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Improved Box Embeddings for Fine-Grained Entity Typing

delete2023-12-01
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PRE
AI
Y
Yixiu Qin
Y
Yizhao Wang
J
Jiawei Li
S
Shun Mao
H
He Wang
Y
Yuncheng Jiang *
DOI:10.1109/TBDATA.2023.3310239delete
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摘要

摘要

En 中文
Different from traditional vector-based fine-grained entity typing methods, the box-based method is more effective in capturing the complex relationships between entity mentions and entity types. The box-based fine-grained entity typing method projects entity types and entity mentions into high-dimensional box space, where entity types and entity mentions are embedded as d-dimensional hyperrectangles. However, the impacts of entity types are not considered during classification in high-dimensional box space, and the model cannot be optimized precisely when two boxes are completely separated or overlapped in high-dimensional box space. Based on the above shortcomings, an Improved Box Embeddings (IBE) method for fine-grained entity typing is proposed in this work. The IBE not only introduces the impacts of entity types during classification in high-dimensional box space, but also proposes a distance based module to optimize the model precisely when two boxes are completely separated or overlapped in high-dimensional box space. Experimental results on four fine-grained entity typing datasets verify the effectiveness of the proposed IBE, demonstrating that IBE is a state-of-the-art method for fine-grained entity typing.
Keyword:
Box embeddings
fine-grained entity typing
multi-label classification
type hierarchy

期刊

I
IEEE Transactions on Big Data
IF:
5.7
论文数:
887
被引数:
3.0K

机构

S
south china normal university
学者数:
2.0W
论文数: 1.3W
被引数: 13
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