67 results about "Graph data model" patented technology

The invention discloses a storage method and management system for high-association big data. The management system includes a storage module and a unified data management module; the storage module includes an Hashmap model for storing data entity contents, a relation model for storing data entity attributes, and a graph data model for storing association relations among data entities; each data entity sets an entity type and a unique ID number, and an association relation between an attribute and a content of the same data entity is established through the ID number of the data entity; and the unified data management module is used for performing adding, delete, update, and inquiry on association relations, attributes, data contents of data entities in the storage module. The storage method and management system for the high-association big data can store and manage big data sets, and can support high-efficiency association inquiry analysis.

The invention discloses an establishment method of enterprise knowledge map based on a graph model. The method comprises the following steps that model establishment step: a graph data model is built,the graph data model comprises a graph data structure module, a graph mining algorithm module and a query interface module; data record step: each dimension data of a sample enterprise is obtained, according to the graph data model, dimension data such as shareholders, external investment, public opinion, judicial and the like of the enterprise is recorded in the graph data structure module; encapsulation step: according to common application scenarios, the graph mining algorithm is encapsulated into the query interface module, and a relational graph model is returned in a JSON format. The invention further discloses a graphical query method based on the graph model.

The invention discloses an enterprise association relation topology establishing method based on a picture model. The establishing method comprises the following steps of model establishment, wherein a picture data model is constructed, a picture data structure of the picture data model comprises nodes, relations and attributes, the relations are used for describing association relations among the nodes, and the nodes and the relations have their own attributes respectively; data recording, wherein association relation data is obtained and is input into the picture data model; structure construction, wherein the picture data model establishes association among the nodes according to the relations to generate an association relation topology represented by the picture data model. The invention further discloses a graphical query method based on the graphical data model.

The invention provides a graph database-based power grid GIS modeling method and device. The modeling method comprises the following steps of establishing power grid equipment elements in a power grid GIS system and attribute information of the power grid equipment elements as vertex data according to a data mapping relationship table of topological source data of the power grid GIS system; establishing edge data according to connection relationships between the power grid equipment elements; and establishing a graph data model according to the vertex data and the edge data. Through implementing the modeling method and device, topological relationship management and query performance problems of the power grid GIS system are solved, a graph database-based power grid GIS system topological analysis application prototype system is completed, a novel data management tool and a rapid calculation analysis method are realized, and various requirements of power grid GIS system topological analysis application are supported.

In some embodiments, templates related to each graph data model of a graph data model set for converting non-graph data representations in a non-graph database to graph data representations compatible with a graph database may be obtained. One or more templates and the non-graph data representations may be provided to a neural network for the neural network to predict additional templates. The additional templates may be provided to the neural network as reference feedback for the neural network's prediction of the additional templates to train the neural network. A collection of non-graph data representations from a given non-graph database may be provided to the neural network for the neural network to generate one or more templates for a given graph data model for converting non-graph data representations in the given non-graph database into graph data representations compatible with a given graph database.

The invention discloses a graph data modeling system and method for power grid topology management. The method comprises steps of extracting characteristic attribute values of the power grid topologydata; judging the relevance between equipment by using a Pearson product moment correlation coefficient method to form topology association graphs, setting attributes of terminals and edges, forming afirst attribute structure topological graph, a second attribute structure topological graph and a third attribute structure topological graph; and filling service data information, connecting the equipment node information to form unit structures by combining the service priority levels to form unit frameworks with different priority levels, carrying out full-graph data communication on the extracted power grid graph logic model and topological structure by combining the three attribute structures, and mapping to form a power grid topology management graph data model. The modeling problem ofthe power grid topology data in the graph database is solved, the graph database technology is adopted for storing and analyzing the power grid topology data, the power grid topology data can be efficiently and rapidly stored in the graph database, and safe and stable operation of the power grid topology database is guaranteed.

