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    题名: Compact Walks: Taming Knowledge-Graph Embeddings with Domain- and Task-Specific Pathways
    作者: 侯佩妤
    Hou, Pei-Yu;Korn, Daniel R.;Melo-Filho, Cleber C.;Wright, David R.;Tropsha, Alexander;Chirkova, Rada
    贡献者: 企管系
    关键词: Biomedical knowledge graphs (KGs);KG embeddings;domain- and task-specific regular expressions for creating node neighborhoods
    日期: 2022-06
    上传时间: 2024-12-26 13:26:26 (UTC+8)
    摘要: 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.
    關聯: Proceedings of the 2022 International Conference on Management of Data (SIGMOD '22), Association for Computing Machinery
    数据类型: conference
    DOI 連結: https://doi.org/10.1145/3514221.3517903
    DOI: 10.1145/3514221.3517903
    显示于类别:[企業管理學系] 會議論文

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