Titlebook: Knowledge Engineering and Knowledge Management; 20th International C Eva Blomqvist,Paolo Ciancarini,Fabio Vitali Conference proceedings 201

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Ontology Forecasting in Scientific Literature: Semantic Concepts Prediction Based on Innovation-Adopilable at time .. Our approach relies on lexical innovation and adoption information extracted from historical data. We evaluated the SIF model on a very large dataset consisting of over one million scientific papers belonging to the Computer Science domain: the outcomes show that the proposed appro

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Leveraging the Impact of Ontology Evolution on Semantic Annotations and standard ontologies covering a period ranging from 2004 to 2016. We highlight the correlation between changes in the ontologies and changes in the annotations and we discuss the necessity to improve existing annotation formalisms in order to include elements required to support (semi-) automati

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Evolutionary Discovery of Multi-relational Association Rules from Ontological Knowledge Bases. The method is able to mine intensional and assertional knowledge by exploiting problem-aware genetic operators, echoing the refinement operators of inductive logic programming, and by taking intensional knowledge into account, which allows to restrict the search space and direct the evolutionary p

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On Emerging Entity Detection considered by entity linking systems. We construct a publicly available benchmark data set based on English news articles and editing behavior on Wikipedia. Our experiments show that predicting whether an entity will be added to Wikipedia is challenging. However, we can reliably identify emerging e

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Alligator: A Deductive Approach for the Integration of Industry 4.0 Standardsnput documents and produce an integrated AutomationML document. Our empirical evaluation of the quality of . against a benchmark of AutomationML documents suggest that . accurately identifies various types of conflicts between AutomationML documents, and thus helps increasing the scalability, effici