The invention discloses a power-grid GIS topology analysis method based on a graph database and a storage medium. The power-grid GIS topology analysis method includes the steps that according to topological data of a power-grid GIS, a graph data model is generated; a topology-analysis basic model is constructed, wherein the topology-analysis basic model comprises a node searching model, an attribute querying model, a power-grid tracking model and a connectivity analysis model; according to the topology-analysis basic model, the topology-analysis algorithm is generated; according to the topology-analysis algorithm, the graph data model is subjected to topology analysis. The power-grid GIS topology analysis method is based on the graph database, the technology bottleneck problem of large-scale data topology analysis processing of a traditional database can be solved, and the efficiency of mass-data topology analysis is improved.

The invention discloses an alarm correlation analysis method based on a graph data model. The alarm correlation analysis method comprises the following steps: step 1, constructing the graph data model: converting a relational database model into the graph data model; Step 2,performing fault marking: when a network fault event or a user complaint event is received, marking a corresponding node inthe graph data model as a fault; Step 3, performing alarm pre-association: taking out the node with the lowest hierarchy from the graph data according to a fault time window, and storing the node in apre-association result set; Step 4, carrying out root alarm association judgment to determine a fault root source: in a pre-association result, when a further association relationship does not exist,determining the corresponding node as the fault root source; And when the further association relationship exists, the node involved in the association relationship is the fault source. According tothe method, the relation model is converted into the graph model, the processing efficiency is improved, the service request can be quickly responded, and the scene of real-time processing and analysis of the network data is effectively supported.

The invention relates to a user portrait construction method and system based on a graph database and a storage medium, and the method comprises the steps: obtaining user data, carrying out the recognition of the user data, and obtaining the multi-dimensional information of the user data; analyzing the plurality of pieces of dimension information, obtaining an association relationship among the dimension information, storing the dimension information and the association relationship into a graph database, and constructing a graph data model according to the association relationship; and receiving to-be-queried user data, and generating a user portrait analysis report according to the graph data model. The method depends on the storage and calculation capabilities of the graph database, establishes the association relationship in a mesh graph and text manner, and is visual, clear, high in user experience, easy to expand, simple in interaction, high in data processing capability, high inspeed, high in query efficiency of the association relationship of the to-be-queried user data and high in accuracy of the obtained user portrait analysis report.

In certain embodiments, data retrieval delays may be reduced via prediction-based generation of data subgraphs. In some embodiments, a data request may be predicted to occur in the future based on prior queries compatible with a graph data model. Based on the graph data model, one or more subgraphs representative of data subsets of a data set may be generated. For example, the data set may be data that the data request is predicted to seek, and the subgraphs may be generated in response to the data request prediction. The subgraphs may be stored in a temporary data storage. A subsequent data request matching the predicted data request may be obtained subsequent to the subgraph storage. Based on the subsequent data request matching the predicted data request, the subgraphs may be obtained from the temporary data storage. The subgraphs may be used to respond to the subsequent data request.

The invention provides a graph database based modeling method and device for a power information communication system. The modeling method comprises the steps of: acquiring attribute information of power information communication equipment and a power grid information system, and according to the attribute information, respectively establishing power information communication equipment nodes and power grid information system nodes; according to a connection relationship between each power information communication equipment, establishing a first edge structure for connecting each power information communication equipment node, and according to a subordination relationship of the power information communication equipment and the power grid information system, establishing a second edge structure for connecting the power information communication equipment nodes and the power grid information system nodes; and according to the power information communication equipment nodes, the power grid information system nodes, the first edge structure and the second edge structure, establishing a graph data model of the power communication equipment and the power grid information system.

The present invention discloses a method and an apparatus for recommending a suspicious component in problem diagnosis for a cloud application. In the method, firstly a graph data model representing a hierarchical structure of the cloud application is constructed, wherein the graph data model comprises an application node representing the cloud application, a plurality of component nodes representing a plurality of components of the cloud application, and inter-node lines indicating inter-node relationships. Then real-time information of the cloud application is obtained, in response to detecting performance degradation of the cloud application. Impact degrees of the plurality of component nodes on the performance degradation of the cloud application is obtained based on the constructed graph data model and the obtained real-time information, and a suspicious component sequence is generated according to the impact degrees of the plurality of component nodes.

