Entity alignment : concepts, recent advances and novel approaches / Xiang Zhao, Weixin Zeng, Jiuyang Tang.

This open access book systematically investigates, the topic of entity alignment, which aims to detect equivalent entities that are located in different knowledge graphs. Entity alignment represents an essential step in enhancing the quality of knowledge graphs, and hence is of significance to downs...

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Bibliographic Details
Main Authors: Zhao, Xiang (Computer scientist) (Author), Zeng, Weixin (Author), Tang, Jiuyang (Author)
Format: eBook
Language:English
Published: Singapore : Springer, 2023.
Series:Big data management,
Subjects:
Online Access:Click for online access

MARC

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245 1 0 |a Entity alignment :  |b concepts, recent advances and novel approaches /  |c Xiang Zhao, Weixin Zeng, Jiuyang Tang. 
264 1 |a Singapore :  |b Springer,  |c 2023. 
300 |a 1 online resource (xi, 247 pages) :  |b illustrations. 
336 |a text  |b txt  |2 rdacontent 
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338 |a online resource  |b cr  |2 rdacarrier 
490 1 |a Big data management,  |x 2522-0187 
505 0 |a Chapter 1. Introduction to Entity Alignment -- Chapter 2. State-of-the-art Approaches and Categorization -- Chapter 3. Recent Advance in Representation Learning -- Chapter 4. Recent Advance in Alignment Inference -- Chapter 5. Experimental Survey and Evaluation -- Chapter 6. Large-scale Entity Alignment -- Chapter 7. Long-tail Entity Alignment -- Chapter 8. Weakly-supervised Entity Alignment -- Chapter 9. Unsupervised Entity Alignment -- Chapter 10. Multimodal Entity Alignment. 
506 0 |a Open access.  |5 GW5XE 
520 |a This open access book systematically investigates, the topic of entity alignment, which aims to detect equivalent entities that are located in different knowledge graphs. Entity alignment represents an essential step in enhancing the quality of knowledge graphs, and hence is of significance to downstream applications, e.g., question answering and recommender systems. Recent years have witnessed a rapid increase in the number of entity alignment frameworks, while the relationships among them remain unclear. This book aims to fill that gap by elaborating the concept and categorization of entity alignment, reviewing recent advances in entity alignment approaches, and introducing novel scenarios and corresponding solutions. Specifically, the book includes comprehensive evaluations and detailed analyses of state-of-the-art entity alignment approaches and strives to provide a clear picture of the strengths and weaknesses of the currently available solutions, so as to inspire follow-up research. In addition, it identifies novel entity alignment scenarios and explores the issues of large-scale data, long-tail knowledge, scarce supervision signals, lack of labelled data, and multimodal knowledge, offering potential directions for future research. The book offers a valuable reference guide for junior researchers, covering the latest advances in entity alignment, and a valuable asset for senior researchers, sharing novel entity alignment scenarios and their solutions. Accordingly, it will appeal to a broad audience in the fields of knowledge bases, database management, artificial intelligence and big data. 
504 |a Includes bibliographical references. 
588 0 |a Online resource; title from PDF title page (SpringerLink, viewed October 30, 2023). 
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700 1 |a Zeng, Weixin,  |e author.  |0 (orcid)0000-0002-2690-3190  |1 https://orcid.org/0000-0002-2690-3190 
700 1 |a Tang, Jiuyang,  |e author. 
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