We study hierarchical segmentations that are optimal in the sense of minimal spanning forests of the original image. We introduce a region-merging operation called uprooting, and w...
In enterprise data warehouses, different users in different business units often define their own application specific dimension hierarchies tailor made to their reporting and b...
Automatic classification of proteins using machine learning is an important problem that has received significant attention in the literature. One feature of this problem is that e...
Arthur Zimek, Fabian Buchwald, Eibe Frank, Stefan ...
Abstract. In this paper, we analyze the effects of energy normalization in adaptivehierarchy-based energy minimization methods. Adaptive hierarchies provide a nt multi-level abstra...
Abstract. An experiment is reported that compared expandable indexes providing full menu context with sequentialmenus providing only partial context. Menu depth was varied using hi...
Panayiotis Zaphiris, Ben Shneiderman, Kent L. Norm...
We present a novel formal interpretation of dynamical hierarchies based on information theory, in which each level is a near-state-determined system, and levels are related to one ...
The Semantic Web is the next step of the current Web where information will become more machine-understandable to support effective data discovery and integration. Hierarchical sc...
Theodore Dalamagas, Alexandra Meliou, Timos K. Sel...
We provide a novel visualization method for the comparison of hierarchically organized data. Our technique visualizes a pair of hierarchies that are to be compared and simultaneou...
Hierarchies have been used for organization, summarization, and access to information, yet a lingering issue is how best to construct them. In this paper, our goal is to automatic...
This paper introduces a new approach to provide users with solutions to explore a domain via an information space. A key point in our approach is that information searching and ex...