The invention provides a method and device for analyzing the outage range of a power distribution network. The method comprises the steps of extracting a data column from topology source data according to a data dictionary in a pre-established graph data model, importing the data column into the graph data model, and building a graph database; retrieving in the graph database according to a presetsearch terminating condition, and sequentially performing wide-depth diffusion analysis; and determining the power failure range according to a result retrieved and returned in the graph database. The analysis device comprises a database unit, a retrieval unit and a result processing unit. The technical scheme provided by the invention retrieves based on the path of edges in a graph and analyzesthe influence area of a fault electrical component, thereby accurately and efficiently processing large-scale fault data of the power distribution network, and providing technical support for outage emergency repair and power distribution network management.

In certain embodiments, query-related resource usage in a data retrieval process may be reduced. In some embodiments, a graph query related to a data request may be obtained. The graph query may be transformed into a query set based on a graph data model and patterns of the graph query. Upon generation, the query set may include queries and query operators linking the queries, where the query operators include a first query operator linking first and second queries of the queries or other query operators. Prior to execution of the first and second queries, a satisfiability issue may be predicted, where the satisfiability issue is related to combining results derived from the first and second queries. Based on the prediction, the first query operator may be removed from the query set to update the query set. The updated query set may be executed to satisfy the graph query.

The present invention provides a database capable of integrated query processing and a data processing method thereof. The database capable of integrated query processing includes: a storage unit configured to store data including relational data, and graph data; a converter configured to convert a query language for a property graph data model for processing the graph data into a relational algebra that is a statement in an intermediate stage; and a controller configured to control the converter so as to convert the query language for the property graph data model in an input integrated query into a syntactic statement structure, and convert the query language for the property graph data model included in the query into the relational algebra, when the integrated query, in which the query language for the property graph data model and the relational query language are mixed, is input.

The embodiment of the invention provides a fault analysis method and apparatus of an electric power information communication system based on an image database. The fault analysis method comprises the following steps: obtaining attribute information of an electric power information communication device and a power grid information system, establishing an image data model of the electric power information communication system according to the attribute information; performing retrieval in the image data model, and performing breadth diffusion analysis according to a preset depth to determine a fault influence range. By implementation of the fault analysis method and apparatus, depth analysis is performed according to the retrieval in the image database, state monitoring of the electric power information communication device can be effectively processed, and the fault influence range is confirmed to provide auxiliary support for fault level evaluation and operation and maintenance object confirmation.

The present invention discloses a rich graph model RichGraph based graph data management method. In the graph data management method, an attribute graph data model where a node and a side element can both contain attribute information is proposed, and a Lucene full-text index search engine based bottom-layer implementation method for the data model is provided. The method disclosed by the present invention solves an inherent graph structure information restriction problem in data acquisition of a traditional relational database model, provides a reasonable expression model for complex data containing rich semantic information, and meanwhile improves graph data complex information management capability.

The invention discloses a method for realizing a mobile phone photographing function with a photographer composition awareness, in order to solve the technical problem that how to enable a mobile phone user without photographing composition knowledge and photographing experience and skills to take a picture with photographing composition like a photographer in the field of mobile phone AI (Artificial Intelligence) smart photographing. The method is characterized by completing a composition process which is performed by the photographer before photographing by automatically correcting a visioncenter of interest and a related area layout of a currently shot picture to match with a corresponding composition data model in a database. Through adoption of the method of the invention, when the mobile phone user without photographing composition knowledge aims a mobile phone at a scene picture which he wants to shot, the mobile phone can automatically perform composition and layout for the current picture like the photographer, so as to achieve a smart composition function of the current AI photographing mobile phone.

The invention provides a system and a method for writing data into a graph database based on NiFi. The system comprises a graph database, a data stream platform comprising a processing module and a plurality of data execution nodes, and a plurality of relational databases storing data tables. The modeling control platform in the graph database is configured to designate the data source informationof the data tables to be synchronized, and the graph data model corresponding to each data table to be synchronized is established. The processing module uses NiFi to call the interface of graph database to generate NiFi data flow including several SQL statements according to the data source information and executes the NiFi data flow to distribute the several SQL statements to each data execution node. The data execution node executes distributed SQL statements to load a data set to be synchronized obtained from its corresponding data table into a graph data model corresponding to the data table. Therefore, this scheme can write the data from the relational database into the graph database.

