Cross-language article linking using cross-encyclopedia entity embedding

研究成果: 書貢獻/報告類型會議論文篇章同行評審

摘要

Cross-language article linking (CLAL) is the task of finding corresponding article pairs of different languages across encyclopedias. This task is a difficult disambiguation problem in which one article must be selected among several candidate articles with similar titles and contents. Existing works focus on engineering text-based or link-based features for this task, which is a time-consuming job, and some of these features are only applicable within the same encyclopedia. In this paper, we address these problems by proposing crossencyclopedia entity embedding. Unlike other works, our proposed method does not rely on known cross-language pairs. We apply our method to CLAL between English Wikipedia and Chinese Baidu Baike. Our features improve performance relative to the baseline by 29.62%. Tested 30 times, our system achieved an average improvement of 2.76% over the current best system (26.86% over baseline), a statistically significant result.

原文???core.languages.en_GB???
主出版物標題Short Papers
發行者Association for Computational Linguistics (ACL)
頁面334-339
頁數6
ISBN(電子)9781948087292
出版狀態已出版 - 2018
事件2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018 - New Orleans, United States
持續時間: 1 6月 20186 6月 2018

出版系列

名字NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference
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???event.eventtypes.event.conference???2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018
國家/地區United States
城市New Orleans
期間1/06/186/06/18

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