Basin information data architecture construction method and device, computer equipment and product

Abstract

The invention relates to the technical field of watershed information management, and discloses a watershed information data architecture construction method and device, computer equipment and a product, and the method comprises the steps: obtaining multi-source watershed data, and constructing a watershed data gravity model based on the multi-source watershed data; dividing a watershed data domain and a data topic based on the watershed data gravity model, and generating a watershed information data asset directory; and numbering and storing the drainage basin information data asset catalog to generate a drainage basin information data architecture. According to the method, the availability and storage retrieval efficiency of the multi-source watershed data are improved, the watershed data quality and the decision quality of watershed cascade scheduling and the like are greatly improved, the operation efficiency of power generation shipping and the like is optimized, and the data circulation is enhanced.

Description

Technical Field

[0001] The present invention relates to the technical field of watershed information management, and in particular to a method, device, computer equipment and product for constructing a watershed information data architecture. Background Art

[0002] The watershed information model can provide a design basis for estimating the outflow process of the watershed, calculating the river flood process, building small and medium-sized reservoirs, developing irrigation canals, and establishing hydropower stations of different sizes. It can also provide useful data for urban water supply, shipping and transportation, and provide decision support for flood control and water diversion.

[0003] The watershed information model includes various types of watershed information and their relationships, including data in various forms, types and scales, which leads to low availability of watershed data and difficulty in ensuring the quality of watershed data, thereby reducing the analysis and decision-making quality of the watershed information model. Summary of the invention

[0004] In view of this, the present invention provides a method, device, computer equipment and product for constructing a watershed information data architecture to solve the problem of low availability of watershed data and difficulty in ensuring the quality of watershed data.

[0005] In a first aspect, the present invention provides a method for constructing a watershed information data architecture, the method comprising: Obtain multi-source watershed data and build a watershed data gravity model based on the multi-source watershed data; Divide the basin data domains and data themes based on the basin data gravity model, and generate a basin information data asset catalog; The watershed information data asset directory is numbered and stored to generate the watershed information data architecture.

[0006] The present embodiment provides a method for constructing a watershed information data architecture, which constructs a watershed data gravity model based on multi-source watershed data, divides watershed data domains and data themes based on the watershed data gravity model, and generates a watershed information data asset directory; the watershed information data asset directory is numbered and stored to generate a watershed information data architecture; wherein, the watershed data gravity model is constructed according to the multi-modality and other characteristics of the watershed data, and then the watershed data gravity model is used to form a watershed data asset directory and storage management, and the watershed information data architecture is constructed, which improves the availability and storage and retrieval efficiency of multi-source watershed data, greatly improves the watershed data quality and the decision-making quality of watershed cascade scheduling, optimizes the operational efficiency of power generation and shipping, and enhances data liquidity.

[0007] In an optional implementation, constructing a watershed data gravity model based on multi-source watershed data includes: Perform multimodal named entity recognition on multi-source watershed data to obtain entities and entity occurrence counts; Determine the interaction forces between entities based on the entities and the number of entity occurrences; The interaction forces between entities are used to associate entities and generate a gravity model of watershed data.

[0008] This embodiment provides a method for constructing a watershed information data architecture, which determines the interaction force between entities through entities and the number of entity occurrences, associates entities using the interaction force between entities, and generates a watershed data gravity model. The watershed data gravity model is generated based on the multimodal characteristics of watershed data, and the gravity of watershed information data is defined, laying the foundation for the subsequent formation of a watershed information data asset directory and numbered storage.

[0009] In an optional implementation, basin data domains and data themes are divided based on the basin data gravity model to generate a basin information data asset directory, including: Construct a data gravity graph based on the watershed data gravity model and calculate the attraction capacity of the vertices in the data gravity graph; Divide the data themes based on the attraction ability of the vertices, and obtain the data theme names corresponding to the divided data themes; Get the subject classification name and calculate the edit distance between the data subject name and the subject classification name; The watershed data domains corresponding to the data subject names are aggregated based on the edit distance to obtain the watershed information data asset directory.

