11 citations · 19 across the 9 of their papers we have counts for
9 papers
ExeKGLib: A Platform for Machine Learning Analytics based on Knowledge Graphs
Antonis Klironomos, Baifan Zhou, Zhipeng Tan +4
Nowadays machine learning (ML) practitioners have access to numerous ML libraries available online. Such libraries can be used to create ML pipelines that consist of a series of st…
ReaLitE: Enrichment of Relation Embeddings in Knowledge Graphs using Numeric Literals
Antonis Klironomos, Baifan Zhou, Zhuoxun Zheng +3
Most knowledge graph embedding (KGE) methods tailored for link prediction focus on the entities and relations in the graph, giving little attention to other literal values, which m…
Real-Time Event Detection with Random Forests and Temporal Convolutional Networks for More Sustainable Petroleum Industry
Yuanwei Qu, Baifan Zhou, Arild Waaler +1
The petroleum industry is crucial for modern society, but the production process is complex and risky. During the production, accidents or failures, resulting from undesired produc…
Addressing the Scalability Bottleneck of Semantic Technologies at Bosch
Diego Rincon-Yanez, Mohamed H. Gad-Elrab, Daria Stepanova +4
At the heart of smart manufacturing is real-time semi-automatic decision-making. Such decisions are vital for optimizing production lines, e.g., reducing resource consumption, impr…
Literal-Aware Knowledge Graph Embedding for Welding Quality Monitoring: A Bosch Case
Zhipeng Tan, Baifan Zhou, Zhuoxun Zheng +5
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 mathem…
Scaling Data Science Solutions with Semantics and Machine Learning: Bosch Case
Baifan Zhou, Nikolay Nikolov, Zhuoxun Zheng +5
Industry 4.0 and Internet of Things (IoT) technologies unlock unprecedented amount of data from factory production, posing big data challenges in volume and variety. In that contex…
ExeKGLib: Knowledge Graphs-Empowered Machine Learning Analytics
Antonis Klironomos, Baifan Zhou, Zhipeng Tan +4
Many machine learning (ML) libraries are accessible online for ML practitioners. Typical ML pipelines are complex and consist of a series of steps, each of them invoking several ML…
Query-based Industrial Analytics over Knowledge Graphs with Ontology Reshaping
Zhuoxun Zheng, Baifan Zhou, Dongzhuoran Zhou +4
Industrial analytics that includes among others equipment diagnosis and anomaly detection heavily relies on integration of heterogeneous production data. Knowledge Graphs (KGs) as…
Towards Ontology Reshaping for KG Generation with User-in-the-Loop: Applied to Bosch Welding
Dongzhuoran Zhou, Baifan Zhou, Jieying Chen +3
Knowledge graphs (KG) are used in a wide range of applications. The automation of KG generation is very desired due to the data volume and variety in industries. One important appr…