instruction, the data in the data update instruction may be used as the second data.

[0091] It should be noted that the second data may be a revision or abolition of the first data. Therefore, when the second data is used to update the knowledge graph, the association relationships corresponding to some nodes and edges in the original knowledge graph may become invalid. At this time, the attribute information of the nodes and edges needs to be modified or deleted.

[0092] Optionally, when a first entity corresponding to a reference node and a second entity matching the reference node have a preset relationship, the reference node can be modified using the second entity, and the attribute information of the edge connected to the reference node can be modified based on the association relationship between the second entity and other second entities.

[0093] The preset relationship refers to the revision or iteration of the first entity corresponding to the reference node with the second entity being the reference node.

[0094] In an embodiment of the present application, when a first entity corresponding to a reference node and a second entity matching the reference node have a preset relationship, the first entity represented by the reference node becomes invalid and needs to be updated to the second entity. For example, after a policy is revised, the revised policy content is used to update the node content corresponding to the original policy in the knowledge graph.

[0095] After the reference node is modified to a second entity, the relationship between the reference node and other nodes may have changed. Therefore, it is necessary to use the association relationship between the second entity and other second entities to modify the attribute information of the edge connected to the reference node. If the other second entities match the other nodes connected to the reference node, the corresponding association relationship can be used to directly modify the attribute information of the original edge. Alternatively, if the other second entities do not match any of the nodes connected to the reference node, a new node and edge can be created based on the associated other second entities and association relationships to complete the knowledge graph update.

[0096] Optionally, when the first entity corresponding to the reference node is the same as the second entity matched with the reference node, and the second data corresponding to the second entity is of a preset type, the reference node and the edge connecting the reference node may be deleted.

[0097] The preset type refers to the second data being the cancellation information of any first data.

[0098] In an embodiment of the present application, when the first entity corresponding to the reference node is the same as the second entity matched by the reference node, and the second data corresponding to the second entity is of a preset type, it can be said that the entity and association relationship extracted from the second data have become invalid and are meaningless for subsequent asset management evaluation and prediction. Therefore, in order to save resource space and reduce the timeliness and complexity of the knowledge graph, the reference node matching the second entity and the edge connecting the reference node can be deleted.

[0099] In this application, a visual interactive interface can also be used to display the knowledge graph, the evaluation results of the model output, and the generated management strategy, so that users can view detailed content as needed in the interface to optimize the user experience. Therefore, this embodiment provides another environmental equity asset management method based on the knowledge graph, such as Figure 4 As shown, Figure 4 A flowchart of another method for managing environmental rights and interests assets based on a knowledge graph provided in an embodiment of the present application.

[0100] like Figure 4 As shown, the environmental rights and interests asset management method based on the knowledge graph may include the following steps:

[0101] Step 401: Display third data on the user interface.

[0102] Among them, the third data may include at least one of a knowledge graph, an evaluation result, and an asset management strategy.

[0103] In an embodiment of the present application, after obtaining the knowledge graph, the evaluation results of the model output, or the generated management strategy, the data can be displayed in the user interface in the form of a chart, so that the user can not only obtain the information intuitively, but also support the user to interact with the displayed third data in the interface.

[0104] Step 402: When an operation instruction for the third data is received, specific content of the third data is displayed according to the operation instruction.

[0105] For example, when displaying a knowledge graph in the interface, users can click on the nodes and relationships in the graph, and the entity content corresponding to the node and the specific content of the relationship corresponding to the edge will be displayed in the interface to query asset details, market trends, optimization suggestions, etc.

[0106] In this embodiment, by displaying data in an interactive visualization interface, the knowledge graph, asset assessment results, and asset management strategies can be intuitively displayed, which is conducive to the user's efficient decision-making. In addition, based on the user's operations, the user can interact with charts such as the knowledge graph, making it easier for the user to quickly obtain information and optimize the user experience.

[0107] In an embodiment of the present application, the environmental rights asset management method based on the knowledge graph described in the above embodiment can be implemented by an asset management system provided by the present application, which can include a data acquisition module, a data processing and storage module, a knowledge graph construction module, an analysis and prediction module, an optimization management module and a result display module.