[0010] This embodiment provides a method for constructing a watershed information data architecture. It constructs a data gravity graph through a watershed data gravity model, transforms the watershed data structured organization problem into a graph node contribution problem, and then divides data themes and watershed data domains by the attraction capabilities of vertices in the data gravity graph, establishes a watershed information data asset directory, solves the watershed data standardization and structured organization problems, realizes accurate division and clustering of data themes and watershed data domains, improves data availability, and provides a standard data organization architecture.

[0011] In an optional implementation, constructing a data gravity graph based on the watershed data gravity model and calculating the attraction capacity of vertices in the data gravity graph include: The entities in the watershed data gravity model are taken as vertices, the connecting routes between entities are taken as edges, and the weights of the edges are determined based on the interaction forces between entities. The data gravity graph is constructed based on the vertices, edges and edge weights respectively. The degree of the vertex, the number of vertex occurrences and the gravity of the vertex connection path are determined based on the data gravity graph, and the attraction ability of the vertex is calculated based on the degree of the vertex, the number of vertex occurrences and the gravity of the vertex connection path.

[0012] This embodiment provides a method for constructing a watershed information data architecture, which constructs a data gravity graph through a watershed data gravity model, and then calculates the attraction capacity of vertices in the data gravity graph, providing a basis for the subsequent division of data themes and watershed data domains.

[0013] In an optional implementation, data themes are divided based on the attraction capabilities of vertices to obtain data theme names corresponding to the divided data themes, including: Determine the division ratio based on the attraction ability of the vertices, and determine the division core vertex based on the division ratio; Obtaining the connection relationship between other vertices and the partition core vertex, and partitioning the data subject based on the connection relationship between other vertices and the partition core vertex; Perform keyword recognition on the entities corresponding to the divided data topics to obtain the data topic names.

[0014] This embodiment provides a method for constructing a watershed information data architecture, which determines the core vertices for division through the attraction capabilities of the vertices, and then divides the data topics using the connection relationships between other vertices and the core vertices for division, thereby achieving accurate division of watershed information data corresponding to different data topics, as well as multi-source data integration, fusion and structured organization of the watershed information data.

[0015] In an optional implementation, the watershed information data asset directory is numbered and stored to generate a watershed information data architecture, including: Define the entity nodes corresponding to the watershed information data asset directory, number the entity nodes, and add labels to the entity nodes based on the numbers; Determine the storage management information of the watershed information data asset directory using the graph database; The watershed information data architecture is constructed based on the labeled watershed information data asset directory and storage management information.

[0016] The present embodiment provides a method for constructing a watershed information data architecture, which implements standard data organization and storage by numbering and labeling the watershed information data asset directory and applying a graph database for storage management, thereby improving storage and retrieval efficiency. By constructing a watershed information data architecture, it further supports watershed data sharing, data analysis, and data research, which will greatly improve the quality of watershed data, the quality of decision-making such as watershed cascade scheduling, optimize operational efficiency such as power generation and shipping, and enhance data liquidity.

[0017] In a second aspect, the present invention provides a device for constructing a watershed information data architecture, the device comprising: A construction module is used to obtain multi-source watershed data and construct a watershed data gravity model based on the multi-source watershed data; A partitioning module is used to partition watershed data domains and data themes based on the watershed data gravity model and generate a watershed information data asset catalog; The numbered storage module is used to store the watershed information data asset directory by number and generate the watershed information data architecture.

[0018] In a third aspect, the present invention provides a computer device, comprising: a memory and a processor, the memory and the processor are communicatively connected to each other, computer instructions are stored in the memory, and the processor executes the method for constructing a watershed information data architecture according to the first aspect or any corresponding embodiment thereof by executing the computer instructions.

[0019] In a fourth aspect, the present invention provides a computer-readable storage medium having computer instructions stored thereon, the computer instructions being used to enable a computer to execute the method for constructing a watershed information data architecture according to the first aspect or any corresponding embodiment thereof.