The invention discloses a method for rapidly making safeguard risk maps of water resources of China in batches on the basis of database drive. By drive of a basic geographic database, a thematic database and a cartographic coincidence library, thematic maps are updated in batches, including making of legend items, a data preparation process, preparation of thematic data, size and drawing range ofset graphs, expression and displaying of thematic data, map finishing and layout and map outputting. Correction and storage of map target object level are facilitated; data redundancy is reduced; batched updating and multi-expression of maps are facilitated; and meanwhile, a traditional GIS map expression ability is convenient to extend. Integrated management of an attribute database and a graphic database and automatic configuration of a thematic map making data model and drawing symbols are realized, the bottleneck of shortage of thematic symbols, troublesome data updating and the like in existing drawing is improved, and the method is a rapid and effective method for drawing safeguard risk maps of water resources of China in batches, and can provide reference for thematic drawing of development of the national economy of China and national defense construction.

An integrated circuit layout method directly extracts plural primitive objects from a user's existing layout to expedite a new layout for reuse and migration and to gain the benefits of full coverage and minimal cost of layout design. The integrated circuit layout method comprises the steps of capturing a set of design parameters from a user's existing layout; capturing a plurality of primitive objects from the user's existing layout; extracting at least one leaf device from the user's existing layout; defining at least one nested device based on the leaf device; setting compaction constraints for the nested device to form a basic layout; and performing a layout task based on the basic layout. In addition, an object-oriented layout data model, used in the aforesaid integrated circuit layout method, comprises a first set of fields storing layer usages of plural layers captured from a user's existing layout to define a primitive object, a second set of field storing a set of design parameters regarding the layers, and a third set of fields defining plural data types of the first and the second sets of fields.

The invention relates to a method for supporting structured and unstructured big data fusion. The method includes the steps: creating a multi-element big data fusion model supporting BLOB (binary large object) attribute values based on an attribute graph data model; generating N-element group data from received data by the multi-element big data fusion model supporting the BLOB attribute values; judging that the generated N-element group data are of a BLOB type and storing the BLOB type attribute values at a first preset position; fusing structured and unstructured big data at the first presetposition by controlling mapping between a handle and the data content of the corresponding BLOB type attribute value. The method provides a management model STRUNS for supporting structured and unstructured multi-element data fusion and an implementation system for the STRUNS. The method can be used for integrated management and uniform query of multi-element heterogeneous data including a text type, a Boolean type, a numeric type, a time type and the BLOB type, and a theoretical model and a practical system are provided for big data fusion management. The invention further relates to a device for supporting structured and unstructured big data fusion.

The invention provides an information system fault model construction method and system based on a graph database. The method comprises the steps of obtaining resource data of all resource objects inan information system; constructing a graph data model according to the resource data; when it is monitored that the abnormal information exists in the graph data model, extracting vertex informationand side information corresponding to the vertex generating the abnormal information from the graph data model within preset time; and establishing a fault model of the information system according tothe vertex information and the side information. According to the method and system, the characteristic that the graph database is a non-relational database which is simple, convenient and quick to inquire is utilized to establis a graph data model of the information system; the query time of the relationship between the resource objects can be greatly shortened through graphical design, so thatwhen abnormal information is monitored, the data query time is greatly shortened, the fault model can be accurately and quickly established to assist operation and maintenance personnel in processingsimilar faults, and the fault processing efficiency is improved.

The invention discloses a control data configuration method and a computer readable storage medium. The method comprises the steps of defining a view data model of a control, wherein the view data model comprises a field of control display data; presetting a field mapping relationship of a data source, wherein the field mapping relationship is a mapping relationship between the field in the view data model and a data field in the data source; and according to the field mapping relationship of the data source, obtaining data of the data field, corresponding to the field in the view data model, in the data source, and returning the data to a control. By separating display logic of the control from the data source, the difference of various different data sources is shielded, so that control development personnel concentrate on control implementation; and the control can be conveniently reused, so that a large amount of repeated development is reduced and the control development efficiency is greatly improved.

