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A search path method for knowledge graph based on deep learning

A technology of search path and knowledge map, applied in the field of knowledge map, can solve the problems of too many search paths and inaccuracy, and achieve the effect of comprehensive search, enhanced credibility and high reliability

Active Publication Date: 2021-07-09
SHANGHAI SQUIRREL CLASSROOM ARTIFICIAL INTELLIGENCE TECH CO LTD
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

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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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  • A search path method for knowledge graph based on deep learning
  • A search path method for knowledge graph based on deep learning
  • A search path method for knowledge graph 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. like 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 more ...

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Abstract

The invention discloses a deep learning-based knowledge map search path method, which is used to solve the problem of too many and inaccurate search paths retrieved by the existing knowledge map search path acquisition method. The method includes: obtaining keywords input by the user; obtaining multiple search paths according to the keywords in the constructed knowledge map; calculating the length of each search path according to a preset path length algorithm; The length of each search path and the preset reliability algorithm are calculated to obtain the reliability of each search path; the search path with the highest reliability is provided to the user as the default search path. In this method, the length and reliability of each search path are calculated, and then the search path with the highest reliability is provided to the user as a default search path, thereby achieving the purpose of improving user experience.

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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Patent Type & Authority Patents(China)
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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