[0108] Among them, the data collection module is responsible for collecting environmental rights and interests asset-related data from multi-source data platforms; the data processing and storage module can clean, format and store the collected raw data to build an environmental rights and interests asset database; the knowledge graph construction module can generate a knowledge graph of environmental rights and interests assets based on the data in the database, and the knowledge graph includes node representation and relationship definition; the analysis and prediction module can realize semantic association analysis and dynamic asset evaluation and prediction based on the knowledge graph; the optimization management module can provide intelligent management suggestions and optimization solutions based on the analysis results; and the result display module can display management results in the form of charts and knowledge graphs to support user interactive operations.

[0109] In order to implement the above embodiments, the present application also proposes an asset management device based on knowledge graph.

[0110] Figure 5 A schematic structural diagram of a knowledge graph-based asset management device provided in an embodiment of the present application.

[0111] like Figure 5As shown, the knowledge graph-based asset management device 500 includes:

[0112] A determination module 501 is configured to determine, based on the first information of the target user, a first target node associated with the target user in a knowledge graph related to environmental equity assets;

[0113] An acquisition module 502 is configured to obtain environmental equity asset data associated with a target user based on the second target node connected to the first target node in the knowledge graph and the attribute information of the edge between the first target node and the second target node;

[0114] Evaluation module 503 is used to input the environmental equity asset data into the asset evaluation model to obtain the evaluation result output by the asset evaluation model for the target user's current environmental equity assets;

[0115] The policy module 504 is used to generate an asset management policy for the target user based on the evaluation results.

[0116] Furthermore, in a possible implementation of the embodiment of the present application, the determining module 501 may also be configured to:

[0117] Acquire first data in a reference platform, wherein the first data is data associated with environmental equity assets;

[0118] Performing semantic analysis on the first data to extract first entities and relationships between the first entities in the first data;

[0119] Taking the first entity as the node, according to the association relationship between the first entities, the edges between the nodes corresponding to the first entity are determined to construct a knowledge graph related to environmental equity assets.

[0120] Furthermore, in a possible implementation of the embodiment of the present application, the reference platform may include at least one of a carbon trading market, a policy database, and an environmental monitoring agency.

[0121] Furthermore, in a possible implementation of the embodiment of the present application, the determination module 501 may be specifically configured to:

[0122] According to the type of the association relationship between the two first entities, attribute information of the edge between the nodes corresponding to the two first entities is determined, and the attribute information is stored in the knowledge graph.

[0123] Furthermore, in a possible implementation of the embodiment of the present application, the determining module 501 may also be configured to:

[0124] Acquiring second data in the reference platform, wherein the second data is different from the first data;

[0125] Performing semantic analysis on the second data to obtain second entities and association relationships between the second entities;

[0126] Match the second entity with the first entity corresponding to each node in the knowledge graph, and determine a reference node that matches the second entity;

[0127] The knowledge graph is updated based on the reference node, the second entity, and the relationship between the second entities.

[0128] Furthermore, in a possible implementation of the embodiment of the present application, the determination module 501 may be specifically configured to:

[0129] Based on a preset update cycle, newly added information in the reference platform during the current update cycle is obtained as second data; or,

[0130] When any reference platform receives a data update instruction, the data in the data update instruction is used as the second data.

[0131] Furthermore, in a possible implementation of the embodiment of the present application, the determination module 501 may be specifically configured to:

[0132] In the case where a first entity corresponding to a reference node and a second entity matching the reference node are in a preset relationship, modifying the reference node using the second entity;

[0133] Based on the association relationship between the second entity and other second entities, the attribute information of the edge connected to the reference node is modified.

[0134] Furthermore, in a possible implementation of the embodiment of the present application, the determination module 501 may be specifically configured to:

[0135] When the first entity corresponding to the reference node is the same as the second entity matched with the reference node, and the second data corresponding to the second entity is of a preset type, the reference node and the edge connecting the reference node are deleted.

[0136] Furthermore, in a possible implementation of the embodiment of the present application, the knowledge graph-based asset management device 500 may further include:

[0137] a display module, configured to display third data on a user interface, wherein the third data includes at least one of a knowledge graph, an evaluation result, and an asset management strategy;

[0138] The processing module is configured to display specific content of the third data according to the operation instruction when an operation instruction for the third data is received.

[0139] It should be noted that the above explanation of the embodiment of the asset management method based on knowledge graph is also applicable to the asset management device based on knowledge graph of this embodiment, and will not be repeated here.

[0140] In the embodiments of the present application, by combining the knowledge graph and the asset valuation model, the value and risk of environmental rights and interests assets are dynamically evaluated and accurately predicted, which is conducive to improving the accuracy of asset management decisions and providing users with optimized management suggestions to improve the efficiency and benefits of asset management.

