A Mobile Tourist Decision Support System for Small Footprint Devices

Souffiau, Wouter; Maervoet, Joris; Vansteenwegen, Pieter; Berghe, Greet Vanden; Oudheusden, Dirk Van

doi:10.1007/978-3-642-02478-8_156

Cited by 22 publications

(12 citation statements)

References 7 publications

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“…The most important contribution is prevent more deaths in the city because stay on an incorrect place on a wrong time, our future research is adequate the information to actualize from the central server of security of the Police Department of the city, if the people considering that 105000 people died during this last six years in Mexico, this innovative application is possible to use in another great cities in Latin America as Caracas in Venezuela, Medellin in Colombia or Río de JaneiroJacaraznho Favela-in Brazil with similar values of homicides, this Intelligent Tool will be used by different Communities for example gay people whom lost 87 people during 2012. In addition this application will be used as Recommender System when travel to another societies [7] and explain different scenarios according time and location.…”

Section: Resultsmentioning

confidence: 99%

Implementation of a Mobile Device to Determine Danger in a Great City Based on Ubiquity

Ochoa¹,

Ponce

S'nchez³

et al. 2012

2012 Eighth International Conference on Intelligent Environments

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Juarez City has been a victim of the consequences brought about organized crime, such as killing of innocent people as the main fact assaults, kidnappings, multi homicides, burglary, among other consequences, including 487500 people abandoned the city. What has pushed the population of the city to take action of different kinds to minimize the violence in a society with 17900 violent homicides during this period of time; the reason which we present the following project, which aims to provide people moving in this city a technological tool that provides an indicator to the user information based statistics compiled by the Centre for Social Research at Juarez City University and public sources so uncertain is the place where you are. This research try to combine a Mobile Device based on Cultural Algorithms and Data Mining to determine the danger of stay in a part of the city in a specific time.

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Section: Resultsmentioning

confidence: 99%

Implementation of a Mobile Device to Determine Danger in a Great City Based on Ubiquity

Ochoa¹,

Ponce

S'nchez³

et al. 2012

2012 Eighth International Conference on Intelligent Environments

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“…In this implementation, the cooling function follows a decreasing exponential law, which depends on current iteration t and parameter α. At a given iteration t, the temperature T t is calculated by using Equation 10, where T t−1 represent the temperature in previous iteration.…”

Section: Simulated Annealing Implementationmentioning

confidence: 99%

“…In the process of trip itinerary planning, a method that estimates the interest of the tourist about POIs is required [10]. A such a method would consider the preferences of the tourist and features of the POIs, and based on their reciprocal match, it would generate the estimated satisfaction factors of the tourist with each POI.…”

Section: Introductionmentioning

confidence: 99%

Solving tourist trip planning problem via a simulated annealing algorithm

Sylejmani

Muhaxhiri²,

Dika

et al. 2014

2014 37th International Convention on Information and Communication Technology, Electronics and Microelectronics (MIPRO)

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Nowadays, by help of tourist trip planners, in many travel destinations, the trip itinerary could be prepared automatically. The trip planners enable customization of trip itinerary based on tourist preferences, available time and budget, where the itinerary is optimized by using optimization techniques from the field of metaheuristics. In this paper, we present a new approach based on simulated annealing algorithm for solving the tourist trip planning problem. The hard constraints include limited trip duration, working hours of points of interest (POIs) and tourist budget, while tourist preferences and traveling time comprise the soft constraints, which take part in a two component function for evaluation of quality of solutions. The search space is explored by using three types of operators, namely insert, swap and shake. The algorithm is tested against some real test data for the city of Prishtina in Kosova. In addition to fine tuning the values of algorithm parameters, further experiments are made for exploring different approaches of construction of initial solution, time duration of algorithm execution for various trip lengths, and influence of shake operator into the solution quality.

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“…This kind of services are often realized as a web-based application or a mobile client-server application (e.g. [1,16]), generating on-thefly suggestions for the end user. This is usually not required for applications in collective tourism planning (bus tour planning, cruise itinerary planning).…”

Section: Tour Suggestion Models For Leisure and Tourismmentioning

confidence: 99%

Tour Suggestion for Outdoor Activities

Maervoet

Brackman²,

Verbeeck

et al. 2013

Web and Wireless Geographical Information Systems

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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.

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A Mobile Tourist Decision Support System for Small Footprint Devices

Cited by 22 publications

References 7 publications

Implementation of a Mobile Device to Determine Danger in a Great City Based on Ubiquity

Implementation of a Mobile Device to Determine Danger in a Great City Based on Ubiquity

Solving tourist trip planning problem via a simulated annealing algorithm

Tour Suggestion for Outdoor Activities

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