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Express logistics service semantic extraction method based on knowledge graph

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

Active Publication Date: 2021-04-30
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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  • Express logistics service semantic extraction method based on knowledge graph
  • Express logistics service semantic extraction method based on knowledge graph
  • Express logistics service semantic extraction method based on knowledge graph

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Embodiment Construction

[0090] The present invention is described in detail below in conjunction with accompanying drawing and by specific embodiment, and following embodiment is explanation of the present invention, and the present invention is not limited to following embodiment.

[0091] Such as Figure 1-4 As shown, a method for extracting semantics of express logistics services based on knowledge graphs provided in this embodiment includes the following steps:

[0092] S1: a step of performing entity recognition processing on the demand statement input by the user;

[0093] S2: a step of converting and concatenating the sentence after the entity recognition;

[0094] S3: According to the knowledge map in the field of express logistics, the step of semantically interpreting the sentences after conversion and splicing;

[0095] S4: the step of constructing the express logistics service user preference model;

[0096] S5: Steps of recommending personalized logistics services to users.

[0097] Th...

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Abstract

The invention relates to an express logistics service semantic extraction method based on a knowledge graph. The express logistics service semantic extraction method comprises the following steps of S1, performing entity identification processing on a demand statement input by a user; s2, converting and splicing the statements subjected to entity recognition; s3, according to the knowledge graph of the express logistics field, carrying out semantic interpretation on the statements obtained after conversion and splicing processing; s4, constructing an express logistics service user preference model; and S5, recommending personalized logistics service to the user.

Description

technical field [0001] The invention belongs to the field of express logistics service search, in particular to a method for extracting semantics of express logistics services based on knowledge graphs. Background technique [0002] The express logistics industry has developed rapidly with the rise of e-commerce. At the same time, some difficult problems have emerged. For example, traditional logistics companies provide users with templated input methods, but in reality, user needs have obvious individuality The characteristics of individualization and multiple changes, the personalized needs of users cover many aspects such as functions, QoS, etc., while traditional logistics services assume that the services required and provided by users are clear, but this assumption is not valid in most scenarios is not established. [0003] The needs expressed by users through templated input are often macroscopic and vague, and logistics companies can only obtain these needs, while i...

Claims

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Application Information

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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