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In the rapidly evolving field of metabolic engineering, the quest for efficient and precise gene target identification for metabolite production enhancement presents significant challenges. Traditional approaches, whether knowledge-based or model-bas
Externí odkaz:
http://arxiv.org/abs/2410.18475
Entity alignment is a crucial task in knowledge graph fusion. However, most entity alignment approaches have the scalability problem. Recent methods address this issue by dividing large KGs into small blocks for embedding and alignment learning in ea
Externí odkaz:
http://arxiv.org/abs/2208.11125
Entity alignment is to find identical entities in different knowledge graphs. Although embedding-based entity alignment has recently achieved remarkable progress, training data insufficiency remains a critical challenge. Conventional semi-supervised
Externí odkaz:
http://arxiv.org/abs/2203.06308
Entity alignment is a crucial step in integrating knowledge graphs (KGs) from multiple sources. Previous attempts at entity alignment have explored different KG structures, such as neighborhood-based and path-based contexts, to learn entity embedding
Externí odkaz:
http://arxiv.org/abs/2201.00304
Akademický článek
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Akademický článek
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Publikováno v:
World Wide Web; 2021, Vol. 24 Issue 1, p351-373, 23p
Publikováno v:
Journal of Liaoning Technical University (Natural Science Edition) / Liaoning Gongcheng Jishu Daxue Xuebao (Ziran Kexue Ban). Aug2024, Vol. 43 Issue 4, p443-453. 11p.
Autor:
Xin Wang, Maria Luisa Sapino, Wook-Shin Han, Amr El Abbadi, Gill Dobbie, Zhiyong Feng, Yingxiao Shao, Hongzhi Yin
The four-volume set LNCS 13943, 13944, 13945 and 13946 constitutes the proceedings of the 28th International Conference on Database Systems for Advanced Applications, DASFAA 2023, held in April 2023 in Tianjin, China.The total of 125 full papers, alo
This book constitutes the proceedings of the 20th International Conference on Web Information Systems Engineering, WISE 2019, held in Hong Kong, China, in November 2019. Due to the problems/protests in Hong Kong, WISE 2019 was postponed from Novem