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Model training method, triplet embedding method, device, medium and equipment

A training method and technology of triplets, applied in the field of machine learning, can solve the problems that the accuracy of triplet embedding processing needs to be improved, and achieve the effect of improving the accuracy of expression and accuracy

Active Publication Date: 2022-04-01
南京医渡云医学技术有限公司 +1
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Problems solved by technology

[0004] However, in the knowledge map embedding method provided by related technologies, the accuracy of triple embedding processing needs to be improved

Method used

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  • Model training method, triplet embedding method, device, medium and equipment
  • Model training method, triplet embedding method, device, medium and equipment
  • Model training method, triplet embedding method, device, medium and equipment

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Embodiment Construction

[0063] An example embodiment will now be described more fully with reference to the accompanying drawings. However, the example embodiments can be implemented in a variety of forms, and should not be construed as being limited to the examples set forth herein; in contrast, the present disclosure will make the present disclosure more comprehensive and complete, and to comprehensively convey the concept of an example embodiment A technician to those skilled in the art.

[0064] Moreover, the features, structures, or characteristics described may be incorporated in one or more embodiments in any suitable manner. In the following description, there is provided a number of specific details to give sufficient understanding of the embodiments of the present disclosure. However, those skilled in the art will appreciate that there may be one or more of the present disclosure without one or more of a particular detail, or other methods, components, devices, steps, and the like can be employ...

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Abstract

The disclosure provides a triplet embedding model training method, triplet embedding, device, computer readable medium and electronic equipment, and relates to the technical field of machine learning. The training method of the embedding model of this triple includes: obtaining N groups of training samples, wherein, each group of training samples includes: the probability that the knowledge expressed by the triple and the triple is established, and N is an integer greater than 1; The triplets in the i group of training samples are input into the embedding model, and the projection distance S is obtained according to the output of the embedding model i , where i is a positive integer less than or equal to N; according to the probability P of the i-th group of training samples i and projection distance S i Determine the loss function of the embedding model to train the embedding model based on the loss function. The technical solution includes probability information in the amount of information after triplet embedding processing, which is conducive to improving the accuracy of expression of medical knowledge points and the accuracy of triplet embedding processing.

Description

Technical field [0001] The present disclosure relates to the field of machine learning, and in particular, there is a training method and apparatus for embedded models of a triple set, a three-component embedding method and a device, computer readable medium, and electronic device. Background technique [0002] Knowledge Graph, Remote, Knowledge Base, referred to as Knowledge Base, referred to as: KB), is a graph structure (GRAPH) structure of knowledge by "entity" and "relationship". KGEMBedding refers to the "entity" and "relationship" in the knowledge map, indicating the vector or low dimensional vector, and can be calculated instead of the symbol reasoning with a vector calculation in the reasoning application based on the knowledge map. That is, it is made more suitable for the preferences based on knowledge maps. [0003] In the relevant technique, the embedded label model of the three-tune in the knowledge map is regarded as a second classification model: the knowledge poi...

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/36
CPCG06F16/36
Inventor 王尧李林峰
Owner 南京医渡云医学技术有限公司
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