72 results about "Relational structure" patented technology

The invention relates to a model and modeling method of the multi-dimensional data integration of heterogeneous databases of an electric power information system. The modeling method comprises the following steps of: (a) establishing a basic container hierarchical structure, predefining a template for each container, i.e. standardizing the problem of loading objects during the actualization of the containers according to the type of the containers, classifying the abstract containers into a plurality of types, and modeling by utilizing the container templates and the hierarchical relational structure thereof; (b) establishing a uniform and standardized common naming method for managing heterogeneous object models of the electric power information system so that a private object of each data source can be reduced to a same common object; (c) loading the common object to private object mapping relationship, establishing common object information, private object information of the heterogeneous databases and the mapping relationship of the common object information and the private object information of the heterogeneous databases through XML (Extensive Makeup Language) description files which are derived by the data sources and contain common names, and loading the objects and the mapping relationship thereof into a hierarchical container model established in the step (a). The invention reduces the complexity and the cost of the data integration without secondary development and maintenance.

The invention relates to a lightweight BIM big data online visualization method and system. The method includes the following steps that lightweight analysis based on semantic guidance is conducted on a BIM scenario component set to obtain a lightweight component base; the interior structure of a BIM building is automatically partitioned to generate multiple relatively independent spaces and a relation structure chart of the relatively independent spaces; a multilayer data index structure with multi-granularity decomposition is established according to the relation structure chart and the component set in each space; the lightweight component base is called according to the multilayer data index structure to achieve progressive visualization of the BIM building, and in the visualization process, with each space as the unit, data in the next space relative to the current space is cached and data in the last space is deleted. Compared with the prior art, the method and system have the advantages of automation, lightweight, fine granularity and the like.

The invention discloses a cross-language knowledge graph entity alignment method based on a GCN twinning network. The method comprises the steps: firstly respectively extracting an adjacent matrix andan attribute information matrix for knowledge graphs of two languages, enabling the known alignment entity pairs of the knowledge graphs of the two languages to serve as positive samples, and forminga positive sample set; respectively constructing a GCN twin network for the relationship structure information and the attribute information, respectively recording the relationship structure information and the attribute information as GCN _ SE and GCN _ AE, and training the GCN twin network GCN _ SE by taking adjacent matrixes of the two knowledge maps as inputs of the GCN twin network GCN _ SE; taking the adjacency matrix and the attribute information matrix of the two knowledge maps as the input of a GCN twin network GCN _ AE, and training the GCN twin network GCN _ AE; and obtaining a potential alignment entity result based on the trained GCN twin network. According to the method, only relation structure information and attribute information between entities in the multi-language knowledge graph and part of aligned entities are needed as a training set, and multiple potential aligned entity pairs can be inferred at the same time without acquiring extra entity feature data.

Visualization frameworks may include solvers. The solvers may be used to determine the properties of view components of view compositions. In some instances, the solvers may be explicitly composed using a relational structure, such as a dependency tree. In some instances, the solvers may be implicitly composed based on property-setters having solvers invoking other property-setters having solvers.

A relational database access system and method provides a new data representation and a query technique which allows information system end users to access (query) relational databases without knowing the relational structure or the structure query language (SQL). The present invention utilizes semantically dynamic objects.

The knowledge graph construction method for the multi-source Chinese financial announcement document comprises the following steps: structuring the hierarchical relationship of each chapter of the document, and constructing a relatively complete document structure tree; labeling all the title data; unifying the length of the title to a preset word number, and carrying out word embedding coding at a character level by using BERT to obtain a corresponding vector representation; dividing the processed data set into a training set and a test set, and training to obtain a title classification model; classifying the document titles by using a title classification model; the complex and effective knowledge of the effective text blocks is masked; constructing a semantic model with a mask, constructing a multi-source similar generalization mask Bi-LSTM semantic model (M-MST model), and feeding the M-MST model for training to obtain a knowledge extraction model; according to the knowledge extraction model, combining with an external knowledge base to obtain an entity relationship triple; and constructing a multi-source financial announcement document knowledge graph and realizing incremental updating or expansion. The invention further discloses a system for implementing the knowledge graph construction method for the multi-source Chinese financial announcement document.

Translation architecture that facilitates translation between schema data and relational structures. The architecture includes a translation component that consumes schema data ( e . g ., an XML schema) that includes a schema structure, validates the schema structure, and persists in memory a representation of the schema as a relational format. Since schemas are shredded into tables, instance validation loads only the necessary components to perform validation. During validation, only parts of the schema that are used are loaded and cached. A schema cache stores the in-memory representation of schema optimized for instance validation. Schema components are loaded from metadata into main memory as read-only objects such that multiple users can use the in-memory objects for validation, query processing, query optimization and storage optimization of XML instance data .

