000			04231nam a22005895i 4500
001			978-981-99-4250-3
003			DE-He213
005			20240507154521.0
007			cr nn 008mamaa
008			231025s2023 si | s |||| 0|eng d
020			_a9789819942503 _9978-981-99-4250-3
024	7		_a10.1007/978-981-99-4250-3 _2doi
050		4	_aQA76.76.E95
050		4	_aQ387-387.5
072		7	_aUYQE _2bicssc
072		7	_aCOM025000 _2bisacsh
072		7	_aUYQE _2thema
082	0	4	_a006.33 _223
100	1		_aZhao, Xiang. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
245	1	0	_aEntity Alignment _h[electronic resource] : _bConcepts, Recent Advances and Novel Approaches / _cby Xiang Zhao, Weixin Zeng, Jiuyang Tang.
250			_a1st ed. 2023.
264		1	_aSingapore : _bSpringer Nature Singapore : _bImprint: Springer, _c2023.
300			_aXI, 247 p. 1 illus. _bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aBig Data Management, _x2522-0187
505	0		_aChapter 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		_aOpen Access
520			_aThis 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	_aExpert systems (Computer science).
650		0	_aData mining.
650		0	_aArtificial intelligence _xData processing.
650	1	4	_aKnowledge Based Systems.
650	2	4	_aData Mining and Knowledge Discovery.
650	2	4	_aData Science.
700	1		_aZeng, Weixin. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aTang, Jiuyang. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut
710	2		_aSpringerLink (Online service)
773	0		_tSpringer Nature eBook
776	0	8	_iPrinted edition: _z9789819942497
776	0	8	_iPrinted edition: _z9789819942510
776	0	8	_iPrinted edition: _z9789819942527
830		0	_aBig Data Management, _x2522-0187
856	4	0	_uhttps://doi.org/10.1007/978-981-99-4250-3
912			_aZDB-2-SCS
912			_aZDB-2-SXCS
912			_aZDB-2-SOB
999			_c37467 _d37467