Role discovery of the links based on the network structure
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- KIKUTA Shumpei
- The University of Tokyo
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- TORIUMI Fujio
- The University of Tokyo
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- NISHIGUCHI Mao
- The University of Tokyo
Bibliographic Information
- Other Title
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- 構造に基づくリンクの役割発見
Abstract
<p>This paper aims at the discovery of link roles in order to understand links on the network. This work presents a flexible, general framework including graph transformation, representation learning, role assignment, and sense-making. We use Edge-dual graph to regard links as nodes and struc2vec to embed links based on roles. We show our model successfully embed the similar links into the low 2-dimensional space on visualization task. Furthermore, we assign roles to links and conclude the structure is critical for a better understanding of links. Future work includes the automatic algorithm to decide the number of clusters and apply our method to real-world datasets.</p>
Journal
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- Proceedings of the Annual Conference of JSAI
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Proceedings of the Annual Conference of JSAI JSAI2019 (0), 1J4J302-1J4J302, 2019
The Japanese Society for Artificial Intelligence
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Details 詳細情報について
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- CRID
- 1390845713072685184
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- NII Article ID
- 130007658324
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- Text Lang
- ja
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- Data Source
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- JaLC
- CiNii Articles
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- Abstract License Flag
- Disallowed