[0020] In a fifth aspect, the present invention provides a computer program product, comprising computer instructions for causing a computer to execute the method for constructing a watershed information data architecture according to the first aspect or any corresponding embodiment thereof. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 is a flow chart of a method for constructing a watershed information data architecture according to an embodiment of the present invention; Figure 2 is a flow chart of another method for constructing a watershed information data architecture according to an embodiment of the present invention; Figure 3 is a schematic diagram of the structure of a data gravity graph according to an embodiment of the present invention; Figure 4 is a schematic diagram of a watershed information data asset directory according to an embodiment of the present invention; Figure 5 is a flow chart of another method for constructing a watershed information data architecture according to an embodiment of the present invention; Figure 6 is a structural block diagram of a device for constructing a watershed information data architecture according to an embodiment of the present invention; Figure 7It is a schematic diagram of the hardware structure of a computer device according to an embodiment of the present invention. DETAILED DESCRIPTION

[0023] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution in the embodiments of the present invention will be clearly and completely described below in conjunction with the drawings in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0024] The embodiment of the present invention provides a method for constructing a watershed information data architecture, which generates a watershed data gravity model based on the characteristics of watershed data such as multimodality, forms a watershed information data asset directory and numbered storage based on the gravity model undirected graph, and constructs a watershed information data architecture; wherein, according to the characteristics of watershed data such as multimodality, a data gravity theory is proposed, a watershed data gravity model is constructed, a watershed data asset directory is formed based on the data gravity model, and graph data is used for numbered storage to construct a watershed information data architecture, which provides standardized data organization and storage, improves data availability and storage retrieval efficiency, greatly improves watershed data quality, decision-making quality such as watershed cascade scheduling, optimizes operational efficiency such as power generation and shipping, and enhances data liquidity.

[0025] The embodiment of the present invention provides a method for constructing a watershed information data architecture. It should be noted that the method for constructing a watershed information data architecture provided by the embodiment of the present invention may be executed by a device for constructing a watershed information data architecture. The device for constructing a watershed information data architecture may be implemented as part or all of an electronic device through software, hardware, or a combination of software and hardware. The electronic device may be a server or a terminal. The server in the embodiment of the present application may be a single server or a server cluster composed of multiple servers. The terminal in the embodiment of the present application may be a smart phone, a personal computer, a tablet computer, a wearable device, an intelligent robot, or other intelligent hardware devices. In the following method embodiments, the execution subject is an electronic device as an example for explanation.

[0026] According to an embodiment of the present invention, an embodiment of a method for constructing a watershed information data architecture is provided. It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although a logical order is shown in the flowchart, in some cases, the steps shown or described can be executed in an order different from that shown here.

[0027] In this embodiment, a method for constructing a watershed information data architecture is provided, which can be used in the above-mentioned electronic device. Figure 1is a flow chart of a method for constructing a watershed information data architecture according to an embodiment of the present invention. Figure 1 As shown, the process includes the following steps: Step S101, acquiring multi-source watershed data, and constructing a watershed data gravity model based on the multi-source watershed data.

[0028] Specifically, multi-source watershed data includes structured data, in which data is collected and recorded through sensors. The collected and recorded data includes 3D models, as well as unstructured data and semi-structured data such as text, tables, emails, pictures, audio, video, web pages, etc.

[0029] Furthermore, according to the multimodal characteristics of watershed data, a data gravity theory is proposed and a watershed data gravity model is constructed.

[0030] Step S102, dividing the watershed data domains and data themes based on the watershed data gravity model, and generating a watershed information data asset directory.

[0031] Specifically, basin data domains and data themes are divided based on subject division standards to form a basin information data asset catalog.

[0032] Step S103, numbering and storing the watershed information data asset directory to generate a watershed information data architecture.

[0033] Specifically, based on the watershed information data asset directory, each node is numbered and labeled, and a graph database is used for storage.

[0034] The present embodiment provides a method for constructing a watershed information data architecture, which constructs a watershed data gravity model based on multi-source watershed data, divides watershed data domains and data themes based on the watershed data gravity model, and generates a watershed information data asset directory; the watershed information data asset directory is numbered and stored to generate a watershed information data architecture; wherein, the watershed data gravity model is constructed according to the multi-modality and other characteristics of the watershed data, and then the watershed data gravity model is used to form a watershed data asset directory and storage management, and the watershed information data architecture is constructed, which improves the availability and storage and retrieval efficiency of multi-source watershed data, greatly improves the watershed data quality and the decision-making quality of watershed cascade scheduling, optimizes the operational efficiency of power generation and shipping, and enhances data liquidity.

