Natural language semantic matching method for sequence global attention and local dynamic attention

A natural language and semantic matching technology, applied in the field of deep learning and natural language understanding, can solve the problems of different degrees of influence and changes, and achieve the effect of accurate judgment

Active Publication Date: 2019-08-06
UNIV OF SCI & TECH OF CHINA
View PDF3 Cites 13 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0005] The above research on the semantic representation of natural language using the attention mechanism is mainly to select all the important information in one selection, ignoring two important phenomena: 1) The important part of the sentence may change with the in-depth understanding of the sentence semantics. (or in-depth understanding of the surrounding context); 2) the same words in different positions in the sentence have different influences on the semantics of the sentence, and the local structure corresponding to these same words helps to distinguish this difference.

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Natural language semantic matching method for sequence global attention and local dynamic attention
  • Natural language semantic matching method for sequence global attention and local dynamic attention
  • Natural language semantic matching method for sequence global attention and local dynamic attention

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0017] The technical solutions in the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some of the embodiments of the present invention, not all of them. 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.

[0018] The embodiment of the present invention provides a natural language semantic matching method of sequence global attention and local dynamic attention, such as figure 1 As shown, it mainly includes the following steps:

[0019] Step 11. Semantic modeling is performed on each word in the natural language sentence pair to obtain a corresponding semantic representation vector.

[0020] The preferred implementation of this step is as follows:

...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

Abstract

The invention discloses a natural language semantic matching method for sequence global attention and local dynamic attention. Global understanding and representation of sentence semantics are achieved through a stacked gating recurrent neural network and a self-attention mechanism; dynamic analysis of important information of the sentences is achieved through a local dynamic attention mechanism,and dynamic local representation of sentence semantics is obtained. According to the method, more comprehensive understanding of sentence semantics is achieved through global attention and local dynamic attention of the sentence sequence, then semantic interaction between two sentences is accurately modeled, finally accurate judgment of the sentence semantic matching relation is achieved, and thedefects of an existing method in the aspect of attention mechanism use are overcome.

Description

technical field [0001] The invention relates to the technical fields of deep learning and natural language understanding, and in particular to a natural language semantic matching method of sequence global attention and local dynamic attention. Background technique [0002] Natural language sentence semantic matching (Sentence Semantic Matching) is a very important part of the field of natural language processing, and it is a common method to evaluate whether the semantic representation of sentences is accurate. The main problem it solves is to judge the semantic relationship between two sentences. Depending on the specific task, the semantic relationship between sentences is also defined differently. For example, in Natural Language Inference (NLI), sentence semantic matching is mainly used to determine whether the semantics of the premise sentence (Premise Sentence) implies the semantics of the Hypothesis Sentence (Hypothesis Sentence). In Information Retrieval (IR), sen...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/27
CPCG06F40/242G06F40/30
Inventor 陈恩红刘淇张琨吕广奕吴乐
Owner UNIV OF SCI & TECH OF CHINA
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products

Browse by: Latest US Patents, China's latest patents, Technical Efficacy Thesaurus, Application Domain, Technology Topic.

© 2024 PatSnap. All rights reserved.Legal|Privacy policy|Modern Slavery Act Transparency Statement|Sitemap