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Under the current background of big data, the data model and the corresponding algorithm can better express the link between data in its storage, management and calculation, and thus it can meet structured storage and management of big data needs. Therefore, as a kind of concept structured storage, sharing and management model, ontology has drawn more and more attention from the researchers in various disciplines, and has become one of the key problems in the study of big data and information field in recent years. Ontology graph can be used to represent the concept structured storage of…mehr

Produktbeschreibung
Under the current background of big data, the data model and the corresponding algorithm can better express the link between data in its storage, management and calculation, and thus it can meet structured storage and management of big data needs. Therefore, as a kind of concept structured storage, sharing and management model, ontology has drawn more and more attention from the researchers in various disciplines, and has become one of the key problems in the study of big data and information field in recent years. Ontology graph can be used to represent the concept structured storage of ontology, where each vertex represents a concept, and the edge between vertices represents some relationship between concepts (such as implicit affiliation, etc.). In this book, we propose some ontology algorithm for similarity measuring and ontology mapping from the learning point of view.
Autorenporträt
Shu Gong is Ph.D student in School of Information and Control Engineering, China University of Mining and Technology. Gang Hua is supervisior.