Recurrent neural network event sequential relationship recognition method based on semantic attention

A time-series relationship and attention technology, applied in semantic analysis, natural language data processing, special data processing applications, etc., can solve problems such as difficulty in capturing semantic information, lack of effective connection and fusion information for different word segmentations, etc.
CN111160027APending Publication Date: 2020-05-15HANGZHOU DIANZI UNIV
0 Cites 5 Cited by

Patent Information

Authority / Receiving Office
CN · China
Current Assignee / Owner
HANGZHOU DIANZI UNIV
Publication Date
2020-05-15

Smart Images

  • Figure 1
    Figure 1
  • Figure 2
    Figure 2
  • Figure 3
    Figure 3
Patent Text Reader

Abstract

The invention discloses a recurrent neural network event sequential relationship recognition method based on semantic attention, and the method mainly comprises the following steps: firstly carrying out syntactic dependency analysis on an inputted event sentence, intercepting a related trigger word semantic dependency branch, and then obtaining a corresponding hidden state vector through a recurrent neural network; then, calculating attention weight vectors except the trigger word, fusing different segmented words according to different weights, then splicing the fused segmented words with thetrigger word, and obtaining event sentence state vectors; and finally, putting the event sentence state vector into a softmax function to predict a time sequence relationship. According to the method, semantic information implied in event sentences can be effectively captured, and different segmented words can be effectively associated and fused, so that the event sequential relationship recognition precision is improved.
Need to check novelty before this filing date? Find Prior Art

Description

technical field

[0001] The invention relates to the field of natural language processing, in particular to a method for recognizing the time sequence relationship of events in a cyclic neural network based on semantic attention. Background technique

[0002] As an important form of knowledge representation, events have received extensive attention in the field of natural language processing. An event is a set of related descriptions about a topic. As an important means of conveying information, it objectively depicts the occurrence of a specific subject (some or some people and objects) in a specific time and place environment. one thing. The event sequence relationship refers to the time sequence relationship between events when they occur. It is a semantic relationship between events, which connects the evolution process of a subject event from the beginning to the end and the interrelationship of events. Examples of event timing relationship recognition (taken from the ...

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