Joris Maervoet

A Mobile Tourist Decision Support System for Small Footprint Devices

This paper presents a mobile tourist decision support system that suggests personal trips, tailored to the users interests and context. The system enables planning a customised trip that maximises the interest of the tourist, while taking the opening hours of the points of interest (POI) and the available time into account. The planning problem is modelled as an orienteering problem with time windows, which is a hard combinatorial optimisation problem. It is solved by an iterated local search metaheuristic procedure, resulting in a personal trip. This procedure is implemented and tested on a mobile phone. Despite the limited computational resources of a small footprint device, the system succesfully solves instances up to 50 POIs in an acceptable execution time. Not more than 1% of the solution quality turned out to be sacrificed in order to keep the worst---case execution time under 5 seconds.

Tour suggestion for outdoor activities

The present article introduces the outdoor activity tour suggestion problem (OATSP). This problem involves finding a closed path of maximal attractiveness in a transportation network graph, given a target path length and tolerance. Total path attractiveness is evaluated as the sum of the average arc attractiveness and the sum of the vertex prizes in the path. This problem definition takes its rise in the design of an interactive web application, which suggests closed paths for several outdoor activity routing modi, such as mountain biking. Both path length and starting point are specified by the user. The inclusion of POIs of some given types enrich the suggested outdoor activity experience. A fast method for the generation of heuristic solutions to the OATSP is presented. It is based on spatial filtering, the evaluation of triangles in a simplified search space and shortest path calculation. It generates valuable suggestions in the context of a web application. It is a promising method to generate candidate paths used by any local search algorithm, which further optimizes the solution.

Fast approximation of reach hierarchies in networks

The reach of an arc in a network can intuitively be described as an indication of the maximum length of the shortest paths of the digraph that pass through this arc. This concept captures the natural hierarchy of any type of network, in an accurate and comprehensive manner. Traditional reach approximation algorithms compute upper bounds to these reaches and require computation of a partial shortest path tree rooted in all vertices of the network. Tailored for route computation enhancement, these methods yield exact reaches in the low reach spectrum, whereas higher reaches are kept set to infinity. The present paper introduces an iterative method for generating lower bounds to the reaches of the arcs in a network. This method is suitable for situations where it is more important to know the order of magnitude of the high than these of the low reaches and where very low or variable calculation times are required. An experiment in an attractiveness-weighted cycling network of considerable size shows that the iterative method steadily approximates the arc reaches for a low number of iterations. The approximation algorithm has been formulated for arc reaches in a digraph but can easily be adapted to a vertex reach version and works in undirected graphs as well.

Tour Suggestion for Outdoor Activities

In recent years, the linked open data (LOD) paradigm has emerged as a promising approach to structuring, publishing, and sharing data online, using Semantic Web standards. From a geospatial perspective, one of the key challenges consists of bridging the gap between the vast amount of crowdsourced, semi-structured or unstructured geoinformation and the Semantic Web. Notably, OpenStreetMap (OSM) has gathered billions of objects from its contributors in a spatial folksonomy. The contribution of this paper is twofold. First, we add a piece to the LOD jigsaw, the OSM Semantic Network, structuring it as a W3C Simple Knowledge Organization System (SKOS) vocabulary, and discussing its role in the constellation of geo-knowledge bases. Second, we devise Voc2WordNet , a mapping approach between a given vocabulary and WordNet, a pivotal component in the LOD cloud. Our approach is evaluated on the OSM Semantic Network against a human-generated alignment, obtaining high precision and recall.