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Method, device, medium, equipment and system for optimizing edge weights in knowledge map

A knowledge map and weight technology, applied in the field of knowledge map optimization, can solve problems such as low quality, errors or statistical errors of edge weight knowledge maps

Active Publication Date: 2018-11-09
EAST CHINA NORMAL UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, these methods are easily affected by errors in the source data itself or statistical errors, resulting in poor accuracy of edge weights and poor quality of knowledge graphs.

Method used

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  • Method, device, medium, equipment and system for optimizing edge weights in knowledge map
  • Method, device, medium, equipment and system for optimizing edge weights in knowledge map
  • Method, device, medium, equipment and system for optimizing edge weights in knowledge map

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Embodiment Construction

[0063] In the following description, many technical details are proposed in order to enable readers to better understand the application. However, those skilled in the art can understand that without these technical details and various changes and modifications based on the following implementation modes, the technical solution claimed in each claim of the present application can be realized.

[0064] In order to make the purpose, technical solution and advantages of the present invention clearer, the following will further describe the implementation of the present invention in detail in conjunction with the accompanying drawings.

[0065] figure 1 It is a schematic structural diagram of an edge weight optimization device in a knowledge graph according to an embodiment of the present invention. The edge weight optimization device 100 includes a knowledge graph definition module 101, a query information receiving module 102, a candidate answer pushing module 103, a feedback in...

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Abstract

The invention relates to a method for optimizing edge weights in a knowledge map, comprising the following steps: defining the knowledge map, wherein the knowledge map comprises nodes, directed edgesamong the nodes and the original edge weights of the directed edges; receiving query information from a user; searching candidate answers corresponding to the query information, sorting the candidateanswers by utilizing the knowledge map, and pushing to the user; receiving feedback information on the sorted candidate answers from the user; constructing a signomial geometric programming problem, wherein a constraint function of the signomial geometric programming problem is set based on the feedback information, and a target function of the signomial geometric programming problem is an edge weight optimizing function; and solving the signomial geometric programming problem to obtain the optimized edge weights. The method provided by the invention converts an edge weight optimization problem of the knowledge map into one signomial geometric programming problem by utilizing the feedback information of the user and can efficiently and automatically improve accuracy of the edge weights andquality of the knowledge map. The invention also relates to a device, a medium, equipment and a system for optimizing the edge weights in the knowledge map.

Description

technical field [0001] The present invention relates to the field of knowledge map optimization, in particular to a method, device, medium, equipment and system for optimizing edge weights in a knowledge map. Background technique [0002] In modern society, knowledge graphs have been widely used in various applications, such as question answering (Q&A) systems, recommender systems, web search engines, and precision medicine, etc. For example, computing the similarity between questions and help documents based on knowledge graphs has been proven to be an effective way to find the best document answers. [0003] In the knowledge graph, an edge represents the association information between two entity nodes, and the strength of the association is usually represented by the weight of the edge. Edge weight information can show high value in knowledge graph applications. For example, in a technical support question answering system application, if the problem of "computer crash"...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
Inventor 杨燕杨瑞达贺樑
Owner EAST CHINA NORMAL UNIV
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