广西师范大学学报（自然科学版）2025，Vol.43Issue(3)：23-34,12.DOI:10.16088/j.issn.1001-6600.2024092807
基于主题多视图表示的零样本实体检索方法
Topic-based Multi-view Entity Representation for Zero-Shot Entity Retrieval
摘要
Abstract
Zero-shot entity retrieval,which aims to link mentions to entities unseen during training,plays a vital role in many natural language processing tasks.However,previous methods suffer from two main limitations:(1)The use of only the first k sentences of entity descriptions to construct multi-view representations leads to redundancy and loss of semantic information in these views,making it difficult to fully learn the matching relationship between mentions and entities;(2)The focus solely on mentions to construct positive and negative examples,with inadequate consideration of the comparative relationships between mentions and entities,results in incorrect matchings.To address these issues,a topic-based multi-view entity representations(Topic-MVER)method is proposed in this paper.This method constructs multi-view representations for entities based on topics and employs contrastive learning to model three types of relationships between mentions and entities,enhancing the matching degree between them.Finally,the method achieves Recall@1 scores of 48.13%and 73.86%on the ZESHEL and MedMentions datasets,respectively,presenting improvements of 2.73%and 1.21%over the baseline models.This validates the effectiveness of the proposed method.关键词
实体检索/零样本/长文本/主题多视图/对比学习Key words
entity retrieval/zero-shot/long document/topic-based multi-view/contrastive learning分类
信息技术与安全科学引用本文复制引用
齐丹丹,王长征,郭少茹,闫智超,胡志伟,苏雪峰,马博翔,李时钊,李茹..基于主题多视图表示的零样本实体检索方法[J].广西师范大学学报（自然科学版）,2025,43(3):23-34,12.基金项目
山西省重点研发计划(202102020101008) （202102020101008）
山西省科技合作交流专项(202204041101016) （202204041101016）
山西省基础研究计划(202203021211286,202403021211092) （202203021211286,202403021211092）
