Congratulations to Dr Wei Liu and her team of Michael Stewart, Majiga Enkhsaikhan, Morgan Lewis and Tom Smoker for winning the first prize in the ICDM/ICBK Knowledge Graph Contest in Beijing on 11 November.
What is the 2019 ICDM & ICBK Contest on Automatic Knowledge Graph Construction
Automatic knowledge graph construction seeks to build a knowledge graph from unstructured text in a specific domain or cross multiple domains, without human intervention. Teams from both degree-granting institutions and industrial labs are invited to compete in the 2019 ICDM & ICBK Knowledge Graph Contest by automatically constructing knowledge graphs in at least two different domains.
Team submissions were judged on (a) their overall quality of the constructed knowledge graphs, and (b) the generalization ability of their methodology in multiple domains.
Team UWA winning submission
Wei Liu's Team presented an overview of their triple extraction system for the ICDM 2019 Knowledge Graph Contest. This system used a pipeline-based approach to extract a set of triples from a given document. It offered a simple and effective solution to the challenge of knowledge graph construction from domain-specific text. It also provided the ability to visualise useful information about each triple such as the degree, betweenness, structured relation type(s), and named entity types.
Presentation of their prize at the IEEE International Conference on Data Mining
The Team were presented their prize at the IEEE International Conference on Data Mining (ICDM). This conference provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences. The conference covers all aspects of data mining, including algorithms, software, systems, and applications.
ICDM draws researchers, application developers, and practitioners from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases, data warehousing, data visualization, knowledge-based systems, and high-performance computing. By promoting novel, high-quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to advance the state-of-the-art in data mining.
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Congratulations to Dr Wei Liu and her team on winning first prize
Congratulations to Dr Wei Liu and her team of Michael Stewart, Majiga Enkhsaikhan, Morgan Lewis and Tom Smoker for winning the first prize in the ICDM/ICBK Knowledge Graph Contest in Beijing on 11 November.
What is the 2019 ICDM & ICBK Contest on Automatic Knowledge Graph Construction
Automatic knowledge graph construction seeks to build a knowledge graph from unstructured text in a specific domain or cross multiple domains, without human intervention. Teams from both degree-granting institutions and industrial labs are invited to compete in the 2019 ICDM & ICBK Knowledge Graph Contest by automatically constructing knowledge graphs in at least two different domains.
Team submissions were judged on (a) their overall quality of the constructed knowledge graphs, and (b) the generalization ability of their methodology in multiple domains.
Team UWA winning submission
Wei Liu's Team presented an overview of their triple extraction system for the ICDM 2019 Knowledge Graph Contest. This system used a pipeline-based approach to extract a set of triples from a given document. It offered a simple and effective solution to the challenge of knowledge graph construction from domain-specific text. It also provided the ability to visualise useful information about each triple such as the degree, betweenness, structured relation type(s), and named entity types.
Presentation of their prize at the IEEE International Conference on Data Mining
The Team were presented their prize at the IEEE International Conference on Data Mining (ICDM). This conference provides an international forum for presentation of original research results, as well as exchange and dissemination of innovative and practical development experiences. The conference covers all aspects of data mining, including algorithms, software, systems, and applications.
ICDM draws researchers, application developers, and practitioners from a wide range of data mining related areas such as statistics, machine learning, pattern recognition, databases, data warehousing, data visualization, knowledge-based systems, and high-performance computing. By promoting novel, high-quality research findings, and innovative solutions to challenging data mining problems, the conference seeks to advance the state-of-the-art in data mining.
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