Automatically Identifying Hypernym-Hyponym Relations of Domain Concepts with Patterns and Projection Learning

doi:10.11925/infotech.2096-3467.2020.0299

Data Analysis and Knowledge Discovery

2020, Vol. 4

Issue (11): 15-25 DOI: 10.11925/infotech.2096-3467.2020.0299

Current Issue | Archive | Adv Search

Automatically Identifying Hypernym-Hyponym Relations of Domain Concepts with Patterns and Projection Learning

Wang Sili^1,²(

),Zhu Zhongming^1,²,Yang Heng¹,Liu Wei¹

¹Literature and Information Center of Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Lanzhou 730000, China
²University of Chinese Academy of Sciences, Beijing 100049, China

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Abstract

[Objective] This paper tries to automatically identify the hypernym-hyponym relations of domain concepts and establish their ontology. [Methods] First, we combined the traditional unsupervised pattern-based method and the advanced supervised-based projection learning method to automatically extract domain concepts. Then, we examined our new method with an empirical study. [Results] The proposed method could identify the hypernym sets of domain concepts. The identification accuracy in medical and general fields, as well as with the benchmark dataset BLESS were 0.88, 0.83, and 0.85 respectively. [Limitations] More research is needed to reduce the weight of high-frequency top-level words and improve the corpus quality. There are also some misidentified relationships. [Conclusions] The proposed model could find hypernym with different meanings for the same concept, which could also extract low-frequency words and named entities.

Key words： Hearst Pattern Projection Learning Word Embedding Hypernym-Hyponym Relations Domain Concept

Received: 09 April 2020 Published: 04 December 2020

ZTFLH:

TP391

Corresponding Authors: Wang Sili E-mail: wangsl@llas.ac.cn

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	Sili Wang
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Cite this article:

Wang Sili,Zhu Zhongming,Yang Heng,Liu Wei. Automatically Identifying Hypernym-Hyponym Relations of Domain Concepts with Patterns and Projection Learning. Data Analysis and Knowledge Discovery, 2020, 4(11): 15-25.

URL:

https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/10.11925/infotech.2096-3467.2020.0299 OR https://manu44.magtech.com.cn/Jwk_infotech_wk3/EN/Y2020/V4/I11/15

Framework of Automatic Recognition of Hypernym-Hyponym Relationship Based on Pattern and Projection Learning

英文模式	中文模式
$Y$ such as $X$	$Y$ 例如/比如 $X$
$Y$ other than $X$	除了 $Y$ 之外的 $X$ / $Y$ 不仅是 $X$
$Y$ including $X$	$Y$ 包含 $X$
$Y$ especially $X$	$Y$ 尤其/特别是 $X$
not all $Y$ are $X$	不全是/并不是所有的 $Y$ 都是 $X$
$Y$ like $X$	$Y$ 类似 $X$
$Y$ for example $X$	$Y$ 例如/比如/示例 $X$
$Y$ which includes $X$	$Y$ 是那些包含 $X$ 的
$X$ are also $Y$	$X$ 也是 $Y$
$X$ are all $Y$	$X$ 都是 $Y$
not $Y$ so much as $X$	没有 $Y$ 而是 $X$
$Y$ is a $X$	$Y$ 是一种/个/只… $X$

Recognition Mode of Hypernym Based on Extended Hearst Pattern

Tests on Recognition of Hypernym-Hyponym Relationship

Recognition Results of Hypernym-Hyponym Relationship in Medical Field

Recognition Results of Hypernym-Hyponym Relationship in General Field

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