Browsing ODA Open Digital Archive by Author "Tan, Zhipeng"

Now showing items 1-4 of 4

    • Knowledge graph embedding closed under composition 

      Zheng, Zhuoxun; Zhou, Baifan; Yang, Hui; Tan, Zhipeng; Sun, Zequn; Li, Chunnong; Waaler, Arild Torolv Søetorp; Kharlamov, Evgeny; Soylu, Ahmet (Peer reviewed; Journal article, 2024)
      Knowledge Graph Embedding (KGE) has attracted increasing attention. Relation patterns, such as symmetry and inversion, have received considerable focus. Among them, composition patterns are particularly important, as they ...

    • Literal-Aware Knowledge Graph Embedding for Welding Quality Monitoring 

      Tan, Zhipeng; Zheng, Zhuoxun; Klironomos, Antonis; Gad-Elrab, Mohamed H.; Xiao, Guohui; Soylu, Ahmet; Kharlamov, Evgeny; Zhou, Baifan (Peer reviewed; Journal article, 2023)
      Recently there has been a series of studies in knowledge graph embedding (KGE), which attempts to learn the embeddings of the entities and relations as numerical vectors and mathematical mappings via machine learning (ML). ...

    • Literal-Aware Knowledge Graph Embedding for Welding Quality Monitoring: A Bosch Case 

      Tan, Zhipeng; Zhou, Baifan; Zheng, Zhuoxun; Savkovic, Ognjen; Huang, Ziqiang; Gonzalez, Irlan-Grangel; Soylu, Ahmet; Kharlamov, Evgeny (Lecture Notes in Computer Science (LNCS);, Chapter; Peer reviewed; Conference object; Journal article, 2023)
      Recently there has been a series of studies in knowledge graph embedding (KGE), which attempts to learn the embeddings of the entities and relations as numerical vectors and mathematical mappings via machine learning (ML). ...

    • Semantic Cloud System for Scaling Data Science Solutions for Welding at Bosch 

      Zheng, Zhuoxun; Zhou, Baifan; Tan, Zhipeng; Savkovic, Ognjen; Rincon-Yanez, Diego; Nikolov, Nikolay Vladimirov; Roman, Dumitru; Soylu, Ahmet; Kharlamov, Evgeny (Peer reviewed; Journal article, 2023)
      Background and Challenges. Industry 4.0 focuses on smart factories that rely on IoT tech- nology for automation. This produces massive amounts of production data, increasing the demand for data-driven solutions and cloud ...