[0035] In this embodiment, a method for constructing a watershed information data architecture is provided, which can be used in the above-mentioned electronic device. Figure 2 is a flow chart of a method for constructing a watershed information data architecture according to an embodiment of the present invention. Figure 2 As shown, the process includes the following steps: Step S201, acquiring multi-source watershed data, and constructing a watershed data gravity model based on the multi-source watershed data.

[0036] Specifically, the above step S201 includes: Step S2011, perform multimodal named entity recognition on multi-source basin data to obtain entities and entity occurrence counts.

[0037] Specifically, the Multimodal Named Entity Recognition (MNER) method is used to identify entities in multi-source watershed data. The type of multi-source watershed data is used as the attribute of the entity, and the number of occurrences of each entity and the number of times two entities appear at the same time are counted.

[0038] Step S2012, determining the interaction force between entities based on the entities and the number of entity occurrences.

[0039] Specifically, suppose entity n appears the number of times , the number of times entity n and entity p appear together is , define the interaction force between two directly associated entities as , and its calculation formula is as follows: (1) in, Representing Entities Number of occurrences, Representing Entities Number of occurrences, Representing Entities and entities Number of co-occurrences.

[0040] Furthermore, the interaction force between two entities that are not directly associated (limited to the case where the two entities can be associated through an intermediate entity) is defined as , and its calculation formula is as follows: ( ) (2) Where b is the intermediate node between entities a and c. If entity a has multiple branches connected to entity c, the gravitational force between entity a and entity c is the sum of the gravitational forces of all paths that do not exceed 3.

[0041] Step S2013, using the interaction forces between entities to associate entities and generate a watershed data gravity model.

[0042] Specifically, the watershed data gravity model is defined as: entities are connected to each other through gravity interaction to form mutually related model bodies. There can be multiple gravity watershed data gravity models.

[0043] Step S202, dividing the watershed data domains and data themes based on the watershed data gravity model, and generating a watershed information data asset directory.

[0044] Specifically, the above step S202 includes: Step S2021, constructing a data gravity graph based on the watershed data gravity model, and calculating the attraction capacity of the vertices in the data gravity graph.

[0045] In some optional implementations, the above step S2021 includes: Step a1: take the entities in the watershed data gravity model as vertices, the connection routes between entities as edges, determine the weights of the edges based on the interaction forces between entities, and construct a data gravity graph based on vertices, edges and edge weights.

[0046] Specifically, Figure 3 As shown in the figure, each entity in the watershed data gravity model is taken as a vertex, an edge is connected between entities with a gravitational relationship, and the sum of the gravity of the connected route is used as the weight of the edge to construct multiple weighted undirected graphs, which are called data gravity graphs G.

[0047] Step a2, determining the vertex degree, vertex occurrence times and the gravity of the vertex connection path based on the data gravity graph, and calculating the attraction ability of the vertex based on the vertex degree, vertex occurrence times and the gravity of the vertex connection path.

[0048] Specifically, for each data gravity graph G, the attraction capacity of each vertex is calculated, and the calculation formula is as follows: (3) in, represents the attraction ability of vertex n, Represents the gravitational force (or interaction force) of the connected path of vertex n, where the connected path is a path with no more than 3 entities. represents the degree of vertex n, Represents the sum of the occurrences of vertex n.

[0049] Step S2022, dividing the data themes based on the attraction capabilities of the vertices, and obtaining data theme names corresponding to the divided data themes.

[0050] In some optional implementations, the above step S2022 includes: Step b1, determining the division ratio based on the attraction ability of the vertices, and determining the division core vertices based on the division ratio.

[0051] Specifically, the attraction capabilities of all vertices are counted, and the division ratio q is set. q is generally less than 0.2. The vertices are sorted from large to small according to their attraction capabilities, and the top q vertices are used as the core vertices for division.

[0052] Step b2, obtaining the connection relationship between other vertices and the partition core vertex, and partitioning the data subject based on the connection relationship between other vertices and the partition core vertex.

