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72 results about "Relational structure" patented technology

Relational structure. (data structure) Definition: The counterpart in formal logic of a data structure or class instance in the object-oriented sense. Examples are strings, directed graphs, and undirected graphs. Sets of relational structures generalize the notion of languages as sets of strings.

Model and modeling method of multi-dimensional data integration of heterogeneous databases of electric power information system

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.
Owner:NR ELECTRIC CO LTD +1

Cross-language knowledge graph entity alignment method based on GCN twinning network

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.
Owner:UNIV OF ELECTRONICS SCI & TECH OF CHINA

Knowledge graph construction method and system for multi-source Chinese financial announcement document

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.
Owner:ZHEJIANG UNIV OF TECH

A knowledge map representation learning method based on entity and relational structure information

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.
Owner:GUILIN UNIV OF ELECTRONIC TECH
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