Provided is a process of validating data to be stored in a graph database, the process including: obtaining a first node to be stored in a graph database, the first node having a relationship to a second node corresponding to an edge; obtaining a node type of the first node having a respective node-type schema; forming a polymorphic schema, based on the node-type schema, specifying criteria to qualify as a valid instance of the node type; validating the first node with the polymorphic schema; and in response to validating the first node, storing the first node and the edge in the graph database.

In certain embodiments, resource usage in a data retrieval process may be reduced. In some embodiments, a graph query related to a data request may be obtained. The graph query may be transformed into a query set based on a graph data model and patterns of the graph query. Upon generation, the query set may include queries and query operators linking the queries, where the query operators include a first query operator linking first and second queries of the queries or other query operators. Prior to execution of the first and second queries, a satisfiability issue may be predicted, where the satisfiability issue is related to combining results derived from the first and second queries. Based on the prediction, the first query operator may be removed from the query set to update the query set. The updated query set may be executed to satisfy the graph query.

The invention discloses a medical data element automatic classification method and system based on depth map matching. A medical data element graph data model based on minimum metadata information is defined, and the effect of a depth map matching model is also suitable for the condition of local data marsh with extremely low metadata information; the purpose of completing automatic classification of data elements by using the least metadata information is achieved, and meanwhile it is guaranteed that graph structure data collected under the graph data model standard is suitable for training of a depth graph matching model; vector representation of medical data elements is calculated based on a representation learning method, and effective data elements possibly mapped to a standard data model are quickly and automatically screened through classification of the vector representation; and vector representation of column vertexes is calculated based on a graph attention mechanism, and a depth map matching model is constructed to complete automatic classification of medical data elements. The method and the system have good expansibility, and can be applied to processing of various data marsh-to-data lake conversion problems.

The invention provides a graph data modeling electric power fingerprint identification method of electrical equipment, a storage medium and a system. The method comprises the steps of detecting an input event of the electrical equipment at a power utilization bus in real time, and extracting a plurality of electrical operation features of the input electrical equipment, establishing an association relationship between every two electrical operation characteristics according to a mutual information entropy theory, taking the extracted electrical operation characteristics as nodes, taking an association relationship between every two electrical operation characteristics as edges, and generating electric fingerprint graph data containing the nodes and the edges according to a graph theory, and performing graph representation learning on the electric power fingerprint graph data by using a graph convolutional network, and constructing a mapping relationship between the electric power fingerprint graph data and the electrical equipment to realize load identification. The mapping relation does not need to be determined through a large amount of calculation in the load identification process, and the electrical operation characteristics of the electrical equipment can be directly obtained based on the electric fingerprint graph data, so that the non-intrusive load identification algorithm is simple, the identification speed is high, and the operation efficiency is high.

The invention belongs to the technical field of Internet of Vehicles roadsides, and discloses an Internet of Vehicles roadside unit deployment method based on a genetic ant colony hybrid algorithm, which comprises the following steps: a data acquisition module acquires trajectory data and map data of a vehicle; the model construction module generates a grid chart based on the acquired map data andestablishes a road network model; the parameter setting module sets deployment parameters; the data calculation module uses a genetic ant colony hybrid algorithm to calculate a deployment scheme of the minimum deployment number and the optimal deployment position under the condition of meeting the parameter requirements based on the set deployment parameters; the storage module is used for storing corresponding data by utilizing a database; and the display module displays the vehicle trajectory data, the generated grid chart and the final deployment scheme. According to the invention, the road network model is constructed, and the deployment scheme is determined by using the Internet of Vehicles road side unit deployment method based on the genetic ant colony hybrid algorithm, so that thevehicle coverage rate can be improved, the RSU deployment quantity can be reduced, and the deployment cost can be reduced.