LEADER 03982nam 22006015 450 001 996558567203316 005 20240228170759.0 010 $a981-9942-50-0 024 7 $a10.1007/978-981-99-4250-3 035 $a(CKB)5600000000764611 035 $a(MiAaPQ)EBC30882932 035 $a(Au-PeEL)EBL30882932 035 $a(DE-He213)978-981-99-4250-3 035 $a(PPN)272917184 035 $a(OCoLC)1407065938 035 $a(EXLCZ)995600000000764611 100 $a20231025d2023 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aEntity Alignment$b[electronic resource] $eConcepts, Recent Advances and Novel Approaches /$fby Xiang Zhao, Weixin Zeng, Jiuyang Tang 205 $a1st ed. 2023. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2023. 215 $a1 online resource (252 pages) 225 0 $aBig Data Management,$x2522-0187. 311 $a981-9942-49-7 327 $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. 330 $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-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. 606 $aExpert systems (Computer science) 606 $aData mining 606 $aArtificial intelligence$xData processing 606 $aKnowledge Based Systems 606 $aData Mining and Knowledge Discovery 606 $aData Science 615 0$aExpert systems (Computer science). 615 0$aData mining. 615 0$aArtificial intelligence$xData processing. 615 14$aKnowledge Based Systems. 615 24$aData Mining and Knowledge Discovery. 615 24$aData Science. 676 $a006.33 700 $aZhao$b Xiang$01428072 701 $aZeng$b Weixin$01433681 701 $aTang$b Jiuyang$01433682 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a996558567203316 996 $aEntity Alignment$93583422 997 $aUNISA