An overview of previous approaches to the visualisation of uncertainty is presented making the distinction between verity visualisation, where the uncertainty information is an in...
This paper presents a method for representing uncertainty in spatial data in a database. The model presented requires moderate amounts of storage space. To compute the probability...
Mining frequent itemsets from transactional datasets is a well known problem with good algorithmic solutions. In the case of uncertain data, however, several new techniques have be...
Classification is one of the most essential tasks in data mining. Unlike other methods, associative classification tries to find all the frequent patterns existing in the input...
We present an automated ontology matching methodology, supported by various machine learning techniques, as implemented in the system MoTo. The methodology is twotiered. On the ...