{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,8]],"date-time":"2026-09-08T11:21:04Z","timestamp":1788866464623,"version":"build-2803163510"},"reference-count":38,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T00:00:00Z","timestamp":1737676800000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Sichuan Key Research Fund","award":["2023YFG0001"],"award-info":[{"award-number":["2023YFG0001"]}]},{"name":"Sichuan Key Research Fund","award":["QZQN25F050009"],"award-info":[{"award-number":["QZQN25F050009"]}]},{"name":"Sichuan Key Research Fund","award":["2023D021"],"award-info":[{"award-number":["2023D021"]}]},{"name":"Quzhou Joint Fund of the Zhejiang Provincial Natural Science Foundation of China","award":["2023YFG0001"],"award-info":[{"award-number":["2023YFG0001"]}]},{"name":"Quzhou Joint Fund of the Zhejiang Provincial Natural Science Foundation of China","award":["QZQN25F050009"],"award-info":[{"award-number":["QZQN25F050009"]}]},{"name":"Quzhou Joint Fund of the Zhejiang Provincial Natural Science Foundation of China","award":["2023D021"],"award-info":[{"award-number":["2023D021"]}]},{"name":"Municipal Government of Quzhou","award":["2023YFG0001"],"award-info":[{"award-number":["2023YFG0001"]}]},{"name":"Municipal Government of Quzhou","award":["QZQN25F050009"],"award-info":[{"award-number":["QZQN25F050009"]}]},{"name":"Municipal Government of Quzhou","award":["2023D021"],"award-info":[{"award-number":["2023D021"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Symmetry"],"abstract":"<jats:p>The rapid advancement of knowledge graph (KG) technology has led to the emergence of temporal knowledge graphs (TKGs), which represent dynamic relationships over time. Temporal knowledge graph embedding (TKGE) techniques are commonly employed for link prediction and knowledge graph completion, among other tasks. However, existing TKGE models mainly rely on basic arithmetic operations, such as addition, subtraction, and multiplication, which limits their capacity to capture complex, non-linear relationships between entities. Moreover, many neural network-based TKGE models focus on static entities and relationships, overlooking the temporal dynamics of entity neighborhoods and their potential for encoding relational patterns, which can result in significant semantic loss. To address these limitations, we propose DuaTHP, a novel model that integrates Transformer blocks with Householder projections in the dual quaternion space. DuaTHP utilizes Householder projections to map head-to-tail entity relations, effectively capturing key relational patterns. The model incorporates two Transformer blocks: the entity Transformer, which models entity\u2013relationship interactions, and the context Transformer, which aggregates relational and temporal information. Additionally, we introduce a time-restricted neighbor selector, which focuses on neighbors interacting within a specific time frame to enhance domain-specific analysis. Experimental results demonstrate that DuaTHP significantly outperforms existing methods in link prediction and knowledge graph completion, effectively addressing both semantic loss and time-related issues in TKGs.<\/jats:p>","DOI":"10.3390\/sym17020173","type":"journal-article","created":{"date-parts":[[2025,1,24]],"date-time":"2025-01-24T03:26:31Z","timestamp":1737689191000},"page":"173","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Integrating Transformer Architecture and Householder Transformations for Enhanced Temporal Knowledge Graph Embedding in DuaTHP"],"prefix":"10.3390","volume":"17","author":[{"given":"Yutong","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Biostatistics, City University of Hong Kong, Hong Kong 999077, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Xia","family":"Li","sequence":"additional","affiliation":[{"name":"Yangtze River Delta Research Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yang","family":"Liu","sequence":"additional","affiliation":[{"name":"Yangtze River Delta Research Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324000, China"},{"name":"Institute of Integrated Circuit Science and Engineering, University of Electronic Science and Technology of China, Chengdu 611700, China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Tiangui","family":"Hu","sequence":"additional","affiliation":[{"name":"Yangtze River Delta Research Institute (Quzhou), University of Electronic Science and Technology of China, Quzhou 324000, China"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,1,24]]},"reference":[{"key":"ref_1","unstructured":"Wang, J.T. 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