![]() Nakashole, N., Theobald, M., Weikum, G.: Scalable knowledge harvesting with high precision and high recall. In: Proceedings of the 16th International Conference on World Wide Web, pp 697–706 (2007) Suchanek, F.M., Kasneci, G., Weikum, G.: Yago: A core of semantic knowledge. Lehmann, J., Isele, R., Jakob, M., Jentzsch, A., Kontokostas, D., Mendes, P.N., Hellmann, S., Morsey, M., Van Kleef, P., Auer, S., et al: Dbpedia–a large-scale, multilingual knowledge base extracted from wikipedia. In: Proceedings of the 2008 ACM SIGMOD International Conference on Management of Data, pp 1247–1250 (2008) ACM 38(11), 33–38 (1995)īollacker, K., Evans, C., Paritosh, P., Sturge, T., Taylor, J.: Freebase: A collaboratively created graph database for structuring human knowledge. Lenat, D.B.: Cyc: A large-scale investment in knowledge infrastructure. Staab, S., Studer, R.: Handbook on Ontologies. Group, R.W.: Resource Description Framework (RDF). Shortliffe, E.: Computer-based Medical Consultations: MYCIN, vol. At last, we combine and compare the collection of the evolution and multiple state-of-the-arts on ocean spatiotemporal data processing.Ĭhung, C.-J.F., Fabbri, A.G.: The representation of geoscience information for data integration. We further summarize related representation works on ocean spatiotemporal data, the construction of a ocean knowledge graph, and the management of ocean spatiotemporal data. In detail, we comprehensively discuss about ocean spatiotemporal data processing techniques. This paper tends to provide a summary of studies on these issues, including the data representation, data processing, knowledge discovery, and algorithms on finding unique patterns on ocean environment changes, such as temperature, tide height, waves, salinity, etc. However, with high dimensionality, large quantities, heterogeneous sources, and especially, the spatiotemporal manner, the diversity between the specific knowledge required and massive data chunk puts forward unique challenges in data representation and knowledge mining, effectively. Studies on Hydrology and Oceanology become the root of many disciplines, including global resource management, macro economy, environment protection, climate predictions, etc, which motivates our further exploration on the underlying feature behind the ocean data. ![]() Ocean data exhibits interesting yet human critical features affecting all creatures around the world.
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