[0141] In order to implement the above embodiments, the present application also proposes an electronic device, comprising: a processor, and a memory communicatively connected to the processor; the memory stores computer-executable instructions; the processor executes the computer-executable instructions stored in the memory to implement the method provided by the above embodiments.

[0142] In order to implement the above embodiments, the present application also proposes a computer-readable storage medium, in which computer-executable instructions are stored. When the computer-executable instructions are executed by a processor, they are used to implement the methods provided by the above embodiments.

[0143] In order to implement the above embodiments, the present application also proposes a computer program product, including a computer program, which implements the methods provided by the above embodiments when executed by a processor.

[0144] The collection, storage, use, processing, transmission, provision and disclosure of user personal information involved in this application are in compliance with relevant laws and regulations and do not violate public order and good morals.

[0145] It is important to note that personal information collected from users should be used for legitimate and reasonable purposes and should not be shared or sold beyond these legitimate uses. Furthermore, such collection / sharing should be conducted only after receiving the user's informed consent, including but not limited to notifying the user to read the user agreement / user notice and sign an agreement / authorization that includes the relevant user information before using the feature. Furthermore, any necessary steps must be taken to safeguard and secure access to such personal information and ensure that others with access to personal information comply with its privacy policy and procedures.

[0146] This application contemplates providing implementations that allow users to selectively block the use or access of personal information data. Specifically, this disclosure contemplates providing hardware and / or software to prevent or block access to such personal information data. Risks can be minimized by limiting data collection and deleting data once it is no longer needed. Furthermore, where applicable, such personal information can be de-identified to protect user privacy.

[0147] In the descriptions of the foregoing embodiments, the reference terms "one embodiment", "some embodiments", "example", "specific example", or "some examples" mean that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present application. In this specification, the schematic expressions of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described may be combined in any one or more embodiments or examples in a suitable manner. In addition, those skilled in the art may combine and combine the different embodiments or examples described in this specification and the features of the different embodiments or examples, unless they are mutually inconsistent.

[0148] Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of the technical features being referred to. Thus, a feature defined as "first" or "second" may explicitly or implicitly include at least one of such features. Throughout the description of this application, "plurality" means at least two, for example, two, three, etc., unless otherwise specifically defined.

[0149] Any process or method description in a flowchart or otherwise described herein may be understood to represent a module, segment or portion of code comprising one or more executable instructions for implementing the steps of a custom logical function or process, and the scope of the preferred embodiments of the present application includes alternative implementations in which functions may be performed out of the order shown or discussed, including performing functions in a substantially simultaneous manner or in the reverse order depending on the functions involved, which should be understood by those skilled in the art to which the embodiments of the present application belong.

[0150] The logic and / or steps represented in the flowcharts or otherwise described herein, for example, can be considered as a sequenced list of executable instructions for implementing the logical functions, and can be embodied in any computer-readable medium for use by, or in conjunction with, an instruction execution system, apparatus, or device (e.g., a computer-based system, a system including a processor, or other system that can fetch and execute instructions from an instruction execution system, apparatus, or device). For purposes of this specification, a "computer-readable medium" can be any device that can contain, store, communicate, propagate, or transport a program for use by, or in conjunction with, an instruction execution system, apparatus, or device. More specific examples (a non-exhaustive list) of computer-readable media include the following: an electrical connection with one or more wires (electronic devices), a portable computer disk cartridge (magnetic device), random access memory (RAM), read-only memory (ROM), erasable and programmable read-only memory (EPROM or flash memory), fiber optic devices, and a portable compact disc read-only memory (CDROM). Furthermore, the computer-readable medium may even be paper or other suitable medium on which the program is printed, since the program may be obtained electronically, for example, by optically scanning the paper or other medium and then editing, interpreting or otherwise processing it in a suitable manner if necessary, and then storing it in a computer memory.

[0151] It should be understood that various parts of the present application can be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods can be implemented using software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if implemented using hardware, as in another embodiment, any one of the following technologies known in the art or a combination thereof can be used to implement: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application-specific integrated circuit having a suitable combination of logic gate circuits, a programmable gate array (PGA), a field programmable gate array (FPGA), etc.

[0152] Those skilled in the art will understand that all or part of the steps in the method of the above embodiment can be completed by instructing related hardware through a program, and the program can be stored in a computer-readable storage medium. When the program is executed, it includes one or a combination of the steps of the method embodiment.