[0053] Specifically, other vertices (i.e., the remaining vertices in the data gravity graph except the partition core vertex) have the following situations: 1) If it is directly connected to one of the partition core vertices and not directly connected to other partition core vertices, the data topics corresponding to other partition core vertices will be divided into the data topic of this partition core vertex.

[0054] 2) If it is directly connected to one of the partition core vertices and directly connected to other partition core vertices, the gravity value from the partition core vertex to the connected partition core vertex is calculated, and the data topics corresponding to other partition core vertices are divided into the data topics corresponding to the maximum gravity value.

[0055] 3) For vertices that are not directly connected to the core vertices, calculate the paths from directly connected vertices to each core vertex and divide them into data topics corresponding to the shortest path.

[0056] Step b3, perform keyword recognition on the entities corresponding to the divided data topics to obtain the data topic names.

[0057] Step S2023, obtain the subject classification name, and calculate the edit distance between the data subject name and the subject classification name.

[0058] Specifically, the subject classification name can adopt the second-level and third-level subject classification names in the subject classification standard, and calculate the edit distances ds and dt between the data subject name and the second-level and third-level subject classification names.

[0059] Step S2024, based on the edit distance, aggregate the watershed data domains corresponding to the data subject names to obtain the watershed information data asset directory.

[0060] Specifically, if dt of a data subject name is less than or equal to 2, ds is used as the data domain of the data subject name.

[0061] Furthermore, if Figure 4 As shown in the figure, the watershed information data asset directory is divided into three levels, including L1 data domain (i.e., watershed data domain), L2 data subject and L3 conceptual entity, among which the integrated logical entity and corresponding attributes (including files, documents, audio, video materials of multimodal data, etc.) are L3 layer conceptual entities.

[0062] Step S203: Number and store the watershed information data asset directory to generate the watershed information data architecture. Figure 1 Step S103 of the illustrated embodiment will not be described in detail here.

[0063] The present embodiment provides a method for constructing a watershed information data architecture, which determines the interaction force between entities through entities and the number of entity occurrences, associates entities using the interaction force between entities, generates a watershed data gravity model, generates a watershed data gravity model based on the multimodality and other characteristics of watershed data, defines the gravity of watershed information data, and lays a foundation for the subsequent formation of a watershed information data asset directory and numbered storage; secondly, constructs a data gravity graph through the watershed data gravity model, transforms the watershed data structured organization problem into a graph node contribution problem, and then divides data themes and watershed data domains through the attraction capabilities of vertices in the data gravity graph, establishes a watershed information data asset directory, solves the watershed data standardization and structured organization problems, realizes accurate division and clustering of data themes and watershed data domains, improves data availability, and provides a standard data organization architecture.

[0064] In this embodiment, a method for constructing a watershed information data architecture is provided, which can be used in the above-mentioned electronic device. Figure 5 is a flow chart of a method for constructing a watershed information data architecture according to an embodiment of the present invention. Figure 5 As shown, the process includes the following steps: Step S501, obtain multi-source watershed data, and build a watershed data gravity model based on the multi-source watershed data. Figure 2 Step S201 of the illustrated embodiment will not be described in detail here.

[0065] Step S502: divide the watershed data domains and data themes based on the watershed data gravity model, and generate a watershed information data asset directory. Figure 2 Step S202 of the illustrated embodiment will not be described in detail here.

[0066] Step S503, numbering and storing the watershed information data asset directory to generate a watershed information data architecture.

[0067] Specifically, the above step S503 includes: Step S5031, define the entity nodes corresponding to the watershed information data asset directory, number the entity nodes, and add labels to the entity nodes based on the numbers.

[0068] Specifically, the conceptual entities in the watershed information data asset catalog are represented as entity nodes, the gravitational forces between entities are represented as edges, and attributes are added to each entity node.

[0069] Furthermore, each level and entity node in the basin information data asset directory are numbered separately. The number of each conceptual entity is: "data domain number-data subject number-concept entity number-logical entity number", and the numbers of the remaining levels are the parent node numbers of the entity node layer by layer until the node itself is numbered, and then the numbers are used as labels for each entity node to improve the efficiency of subsequent queries.

