TransERR: Translation-based Knowledge Graph Embedding via Efficient Relation Rotation

arXiv:2306.14580v2 Announce Type: replace
Abstract: This paper presents a translation-based knowledge geraph embedding method via efficient relation rotation (TransERR), a straightforward yet effective alternative to traditional translation-based knowledge graph embedding models. Different from the previous translation-based models, TransERR encodes knowledge graphs in the hypercomplex-valued space, thus enabling it to possess a higher degree of translation freedom in mining latent information between the head and tail entities. To further minimize the translation distance, TransERR adaptively rotates the head entity and the …

arxiv cs.ai cs.cl embedding graph knowledge knowledge graph rotation translation type via