[0153] In addition, the functional units in the various embodiments of the present application may be integrated into a processing module, or each unit may exist physically separately, or two or more units may be integrated into a module. The above-mentioned integrated module may be implemented in the form of hardware or in the form of a software functional module. If the integrated module is implemented in the form of a software functional module and sold or used as an independent product, it may also be stored in a computer-readable storage medium.

[0154] The storage medium mentioned above may be a read-only memory, a magnetic disk, or an optical disk, etc. Although the embodiments of the present application have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present application. Persons skilled in the art may make changes, modifications, substitutions, and variations to the above embodiments within the scope of the present application.

Claims

1. A method for managing environmental rights and interests assets based on knowledge graph, characterized in that: The following steps are involved: Determining, based on the first information of the target user, a first target node associated with the target user in a knowledge graph related to environmental equity assets; Obtaining environmental equity asset data associated with the target user based on the second target node connected to the first target node in the knowledge graph and attribute information of the edge between the first target node and the second target node; Inputting the environmental equity asset data into an asset evaluation model to obtain an evaluation result output by the asset evaluation model for the target user's current environmental equity assets; An asset management policy for the target user is generated based on the evaluation result.

2. The method according to claim 1, wherein Before determining, based on the first information of the target user, in a knowledge graph related to environmental equity assets, a first node associated with the target user, the method further includes: Acquire first data in a reference platform, wherein the first data is data associated with environmental equity assets; Performing semantic analysis on the first data to extract first entities in the first data and association relationships between the first entities; Taking the first entity as a node, based on the association relationship between the first entities, determine the edges between the nodes corresponding to the first entity to construct a knowledge graph related to environmental equity assets.

3. The method according to claim 2, wherein The reference platform includes at least one of a carbon trading market, a policy database, and an environmental monitoring agency.

4. The method according to claim 2, wherein The first entity is used as a node, and according to the association relationship between the first entities, edges between the nodes corresponding to the first entity are determined to construct a knowledge graph related to environmental equity assets, including: According to the type of the association relationship between the two first entities, attribute information of the edge between the nodes corresponding to the two first entities is determined, and the attribute information is stored in the knowledge graph.

5. The method according to claim 2, wherein After constructing the knowledge graph related to environmental equity assets, it also includes: Acquire second data in the reference platform, wherein the second data is different from the first data; Performing semantic analysis on the second data to obtain a second entity and an association relationship between the second entities; Matching the second entity with the first entity corresponding to each node in the knowledge graph, and determining a reference node matching the second entity; Based on the reference node, the second entity and the relationship between the second entities, the knowledge graph is updated.

6. The method according to claim 5, wherein The obtaining of the second data in the reference platform includes: Based on a preset update cycle, newly added information in the reference platform during the current update cycle is obtained as second data; or, When any of the reference platforms receives a data update instruction, the data in the data update instruction is used as the second data.

7. The method according to claim 5, wherein The updating of the knowledge graph based on the reference node, the second entity, and the association relationship between the second entities includes: When a first entity corresponding to a reference node and a second entity matching the reference node are in a preset relationship, modifying the reference node using the second entity; Based on the association relationship between the second entity and other second entities, the attribute information of the edge connected to the reference node is modified.

8. The method according to claim 5, wherein The updating of the knowledge graph based on the reference node, the second entity, and the association relationship between the second entities includes: When a first entity corresponding to the reference node is identical to a second entity matched with the reference node, and second data corresponding to the second entity is of a preset type, an edge connecting the reference node and the reference node is deleted.

9. The method according to any one of claims 1 to 8, wherein Also includes: Displaying third data on a user interface, wherein the third data includes at least one of the knowledge graph, the evaluation result, and the asset management strategy; When an operation instruction for the third data is received, specific content of the third data is displayed according to the operation instruction.

10. An asset management device based on knowledge graph, characterized in that: include: a determination module, configured to determine, based on the first information of the target user, a first target node associated with the target user in a knowledge graph related to environmental equity assets; An acquisition module, configured to obtain environmental equity asset data associated with the target user based on the second target node connected to the first target node in the knowledge graph and attribute information of the edge between the first target node and the second target node; An evaluation module, configured to input the environmental equity asset data into an asset evaluation model to obtain an evaluation result output by the asset evaluation model for the target user's current environmental equity assets; A policy module is used to generate an asset management policy for the target user based on the evaluation result.

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