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Nos liseuses Vivlio rencontrent actuellement des problèmes de synchronisation. Nous faisons tout notre possible pour résoudre ce problème le plus rapidement possible. Toutes nos excuses pour la gêne occasionnée !
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- 7.000.0000 titres dans notre catalogue
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- Toujours un magasin près de chez vous
Entity Alignment
Concepts, Recent Advances and Novel Approaches
Xiang Zhao, Weixin Zeng, Jiuyang Tang
76,45 €
+ 152 points
Format
Description
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.
Spécifications
Parties prenantes
- Auteur(s) :
- Editeur:
Contenu
- Nombre de pages :
- 247
- Langue:
- Anglais
- Collection :
Caractéristiques
- EAN:
- 9789819942527
- Date de parution :
- 26-10-23
- Format:
- Livre broché
- Format numérique:
- Trade paperback (VS)
- Dimensions :
- 156 mm x 234 mm
- Poids :
- 367 g
