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A semantic extraction method of express logistics service based on knowledge graph

A technology of knowledge graph and extraction method, applied in the field of semantic extraction of express logistics service based on knowledge graph, can solve the problems of lack of efficiency, ignoring the mining of user historical features, etc., and achieve the effect of highlighting substantive features

Active Publication Date: 2022-07-12
HARBIN INST OF TECH
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0004] In addition, ignoring the mining of user historical characteristics
A typical feature of the service field is "priority", that is, the historical records formed by using services in the past imply the rules of using services in the future. At present, few logistics companies mine the hidden personal characteristics in user history records. Always provide services to users from the starting point when the demand arrives, lacking sufficient efficiency

Method used

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  • A semantic extraction method of express logistics service based on knowledge graph
  • A semantic extraction method of express logistics service based on knowledge graph
  • A semantic extraction method of express logistics service based on knowledge graph

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Embodiment Construction

[0087] The present invention will be described in detail below with reference to the accompanying drawings and specific examples. The following examples are to explain the present invention, but the present invention is not limited to the following embodiments.

[0088] like Figure 1-4 As shown, a method for semantic extraction of express logistics services based on knowledge graph provided by this embodiment includes the following steps:

[0089] S1: the step of performing entity recognition processing on the demand statement input by the user;

[0090] S2: the step of converting and splicing the sentence after entity recognition;

[0091] S3: The step of semantically interpreting the converted and spliced ​​sentences according to the knowledge map in the field of express logistics;

[0092] S4: the step of constructing a user preference model for express logistics services;

[0093] S5: The step of recommending personalized logistics services to users.

[0094] The step...

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Abstract

The present invention relates to a method for extracting express logistics service semantics based on a knowledge graph, comprising the following steps: S1: a step of performing entity recognition processing on a demand statement input by a user; S2: a step of performing conversion and splicing processing on the entity-recognized statement; S3: The step of semantically interpreting the converted and spliced ​​sentences according to the knowledge graph in the field of express logistics; S4: The step of building a user preference model for express logistics services; S5: The step of recommending personalized logistics services to users.

Description

technical field [0001] The invention belongs to the field of express logistics service search, in particular to a method for extracting express logistics service semantics based on a knowledge graph. Background technique [0002] The express logistics industry has developed rapidly with the rise of e-commerce, and at the same time, there have been some difficult problems to solve. For example, traditional logistics companies provide users with templated input methods, but in reality, user needs have obvious personalities. With the characteristics of customization and change, the personalized needs of users cover many aspects such as functions and QoS. In traditional logistics services, it is assumed that the services required and provided by users are clear, but this assumption is in most scenarios. is not established. [0003] The needs reflected by users through templated input are often macroscopic and vague, and logistics companies can only obtain these needs, while use...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F16/36G06F40/30G06F40/289G06F16/9535
CPCG06F16/367G06F40/30G06F40/289G06F16/9535
Inventor 孟凡超郑璇池孙山鑫
Owner HARBIN INST OF TECH