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Clustering is traditionally viewed as an un-supervised method for data analysis. However , in some cases information about the problem domain is available in addition to the data instances themselves. In this paper, we demonstrate how the popular k-means clustering algorithm can be profitably modified to make use of this information. In experiments with(More)
Despite the increasing popularity of route guidance systems, current digital maps are still inadequate for many advanced applications in automotive safety and convenience. Among the drawbacks are the insufficient accuracy of road geometry and the lack of fine-grained information, such as lane positions and intersection structure. In this paper, we present(More)
Navigation systems assist almost any kind of motion in the physical world including sailing, flying, hiking, driving and cycling. On the other hand, traces supplied by global positioning systems (GPS) can track actual time and absolute coordinates of the moving objects. Consequently, this paper addresses ef®cient algorithms and data structures for the route(More)
Multiple sequence alignment (MSA) is a ubiquitous problem in computational biology. Although it is NP-hard to find an optimal solution for an arbitrary number of sequences, due to the importance of this problem researchers are trying to push the limits of exact algorithms further. Since MSA can be cast as a classical path finding problem, it is attracting a(More)
Heuristic search in large problem spaces inherently calls for algorithms capable of running under restricted memory. This question has been investigated in a number of articles. However, in general the eecient usage of two-layered storage systems is not further discussed. Even if hard-disk capacity is suucient for the problem instance at hand, the(More)
We report on a combined approach to solve two known problems of traditional Explanation-Based Generalization (EBG) concerning utility and expressiveness. (1) Usually, for each training example a new rule is derived and added separately. Therefore, the overall performance of the associated inference system may degrade if the presented instances are numerous(More)
In this paper we study External A*, a variant of the conventional (internal) A* algorithm that makes use of external memory, e.g., a hard disk. The approach applies to implicit, undirected, unweighted state space problem graphs with consistent estimates. It combines all three aspects of best-first search, frontier search and delayed duplicate detection and(More)