A new method is presented to get insight into univariate time series data. The problem addressed here is how to identify patterns and trends on multiple time scales (days, weeks, ...
We give a new view on building content clusters from page pair models. We measure the heuristic importance within every two pages by computing the distance of their accessed positi...
Abstract. We propose an approach for efficient word retrieval from printed documents belonging to Digital Libraries. The approach combines word image clustering (based on Self Orga...
We developa clustereddithering methodthatusesstochasticscreening and is able to perform an adaptive variation of the cluster size. This makes it possible to achieve optimal rendit...
In this paper, a bottom-up hierarchical genetic algorithm is proposed to visualize clustered data into a planar graph. To achieve global optimization by accelerating local optimiz...