Survey on using constraints in data mining
作者： Valerio Grossi , Andrea Romei , Franco Turini
DOI: 10.1007/S10618-016-0480-Z
关键词:
摘要: This paper provides an overview of the current state-of-the-art on using constraints in knowledge discovery and data mining. The use a mining task requires specific definition satisfaction tools during extraction. survey proposes three groups studies based classification, clustering pattern mining, whether are data, models or measures, respectively. We consider distinctions between hard soft constraint satisfaction, extraction phases where considered. In addition to discussing how can be used we show constraint-based languages throughout process.
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