Abstract. We present a prototype application for graph-based data exploration and mining, with particular emphasis on scientific data. The application has a Flash-based graphical i...
Co-training, a paradigm of semi-supervised learning, may alleviate effectively the data scarcity problem (i.e., the lack of labeled examples) in supervised learning. The standard ...
Abstract. Frequent itemset mining can be regarded as advanced database querying where a user specifies the dataset to be mined and constraints to be satisfied by the discovered i...
Data mining applications are typically used in the decision making process. The Knowledge Discovery Process (KDD process for short) is a typical iterative process, in which not on...
The subfield of itemset mining is essentially a collection of algorithms. Whenever a new type of constraint is discovered, a specialized algorithm is proposed to handle it. All o...
Daniel Kifer, Johannes Gehrke, Cristian Bucila, Wa...