Legal case similarity calculation method and system based on knowledge graph matching
A similarity calculation and knowledge graph technology, applied in computing, neural learning methods, biological neural network models, etc., can solve problems such as insufficient accuracy, lack of consideration for coordinating local matching and global matching, and inaccurate calculation results. easy-to-capture effects
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Embodiment 1
[0059] An embodiment of the present invention provides a method for calculating the similarity of legal cases based on knowledge map matching, including the following steps:
[0060] S1. Convert the entity and relationship information in the knowledge graph of the two cases into the initial vector through the text encoder:
[0061] The initial data used by the algorithm is a knowledge graph constructed based on triples (h, r, t) of the RDF model, where h is the head node, r is the relationship edge, and t is the tail node. The graph display samples of the source graph or the target graph are as follows image 3 Shown; The present invention adopts such as image 3 The knowledge map input in the judicial field shown, combined with the calculation method described in the present invention, makes it possible to finally obtain results close to those evaluated by experts in the field.
[0062] S11. Assign different ids to all entities and relationships in the knowledge graph, using...
Embodiment 2
[0110] An embodiment of the present invention provides a legal case similarity calculation system based on knowledge map matching, the system includes a text encoding module, a knowledge map embedding module, a matching score matrix calculation module, a matrix pooling module, and a graph similarity calculation module. The style encoding module is connected with the knowledge map embedding module and the matrix pooling module, the matching score matrix calculation module is connected with the knowledge map embedding module and the matrix pooling module, and the knowledge map embedding module is similar to the graph The degree calculation module is connected, and the matrix pooling module is connected with the graph similarity calculation module, wherein:
[0111] The text encoding module is used to convert the node attributes and relationships in the knowledge graph into fixed-length vector representations;
[0112] The knowledge map embedding module is used to aggregate the i...
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