Q. In competitive scenarios among Knowledge Organisms (KOs), who typically acquires a knowledge token?

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Q. What is the primary objective of a Big Data computing system or infrastructure?

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Q. What role do ontologies play in the Knowledge Organism (KO) ecosystem?

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Q. How do ontologies change in the evolving ecosystem?

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Q. What does "reuse" of an ontology in the context of KOs and data processing mean?

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Q. How does the reuse of ontologies increase their value in the KO ecosystem?

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Q. In the evolving KO ecosystem, what leads to changes in ontologies?

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Q. What is the purpose of the knowledge extraction subsystem in the KO ecosystem?

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Q. How do ontologies naturally change in the KO ecosystem?

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Q. What is one of the factors that can influence the fitness of a KO in the ecosystem?

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Q. How does the age of assertions in a KO's knowledge body affect its fitness?

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Q. What is the proportion between the parts of knowledge tokens that influences a KO's fitness?

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Q. What property of a knowledge token can affect its value?

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Q. Why does a token become less valuable over its lifetime in the environment?

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Q. How can the quality of an ontology be assessed as a dynamic optimization problem?

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Q. What is the essence of adequate understanding of the changes in the world reflected in Big Data?

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Q. What is Big Data considered to be a fine-grained reflection of?

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Q. Why is the demand for effective and efficient use of Big Data in industries enormous?

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Q. What approach was offered to help understand Big Data in a way that balances effectiveness and efficiency?

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Q. What is one of the major recommendations for achieving a balance in processing data semantics?

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