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Automatic Knowledge Graph Construction: A Report on the 2019 ICDM/ICBK Contest
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Citations
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References
2019
Year
Unknown Venue
EngineeringKnowledge ExtractionSemantic WebIeee Icdm 2019Knowledge TechnologyText MiningKnowledge Graph EmbeddingsInformation RetrievalData ScienceData MiningKnowledge EngineeringKnowledge RepresentationKnowledge DiscoveryIcdm/icbk ContestComputer ScienceAutomated Knowledge AcquisitionKnowledge GraphsKnowledge BaseKnowledge Data EngineeringGraph TheoryKnowledge Graph ContestAutomated ReasoningBusinessSemantic Graph
Automatic knowledge graph construction seeks to build a knowledge graph from unstructured text in a specific domain or cross multiple domains, without human intervention. IEEE ICDM 2019 and ICBK 2019 invited teams from both degree-granting institutions and industrial labs to compete in the 2019 Knowledge Graph Contest by automatically constructing knowledge graphs in at least two different domains. This article reports the outcomes of the Contest. The participants were expected to build a model to extract knowledge represented as triplets from text data and develop a web application to visualize the triplets. Awards were given to five teams. Their models and key techniques used to construct knowledge graphs are summarized.
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