[0070] Step S5032, using the graph database to determine the storage management information of the watershed information data asset directory.

[0071] Specifically, graph databases (such as Neo4j, ArangoDB, Amazon Neptune, etc.) are used to store watershed data.

[0072] Step S5033, constructing the watershed information data architecture based on the labeled watershed information data asset directory and storage management information.

[0073] The present embodiment provides a method for constructing a watershed information data architecture, which implements standard data organization and storage by numbering and labeling the watershed information data asset directory and applying a graph database for storage management, thereby improving storage and retrieval efficiency. By constructing a watershed information data architecture, it further supports watershed data sharing, data analysis, and data research, which will greatly improve the quality of watershed data, the quality of decision-making such as watershed cascade scheduling, optimize operational efficiency such as power generation and shipping, and enhance data liquidity.

[0074] In this embodiment, a watershed information data architecture construction device is also provided, which is used to implement the above-mentioned embodiments and preferred implementation modes, and the descriptions that have been made will not be repeated. As used below, the term "module" can implement a combination of software and / or hardware of a predetermined function. Although the devices described in the following embodiments are preferably implemented in software, the implementation of hardware, or a combination of software and hardware, is also possible and conceivable.

[0075] This embodiment provides a device for constructing a watershed information data architecture. Figure 6 As shown, including: A construction module 601 is used to obtain multi-source watershed data and construct a watershed data gravity model based on the multi-source watershed data; A division module 602 is used to divide the watershed data domains and data themes based on the watershed data gravity model to generate a watershed information data asset directory; The number storage module 603 is used to store the watershed information data asset directory by number and generate the watershed information data architecture.

[0076] In some optional implementations, the building block 601 includes: The recognition unit is used to perform multimodal named entity recognition on multi-source watershed data to obtain entities and entity occurrence counts; A first determining unit, configured to determine the interaction force between entities based on the entities and the number of entity occurrences; The generation unit is used to associate entities using the interaction forces between entities and generate a gravity model of watershed data.

[0077] In some optional implementations, the partitioning module 602 includes: A first calculation unit is used to construct a data gravity graph based on the watershed data gravity model and calculate the attraction capacity of vertices in the data gravity graph; A partitioning unit, used for partitioning the data topics based on the attraction ability of the vertices, and obtaining data topic names corresponding to the partitioned data topics; The second calculation unit is used to obtain the subject classification name and calculate the edit distance between the data subject name and the subject classification name; The aggregation unit is used to aggregate the watershed data domains corresponding to the data subject names based on the edit distance to obtain the watershed information data asset directory.

[0078] In some optional implementations, the first computing unit includes: Constructing subunits, which are used to take entities in the watershed data gravity model as vertices, take the connecting routes between entities as edges, determine the weights of the edges based on the interaction forces between the entities, and construct data gravity graphs based on vertices, edges and edge weights respectively; The calculation subunit is used to determine the degree of the vertex, the number of vertex occurrences and the gravity of the vertex connection path based on the data gravity graph, and calculate the attraction ability of the vertex based on the degree of the vertex, the number of vertex occurrences and the gravity of the vertex connection path.

[0079] In some optional implementations, the dividing unit includes: Determine a subunit, which is used to determine a division ratio based on the attraction ability of the vertices, and determine a division core vertex based on the division ratio; A partitioning subunit is used to obtain the connection relationship between other vertices and the partitioning core vertex, and partition the data subject based on the connection relationship between other vertices and the partitioning core vertex; The identification subunit is used to perform keyword identification on the entities corresponding to the divided data topics to obtain the data topic names.

[0080] In some optional implementations, the serial number storage module 603 includes: A definition unit is used to define entity nodes corresponding to the watershed information data asset directory, number the entity nodes, and add labels to the entity nodes based on the numbers; A second determination unit is used to determine storage management information of a watershed information data asset directory using a graph database; A construction unit is used to construct a watershed information data architecture based on the watershed information data asset directory and storage management information after adding tags.

[0081] The further functional description of each of the above modules and units is the same as that of the above corresponding embodiments and will not be repeated here.

