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Knowledge graph path searching method based on deep learning

A search path and knowledge map technology, applied in the field of knowledge map, can solve problems such as inaccuracy and too many search paths

Active Publication Date: 2020-12-01
SHANGHAI SQUIRREL CLASSROOM ARTIFICIAL INTELLIGENCE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0003] The present invention provides a knowledge map search path method based on deep learning, which is used to solve the problem of too many and inaccurate search paths retrieved by the existing knowledge map search path acquisition method

Method used

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  • Knowledge graph path searching method based on deep learning
  • Knowledge graph path searching method based on deep learning
  • Knowledge graph path searching method based on deep learning

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Embodiment Construction

[0028] The preferred embodiments of the present invention will be described below in conjunction with the accompanying drawings. It should be understood that the preferred embodiments described here are only used to illustrate and explain the present invention, and are not intended to limit the present invention.

[0029] figure 1 It is a flow chart of Embodiment 1 of a deep learning-based knowledge map search path method in an embodiment of the present invention. Such as figure 1 As shown, the method includes the following steps S101-S105:

[0030] S101: Obtain keywords input by the user;

[0031] In this embodiment, there are many ways to acquire the keywords input by the user, and the keywords input by the user may be acquired through the input box of the knowledge map search engine.

[0032] S102: Obtain multiple search paths according to the keywords in the constructed knowledge graph;

[0033] In this embodiment, the search path can be obtained by using any one or mo...

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PUM

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Abstract

The invention discloses a knowledge graph search path method based on deep learning. The method is used for solving the problems that search paths retrieved by an existing knowledge graph search pathobtaining method are too many and inaccurate. The method comprises the steps of obtaining a keyword input by a user; acquiring a plurality of search paths according to the keywords in a constructed knowledge graph; calculating the length of each search path according to a preset path length algorithm; calculating the reliability of each search path according to the length of each search path and apreset reliability algorithm; and providing the search path with the highest reliability as a default search path for the user. According to the method, the length and the reliability of each searchpath are calculated, and then the search path with the highest reliability is provided for the user as the default search path, so that the purpose of improving the user experience is achieved.

Description

technical field [0001] The present invention relates to the technical field of knowledge graphs, in particular to a deep learning-based search path method for knowledge graphs. Background technique [0002] With the rapid development of theories and methods in applied mathematics, graphics, information visualization technology, information science and other disciplines, the number of knowledge graphs is also increasing explosively, and the correlation between knowledge graphs is also increasing. In the process of knowledge map search, search engines often use keyword direct search, semantic search, contextual search, etc. to display the searched knowledge map to users, but often the displayed knowledge map is too many and not what users need. Users have a very poor experience. In order to improve the user experience, the current search engine uses the keyword input by the user to generate a search path, and the user can use this search path to quickly obtain the desired kno...

Claims

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Application Information

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IPC IPC(8): G06F16/36G06F16/33G06F16/332
CPCG06F16/3329G06F16/3334G06F16/3344G06F16/367
Inventor 王鑫
Owner SHANGHAI SQUIRREL CLASSROOM ARTIFICIAL INTELLIGENCE TECH CO LTD
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