A multi-view fusion approach for entity alignment

Chunxia Zhang, Xiuzhang Yang, Shuliang Wang, Zhendong Niu, Yu Guo

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

Entity alignment is an important issue in the areas of ontology alignment and computational intelligence. Ontology alignment is a key technology to solve the semantic heterogeneity problem of ontology and the Semantic Web, and to realize knowledge reusing and integration. The task of entity alignment is to identify entities represented in textual documents or web pages which refer to the same entities in the real world. In this paper, we propose a multi-view fusion approach for entity alignment, and that approach aims to identify the equivalent alignment relations between multiple sets of items or web pages which exist in different Encyclopedia websites. Our approach offers an effective and convenient technique for view construction, view combination and entity alignment. Experimental results show that our algorithm is promising, and its performance outperforms those of single-view based methods.

源语言英语
主期刊名Proceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
编辑Yingxu Wang, Freddie Hamdy, Newton Howard, Lotfi A. Zadeh, Amir Hussain, Bernard Widrow
出版商Institute of Electrical and Electronics Engineers Inc.
388-393
页数6
ISBN(电子版)9781538607701
DOI
出版状态已出版 - 14 11月 2017
活动16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017 - Oxford, 英国
期限: 26 7月 201728 7月 2017

出版系列

姓名Proceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017

会议

会议16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
国家/地区英国
Oxford
时期26/07/1728/07/17

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