[0082] In this embodiment, a watershed information data architecture construction device is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and memory that executes one or more software or fixed programs, and / or other devices that can provide the above functions.

[0083] The embodiment of the present invention also provides a computer device having the above Figure 6 A device for constructing a watershed information data architecture is shown.

[0084] See also Figure 7 , Figure 7 is a schematic diagram of the structure of a computer device provided by an optional embodiment of the present invention, such as Figure 7 As shown, the computer device includes: one or more processors 10, a memory 20, and interfaces for connecting various components, including high-speed interfaces and low-speed interfaces. Various components are connected to each other using different buses for communication, and can be installed on a common mainboard or installed in other ways as needed. The processor can process instructions executed in the computer device, including instructions stored in or on the memory to display the graphical information of the GUI on an external input / output device (such as a display device coupled to the interface). In some optional embodiments, if necessary, multiple processors and / or multiple buses can be used together with multiple memories. Similarly, multiple computer devices can be connected, and each device provides some necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). Figure 7 A processor 10 is taken as an example.

[0085] The processor 10 may be a central processing unit, a network processor or a combination thereof. The processor 10 may further include a hardware chip. The hardware chip may be a dedicated integrated circuit, a programmable logic device or a combination thereof. The programmable logic device may be a complex programmable logic device, a field programmable gate array, a general purpose array logic or any combination thereof.

[0086] The memory 20 stores instructions executable by at least one processor 10, so that the at least one processor 10 executes the method shown in the above embodiment.

[0087] The memory 20 may include a program storage area and a data storage area, wherein the program storage area may store an operating system, an application required for at least one function; the data storage area may store data created according to the use of the computer device, etc. In addition, the memory 20 may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some optional embodiments, the memory 20 may optionally include a memory remotely arranged relative to the processor 10, and these remote memories may be connected to the computer device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0088] The memory 20 may include a volatile memory, such as a random access memory; the memory may also include a non-volatile memory, such as a flash memory, a hard disk or a solid state drive; the memory 20 may also include a combination of the above types of memory.

[0089] The computer device also includes an input device 30 and an output device 40. The processor 10, the memory 20, the input device 30 and the output device 40 may be connected via a bus or other means. Figure 7 The example of connecting through bus is taken in the following.

[0090] The input device 30 can receive input digital or character information, and generate key signal input related to the user settings and function control of the computer device, such as a touch screen, a keypad, a mouse, a track pad, a touch pad, an indicator bar, one or more mouse buttons, a trackball, a joystick, etc. The output device 40 may include a display device, an auxiliary lighting device (e.g., an LED) and a tactile feedback device (e.g., a vibration motor), etc. The above-mentioned display device includes but is not limited to a liquid crystal display, a light emitting diode, a display and a plasma display. In some optional embodiments, the display device may be a touch screen.

[0091] The embodiment of the present invention also provides a computer-readable storage medium. The method according to the embodiment of the present invention can be implemented in hardware, firmware, or can be implemented as a computer code that can be recorded in a storage medium, or can be implemented as a computer code that is originally stored in a remote storage medium or a non-temporary machine-readable storage medium and will be stored in a local storage medium through a network download, so that the method described herein can be stored in such software processing on a storage medium using a general-purpose computer, a dedicated processor, or programmable or dedicated hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only storage memory, a random access memory, a flash memory, a hard disk or a solid-state hard disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that a computer, a processor, a microprocessor controller, or programmable hardware includes a storage component that can store or receive software or computer code. When the software or computer code is accessed and executed by a computer, a processor, or hardware, the method shown in the above embodiment is implemented.

[0092] A part of the present invention may be applied as a computer program product, such as a computer program instruction, which, when executed by a computer, can call or provide the method and / or technical solution according to the present invention through the operation of the computer. Those skilled in the art should understand that the existence of the computer program instruction in a computer-readable medium includes, but is not limited to, a source file, an executable file, an installation package file, etc., and accordingly, the way in which the computer program instruction is executed by the computer includes, but is not limited to: the computer directly executes the instruction, or the computer compiles the instruction and then executes the corresponding compiled program, or the computer reads and executes the instruction, or the computer reads and installs the instruction and then executes the corresponding installed program. Here, the computer-readable medium may be any available computer-readable storage medium or communication medium accessible to the computer.

