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Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/154901

Title:	Compact Walks: Taming Knowledge-Graph Embeddings with Domain- and Task-Specific Pathways
Authors:	侯佩妤 Hou, Pei-Yu;Korn, Daniel R.;Melo-Filho, Cleber C.;Wright, David R.;Tropsha, Alexander;Chirkova, Rada
Contributors:	企管系
Keywords:	Biomedical knowledge graphs (KGs);KG embeddings;domain- and task-specific regular expressions for creating node neighborhoods
Date:	2022-06
Issue Date:	2024-12-26 13:26:26 (UTC+8)
Abstract:	Knowledge-graph (KG) embeddings have emerged as a promise in addressing challenges faced by modern biomedical research, including the growing gap between therapeutic needs and available treatments. The popularity of KG embeddings in graph analytics is on the rise, due at least partially to the presumed semanticity of the learned embeddings. Unfortunately, the ability of a node neighborhood picked up by an embedding to capture the node's semantics may depend on the characteristics of the data. One of the reasons for this problem is that KG nodes can be promiscuous, that is, associated with a number of different relationships that are not unique or indicative of the properties of the nodes.
Relation:	Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22), Association for Computing Machinery
Data Type:	conference
DOI link:	https://doi.org/10.1145/3514221.3517903
DOI:	10.1145/3514221.3517903
Appears in Collections:	[Department of Business Administation] Proceedings

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