A computing device including a file system in memory is provided. The file system has a plurality of items. Each item can be one of a file or a folder. Where an item is a file, it has a unique content. Where an item is a folder, it is represented by a plurality of container structures. Each container structure references items in the file system through the use of references such as pointers. Each item can be contained by more than one folder by being referenced by more than one folder. Each item can also include a contained-by structure including references to folders containing that item. Moreover, each item can include relationship structures allowing the items to be organized in accordance with relationships other than contained-by relationships, such as content derivation relationships. The file system can be manipulated through the use of various operations such as “Archive” and “Restore” operations.

The invention provides a security mechanism with combination of a secure channel switching strategy and a curtain-style digital signature scheme, which aims at guaranteeing the security of a single-transceiver time-slot type cognitive radio C-MAC (Cognitive-Multiple Access Control) protocol and preventing possible channel preemptive-type denial of service attack. The method comprises the following steps of: carrying out random sequencing and encrypting by utilizing an available channel list so that malicious nodes can not monitor channel consultation information between communicating parties, thereby avoiding the malicious nodes from seizing channels; and secondly, establishing a signature scheme with a curtain-type relational structure by adopting two hash functions to solve the problem that the correlation of a plurality of signature process needs to be guaranteed when a cognitive ratio network adopts digital signatures. The invention guarantees the suspensive communication caused by withdrawing a master user before the cognitive ratio C-MAC protocol can be accessed into an idle channel to continuously communicate under the situation of suffering from denial of service attack.

The invention provides a node-tree-based engineering supervision task processing method and device. Nodes and leaves of a node tree are set engineering supervision tasks, and data of the nodes and theleaves and relational structures of the data are stored in a data file; the method comprises the steps that current progress of engineering supervision is obtained, and associated nodes of the node tree is sought in the data file according to the current progress; all nodes belonging to the associated nodes in the node tree form a to-do task list, and data containing the to-do task list is pushedto associated users through a network; when the associated users receive the to-do task list, related engineers are assigned to tasks in the to-do task list, and data containing the tasks is pushed to the related engineers corresponding to the tasks through the network; when the related engineers receive the data containing the tasks, the tasks are executed, and task results are collected. According to the method and device, the technical effects of optimizing engineering supervision task processing and achieving irreversibility and traceability of data archiving can be achieved.

Providing a broadcast system wherein storage of contents on the receiving side and use restriction on the stored contents, etc. can be performed per service provided by contents providers. In a storage-based digital broadcast system wherein contents transmitted from a sending side are stored on a receiving side then reproduced, the sending side transmits service structure information for describing relational structure between services provided by contents providers and reference information for associating the contents with the service structure information in advance, and the receiving side receives and stores service structure information and reference information and uses the received service structure information and reference information to manage storage of contents. It is possible to control contents per service based on service structure information and information that can be reorganized from reference information.

The invention relates to a knowledge graph construction method and system based on a manufacturing field. The method comprises the steps of acquiring description statements of the machining process ofthe manufacturing field; performing statement splitting and semantic analysis on the description statement of the manufacturing field processing process based on a pre-established knowledge dictionary to extract corresponding words; performing automatic matching according to the knowledge dictionary to classify the words; querying the knowledge dictionary, and replacing the classified words to obtain standard words corresponding to the classified words in the knowledge dictionary; generating a triple relation structure according to the standard words; obtaining structured data of a knowledgegraph of a to-be-constructed manufacturing field according to the triple relation structure, wherein the structured data comprises a plurality of entity names; and updating the structured data according to the reference entity names corresponding to the plurality of entity names to obtain a knowledge graph of the manufacturing field. The knowledge graph in the manufacturing field constructed by the method is high in accuracy.

The invention provides a knowledge map representation learning method based on entity and relationship structure information, the method comprising the following steps: acquiring structural semantic information of the entity and structural semantic information of the relationship in the knowledge map; according to the structural semantic information of the entity and the structural semantic information of the relationship, constructing an entity target vector and a target relation vector; constructing a score function according to the entity target vector and the target relation vector; constructing a loss function according to the score function, and learning an optimal vector representation of an entity and a relationship by minimizing the loss function. The present invention makes fulluse of structural information around entities and relationships to enrich and constrain the representation of entities and relationships. The method effectively enhances the expression ability of theentity and the relationship, constructs a new objective function, better expresses the entity and the relationship, and preserves the relationship between the entity and the relationship, so that themethod can be well applied to the large-scale knowledge map complement.

A messaging server (112) provides a message store (116) for storing messages in a relational manner. A set of related messages, such as an email string between two or more people, is represented as a message container (200) having relational references to one or more submessages (210, 212, 214). The messaging server (112) processes non-relational messages sent by the server by inserting (516) tags that uniquely identify components within the message. The messaging server (112) also processes tagged or untagged non-relational messages received by the server to create (616, 618) relational counterparts in the message store (116). Relational searches can be executed on the messages in the message store (116) to perform audits or forensic analyses of the messages.