Set-aware Entity Synonym Discovery with Flexible Receptive Fields (Extended Abstract)

Shichao Pei, Lu Yu, Xiangliang Zhang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Entity synonym discovery (ESD) from text corpus is an essential problem in many entity-leveraging applications. This paper aims to address three limitations that widely exist in the current ESD solutions: 1) the lack of effective utilization for synonym set information; 2) the feature extraction of entities from restricted receptive fields; and 3) the incapacity to capture higher-order contextual information. We propose a novel set-aware ESD model that enables a flexible receptive field for ESD by using entity synonym set information and constructing a two-level network. Extensive experimental results on public datasets show that our model consistently outperforms the state-of-the-art with significant improvement.
Original languageEnglish (US)
Title of host publication2022 IEEE 38th International Conference on Data Engineering (ICDE)
ISBN (Print)978-1-6654-0884-4
StatePublished - Aug 2 2022

Bibliographical note

KAUST Repository Item: Exported on 2022-09-14


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