海洋学数据库中的知识发现:数据源的复杂性问题

R. Ladner, F. Petry
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引用次数: 0

摘要

数据挖掘或知识发现是指旨在从大型数据库中发现有用模式和关联的各种技术。我们一直在为各种海洋学数据使用数据挖掘技术,并且遇到了一些与可用数据相关的麻烦问题。我们描述了数据挖掘的准备步骤和我们应用于时空数据的三种数据挖掘技术。我们详细回顾了地理空间、海洋学和气象数据的各种来源,以及在知识发现中使用这些数据所固有的相关问题。我们还提供了与为知识发现提供这种异构数据的全面集成的困难相关的问题。
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Knowledge discovery in oceanographic databases: issues of complications in data sources
Data mining or knowledge discovery refers to a variety of techniques having the intent of uncovering useful patterns and association from large databases. We have been working with data mining techniques for a variety of oceanographic data and have encountered a number of troublesome issues relative to available data. We describe the steps preparatory to data mining and three data mining techniques that we have applied to spatio-temporal data. We include a detailed review of various sources of geospatial, oceanographic and meteorological data and associated issues inherent in their use in knowledge discovery. We also provide issues relevant to the difficulties in providing an overall integration of this heterogeneous data for knowledge discovery.
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