Semantic recognition method and system based on knowledge graph

A knowledge graph, semantic recognition technology, applied in the field of natural language processing, can solve problems such as the inability to support natural language semantic recognition

Active Publication Date: 2017-05-31
张永成 +1
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  • Description
  • Claims
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AI Technical Summary

Problems solved by technology

[0005] The purpose of the present invention is to provide a semantic recognition method and system based on knowledge graphs to solve the problem that the technical solutions for semantic recognition in the prior art cannot support the semantic recognition of natural language that is not associated with the semantic recognition model

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  • Semantic recognition method and system based on knowledge graph
  • Semantic recognition method and system based on knowledge graph

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Embodiment Construction

[0075] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0076] see figure 1 , which shows a flow chart of a semantic recognition method based on a knowledge map provided by an embodiment of the present invention, which may include the following steps:

[0077] S11: Construct a knowledge graph in advance, the knowledge graph includes a speech layer, a word layer, a presentation layer, a semantic layer and an intent layer, each of which has a corresponding unit.

[0078] It should be noted that the step of pre-const...

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Abstract

The invention discloses a semantic recognition method and system based on a knowledge graph. The method comprises the following steps: constructing the knowledge graph in advance, wherein the knowledge graph comprises a phonetic layer, a word layer, a presentation layer, a semantic layer and an intention layer; receiving input information; converting the input information into phonetic units; determining a word unit related to each phonetic unit and a presentation unit related to each word unit; determining a semantic unit related to each presentation unit; selecting a selected semantic unit according to each semantic unit and a relation between a forerunner group located in front of a corresponding position of the corresponding presentation unit in the input information and a following group behind the corresponding position of the corresponding presentation unit in the input information; determining an intention unit related to each selected semantic unit, and selecting the selected intention units from the intention units according to a relation between each intention unit and the corresponding selected semantic unit; determining that a selected intention set composed of the selected intention units is an intention corresponding to the input information. Therefore, the semantic recognition method and system can be used for carrying out semantic recognition on all natural languages.

Description

technical field [0001] The present invention relates to the technical field of natural language processing, and more specifically, to a semantic recognition method and system based on knowledge graphs. Background technique [0002] In natural language processing, semantic recognition is the core issue. Only when this work is completed can the information in natural language input be effectively recognized and the computer truly understand the text. Simply put, through the realization of this work, the computer can understand the information entered by the user in the form of natural language and obtain the data entered by the user. [0003] The existing technical solutions for semantic recognition are generally based on machine learning. Specifically, the entire semantic recognition process is divided into multiple steps, including word segmentation, part-of-speech tagging, dependency analysis, named entity recognition, and keyword extraction. The above steps all need to us...

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27
CPCG06F40/30
Inventor 张永成尹弘
Owner 张永成
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