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However, the current solutions based on PLMs encounter obstacles such as the need for extensive training, expensive data annotation, and inadequate incorporation of structural information. In this study, we introduce a novel zero-training EA framework, ZeroEA, which effectively captures both semantic and structural information for PLMs. To be specific, Graph2Prompt module serves as the bridge between graph structure and plain text by converting KG topology into textual context suitable for PLM input. Additionally, in order to provide PLMs with concise and clear input text of reasonable length, we design a motif-based neighborhood filter to eliminate noisy neighbors. The comprehensive experiments and analyses on 5 benchmark datasets demonstrate the effectiveness of ZeroEA, outperforming all leading competitors and achieving state-of-the-art performance in entity alignment. Notably, our study highlights the considerable potential of EA technique in improving the performance of downstream tasks, thereby benefitting the broader research field.<\/jats:p>","DOI":"10.14778\/3654621.3654640","type":"journal-article","created":{"date-parts":[[2024,5,30]],"date-time":"2024-05-30T22:21:08Z","timestamp":1717107668000},"page":"1765-1774","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":12,"title":["ZeroEA: A Zero-Training Entity Alignment Framework via Pre-Trained Language Model"],"prefix":"10.14778","volume":"17","author":[{"given":"Nan","family":"Huo","sequence":"first","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"given":"Reynold","family":"Cheng","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"given":"Ben","family":"Kao","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"given":"Wentao","family":"Ning","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"given":"Nur Al Hasan","family":"Haldar","sequence":"additional","affiliation":[{"name":"The University of Western Australia"}]},{"given":"Xiaodong","family":"Li","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"given":"Jinyang","family":"Li","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"given":"Mohammad Matin","family":"Najafi","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]},{"given":"Tian","family":"Li","sequence":"additional","affiliation":[{"name":"TCL Research, Hong Kong, China"}]},{"given":"Ge","family":"Qu","sequence":"additional","affiliation":[{"name":"The University of Hong Kong, Hong Kong, China"}]}],"member":"320","published-online":{"date-parts":[[2024,5,30]]},"reference":[{"key":"e_1_2_1_1_1","doi-asserted-by":"publisher","DOI":"10.1109\/ICDM.2015.141"},{"key":"e_1_2_1_2_1","volume-title":"Higher-order organization of complex networks. 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