A multi-view fusion approach for entity alignment

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationProceedings of 2017 IEEE 16th International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
EditorsYingxu Wang, Freddie Hamdy, Newton Howard, Lotfi A. Zadeh, Amir Hussain, Bernard Widrow
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages388-393
Number of pages6
ISBN (Electronic)9781538607701
DOIs
Publication statusPublished - 14 Nov 2017
Event16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017 - Oxford, United Kingdom
Duration: 26 Jul 201728 Jul 2017

Publication series

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

Conference

Conference16th IEEE International Conference on Cognitive Informatics and Cognitive Computing, ICCI*CC 2017
Country/TerritoryUnited Kingdom
CityOxford
Period26/07/1728/07/17

Keywords

  • Entity alignment
  • computational intelligence
  • multi-view fusion model
  • ontology alignment
  • semantic computing

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