Entity Alignment Concepts, Recent Advances and Novel Approaches /

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...

Full description

Saved in:
Bibliographic Details
Main Authors: Zhao, Xiang (Author), Zeng, Weixin (Author), Tang, Jiuyang (Author)
Corporate Author: SpringerLink (Online service)
Format: Electronic eBook
Language:English
Published: Singapore : Springer Nature Singapore : Imprint: Springer, 2023.
Edition:1st ed. 2023.
Series:Big Data Management,
Subjects:
Online Access:Link to Metadata
Tags: Add Tag
No Tags, Be the first to tag this record!

MARC

LEADER 00000nam a22000005i 4500
001 978-981-99-4250-3
003 DE-He213
005 20240307115240.0
007 cr nn 008mamaa
008 231025s2023 si | s |||| 0|eng d
020 |a 9789819942503  |9 978-981-99-4250-3 
024 7 |a 10.1007/978-981-99-4250-3  |2 doi 
050 4 |a QA76.76.E95 
050 4 |a Q387-387.5 
072 7 |a UYQE  |2 bicssc 
072 7 |a COM025000  |2 bisacsh 
072 7 |a UYQE  |2 thema 
082 0 4 |a 006.33  |2 23 
100 1 |a Zhao, Xiang.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
245 1 0 |a Entity Alignment  |h [electronic resource] :  |b Concepts, Recent Advances and Novel Approaches /  |c by Xiang Zhao, Weixin Zeng, Jiuyang Tang. 
250 |a 1st ed. 2023. 
264 1 |a Singapore :  |b Springer Nature Singapore :  |b Imprint: Springer,  |c 2023. 
300 |a XI, 247 p. 1 illus.  |b online resource. 
336 |a text  |b txt  |2 rdacontent 
337 |a computer  |b c  |2 rdamedia 
338 |a online resource  |b cr  |2 rdacarrier 
347 |a text file  |b PDF  |2 rda 
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 
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-upresearch. 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. 
650 0 |a Expert systems (Computer science). 
650 0 |a Data mining. 
650 0 |a Artificial intelligence  |x Data processing. 
650 1 4 |a Knowledge Based Systems. 
650 2 4 |a Data Mining and Knowledge Discovery. 
650 2 4 |a Data Science. 
700 1 |a Zeng, Weixin.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
700 1 |a Tang, Jiuyang.  |e author.  |4 aut  |4 http://id.loc.gov/vocabulary/relators/aut 
710 2 |a SpringerLink (Online service) 
773 0 |t Springer Nature eBook 
776 0 8 |i Printed edition:  |z 9789819942497 
776 0 8 |i Printed edition:  |z 9789819942510 
776 0 8 |i Printed edition:  |z 9789819942527 
830 0 |a Big Data Management,  |x 2522-0187 
856 4 0 |u https://doi.org/10.1007/978-981-99-4250-3  |z Link to Metadata 
912 |a ZDB-2-SCS 
912 |a ZDB-2-SXCS 
912 |a ZDB-2-SOB 
950 |a Computer Science (SpringerNature-11645) 
950 |a Computer Science (R0) (SpringerNature-43710)