SpaceE: Knowledge Graph Embedding by Relational Linear Transformation in the Entity Space
Translation distance based knowledge graph embedding (KGE) methods, such as _TransE_ and _RotatE_, model the relation in knowledge graphs as translation or rotation in the vector space. Both translation and rotation are injective; that is, the translation or rotation of different vectors results in different results. In knowledge graphs, different entities may have a relation with the same entity; for example, many actors starred in one movie. Such a non-injective relation pattern cannot be well modeled by the translation or rotation operations in existing translation distance based KGE methods. To tackle the challenge, we propose a translation distance-based KGE method called **SpaceE** to model relations as linear transformations. The proposed SpaceE embeds both entities and relations in knowledge graphs as matrices and SpaceE naturally models non-injective relations with singular line- doi
- 10.1145/3511095.3531284
- name
- SpaceE: Knowledge Graph Embedding by Relational Linear Transformation in the Entity Space
- source
- authorized-acm-archival-pdf
- license
- © 2022 Association for Computing Machinery.
- summary
- Translation distance based knowledge graph embedding (KGE) methods, such as _TransE_ and _RotatE_, model the relation in knowledge graphs as translation or rotation in the vector space. Both translation and rotation are injective; that is, the translation or rotation of different vectors results in different results. In knowledge graphs, different entities may have a relation with the same entity; for example, many actors starred in one movie. Such a non-injective relation pattern cannot be well modeled by the translation or rotation operations in existing translation distance based KGE methods. To tackle the challenge, we propose a translation distance-based KGE method called **SpaceE** to model relations as linear transformations. The proposed SpaceE embeds both entities and relations in knowledge graphs as matrices and SpaceE naturally models non-injective relations with singular line
- import_kind
- full_text
- open_access
- false
- displayAuthor
- Jinxing Yu, Yunfeng Cai, Mingming Sun, Ping Li
- displayPublishTime
- 2022-06-28
- acm_source_attribution
- Converted from authorized ACM archival PDF; DOI 10.1145/3511095.3531284
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