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Error-reduction sampling (ERS) is a high performing (but computationally expensive) query selection strategy for active learning. Subset optimisation has been proposed to reduce computational expense by applying ERS to only a subset of examples from the pool. This paper compares techniques used to construct the subset, namely random sub-sampling and pre-filtering. We focus on pre-filtering which populates...
In Data Mining, the usefulness of association rules is strongly limited by the huge amount of delivered rules. In this paper we propose a new approach to prune and filter discovered rules. Using Domain Ontologies, we strengthen the integration of user knowledge in the post-processing task. Furthermore, an interactive and iterative framework is designed to assist the user along the analyzing task....
We present Graphite, a system that allows the user to visually construct a query pattern, finds both its exact and approximate matching subgraphs in large attributed graphs, and visualizes the matches. For example, in a social network where a person's occupation is an attribute, the user can draw a 'star' query for "finding a CEO who has interacted with a Secretary, a Manager, and an Accountant,...
Matrix factorization (MF) based approaches have proven to be efficient for rating-based recommendation systems. In this work, we propose several matrix factorization approaches with improved prediction accuracy. We introduce a novel and fast (semi)-positive MF approach that approximates the features by using positive values for either users or items. We describe a momentum-based MF approach. A transductive...
Coastal buoys and stations provide frequent, high quality marine observations for oceanographic study, weather service, atmospheric and public safety. Sharing of the generated data sets requires tremendous efforts and coordination among the different sensor network agencies to come to a shared understanding and for dissemination in a uniform way. Syntactic standardization provides data description...
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