In this paper, we consider Dijkstra's algorithm for the single source single target shortest paths problem in large sparse graphs. The goal is to reduce the response time for online queries by using precomputed information. For the result of the preprocessing, we admit at most linear space. We assume that a layout of the graph is given. From this layout, in the preprocessing, we determine for each edge a geometric object containing all nodes that can be reached on a shortest path starting with that edge. Based on these geometric objects, the search space for online computation can be reduced significantly. We present an extensive experimental study comparing the impact of different types of objects. The test data we use are traffic networks, the typical field of application for this scenario.

We consider the problem of (repeatedly) computing singlesource single-target shortest paths in large, sparse graphs. Previous investigations have shown the practical usefulness of geometric speed-up techniques that guarantee the correctness of the result for shortest-path computations. However, such speed-up techniques utilize a layout of the graph which typically comes from geographic information. This paper examines the question how geometric speed-up techniques can be used in case there is no layout given. We present an extensive computational study analyzing the usefulness of methods from graph drawing as foundation for such techniques. It turns out that using appropriate layout algorithms, a significant speed-up can be achieved.

In this paper, we consider Dijkstra's algorithm for the single source single target shortest path problem in large sparse graphs. The goal is to reduce the response time for on-line queries by using precomputed information. Due to the size of the graph, preprocessing space requirements can be only linear in the number of nodes. We assume that a layout of the graph is given. In the preprocessing, we determine from this layout a geometric object for each edge containing all nodes that can be reached by a shortest path starting with that edge.

Abstract. Current practice in adaptation modeling assumes that concepts and relationships between concepts are the fundamental building blocks of any adaptive course or adaptive application. This assumption underlies many of the mismatches we nd between the syntax of an adaptation model and the semantics of the `realworld' entity it is trying to model, e.g. procedural knowledge modeled as a single concept and services or activities modeled as pockets of intelligent content. Furthermore, it results in adaptation models that are devoid of truly interactive services with work ow and data ow between those services; it is impossible to capture the semantics of a process-oriented application, e.g. activity-based learning in education and Standard Operating Procedures (SOPs) in the workplace. To this end, we describe a representation of a conceptual and service-based adaptation model. The most signi cant departure from existing representations for adaptation models is the rei cation of services. The goal is to allow for the adaptation of the process itself and not just its constituent parts, e.g. an SOP can be adapted to the role or job function of a user. This expressive power will address the mismatches identi ed above and allow for activity-based and process-oriented adaptive applications. 1