[0093] Although the embodiments of the present invention have been described in conjunction with the accompanying drawings, those skilled in the art may make various modifications and variations without departing from the spirit and scope of the present invention, and such modifications and variations are all within the scope defined by the appended claims.

Claims

1. A method for constructing a watershed information data architecture, characterized in that: The method comprises: Acquire multi-source watershed data, and construct a watershed data gravity model based on the multi-source watershed data; Divide the watershed data domains and data themes based on the watershed data gravity model, and generate a watershed information data asset catalog; The watershed information data asset directory is numbered and stored to generate a watershed information data architecture.

2. The method according to claim 1, characterized in that: The constructing of a watershed data gravity model based on the multi-source watershed data includes: Performing multimodal named entity recognition on the multi-source watershed data to obtain entities and entity occurrence counts; determining an interaction force between entities based on the entities and the number of occurrences of the entities; The entities are associated by utilizing the interaction forces between the entities to generate the watershed data gravity model.

3. The method according to claim 2, characterized in that The dividing of the watershed data domains and data themes based on the watershed data gravity model to generate a watershed information data asset directory includes: Constructing a data gravity graph based on the watershed data gravity model, and calculating the attraction capacity of vertices in the data gravity graph; Dividing the data topics based on the attraction capabilities of the vertices to obtain data topic names corresponding to the divided data topics; Obtain a subject classification name, and calculate the edit distance between the data subject name and the subject classification name; The watershed data domains corresponding to the data subject names are aggregated based on the edit distance to obtain the watershed information data asset directory.

4. The method according to claim 3, characterized in that: The step of constructing a data gravity graph based on the watershed data gravity model and calculating the attraction capacity of vertices in the data gravity graph includes: The entities in the watershed data gravity model are taken as vertices, the connection routes between the entities are taken as edges, and the weights of the edges are determined based on the interaction forces between the entities, and the data gravity graph is constructed based on the vertices, the edges and the weights of the edges respectively; The degree of the vertex, the number of vertex occurrences and the gravity of the vertex connection path are determined based on the data gravity graph, and the attraction ability of the vertex is calculated based on the degree of the vertex, the number of vertex occurrences and the gravity of the vertex connection path.

5. The method according to claim 3, characterized in that: The dividing of the data topics based on the attraction ability of the vertices to obtain data topic names corresponding to the divided data topics includes: Determine a division ratio based on the attraction ability of the vertices, and determine a division core vertex based on the division ratio; Acquire the connection relationship between other vertices and the partition core vertex, and partition the data subject based on the connection relationship between the other vertices and the partition core vertex; Keyword recognition is performed on entities corresponding to the divided data topics to obtain the data topic names.

6. The method according to claim 1, characterized in that The method of storing the watershed information data asset directory by numbers to generate a watershed information data architecture includes: Define the entity nodes corresponding to the watershed information data asset directory, number the entity nodes, and add labels to the entity nodes based on the numbers; Determining storage management information of the watershed information data asset directory using a graph database; The watershed information data architecture is constructed based on the labeled watershed information data asset directory and the storage management information.

7. A device for constructing a watershed information data architecture, characterized in that: The device comprises: A construction module, used for acquiring multi-source watershed data and constructing a watershed data gravity model based on the multi-source watershed data; A division module, used to divide the watershed data domains and data themes based on the watershed data gravity model, and generate a watershed information data asset directory; The number storage module is used to store the watershed information data asset directory by number and generate a watershed information data architecture.

8. A computer device, characterized in that: include: A memory and a processor, wherein the memory and the processor are communicatively connected to each other, the memory stores computer instructions, and the processor executes the method for constructing a watershed information data architecture according to any one of claims 1 to 6 by executing the computer instructions.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer instructions, and the computer instructions are used to enable a computer to execute the method for constructing a watershed information data architecture according to any one of claims 1 to 6.

10. A computer program product, characterized in that It includes computer instructions, and the computer instructions are used to enable a computer to execute the watershed information data architecture construction method described in any one of claims 1 to 6.

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