通过多尺度层次的原型学习来改进几次拍摄的关系分类
1College of Computer Science and Technology, Jilin University, Changchun, Jilin, 130012, China; Key Laboratory of Symbol Computation and Knowledge Engineer of the Ministry of Education, Changchun, Jilin, 130012, China.
概括
本研究引入了一种新的多尺度层次原型 (马里奥) 学习方法,用于几次拍摄的关系分类. 马里奥方法通过在多个层面上捕获关系信息并处理文本变异来提高准确性.
科学领域:
- 自然语言处理自然语言处理.
- 机器学习 机器学习
- 人工智能的人工智能
背景情况:
- 短暂的关系分类面临着有限的注释数据的挑战,导致不准确的原型.
- 现有的方法往往忽略了对准确分类至关重要的层次关系信息.
研究的目的:
- 提出一种新的多尺度层次原型 (马里奥) 学习方法,用于几次射击关系分类.
- 提高对全球语义信息的理解,并区分微妙的阶级差异.
主要方法:
- 开发了一种多层次层次的原型学习方法 (Mario),捕获跨集,跨类和类内部的关系信息.
- 嵌入关系描述信息以减轻文本表达的多样性.
主要成果:
- 在FewRel数据集上,在四个少数镜头设置中实现了高准确率 (92.52%/95.33%/85.46%/91.33%).
- 在关键的5向和10向单射设置中,分别超过最强的基线2.87%和4.29%.
结论:
- 拟议的马里奥方法通过利用多个规模的等级原型,有效地增强了几次拍摄关系分类.
- 该模型通过更好地模拟人类认知过程,表现出卓越的性能,特别是在具有挑战性的低数据场景中.
相关概念视频
01:24Concepts and Prototypes
508
The human nervous system handles vast amounts of information by translating sensory stimuli into neural impulses, which the brain processes, creating thoughts expressed through language or stored as memories. The brain also synthesizes information from emotions and memories, which significantly influence thoughts and behaviors. This intricate process creates a comprehensive mental picture.
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
The brain organizes this information using concepts, which are mental categories grouping linguistic data,...
508
01:19Survival Tree
388
Survival trees are a non-parametric method used in survival analysis to model the relationship between a set of covariates and the time until an event of interest occurs, often referred to as the "time-to-event" or "survival time." This method is particularly useful when dealing with censored data, where the event has not occurred for some individuals by the end of the study period, or when the exact time of the event is unknown.
Building a Survival Tree
Constructing a...
Building a Survival Tree
Constructing a...
388