S.A. Mikhailov – Post-graduate Student, ITMO University (Saint Petersburg); Junior Research Scientist, St. Petersburg Institute for Informatics and Automation of RAS
A.M. Kashevnik – Ph.D.(Eng.), Senior Research Scientist, St. Petersburg Institute for Informatics and Automation of RAS
The tourism industry has been actively developing in the world over the past decades. According to the forecast of the UNWTO World Tourism Organization, the total number of international trips will reach 1.8 billion by 2030. Tourists are increasingly using personal mobile devices and the Internet to get suitable travel routes and attraction information. The problem of a route generation with most suitable tourist attractions attendance for a certain time frame (Orienteering Problem with Time Windows) has been relevant and investigated recently. The tourist conditions and preferences are considering for attraction route construction in current article. The ant colony / bee hive algorithms and evolutionary algorithms are used to solve this kind of problem. However, contextual information is not fully used as the criteria in the route construction process. Usually, only the tourist location and the attraction open hours are considered.
The method proposed in the article is based on the technologies of recommender systems with selecting points of interest and is focused on the ontological approach in conjunction with context management methods. The context in this method is divided into two parts: user part, which describes the situation about the tourist, and regional part, which refers to the region in which the tourist is located. As a problem solution, the article proposes the adaptation of the local iteration method by adding the multi-criteria choice of attractions based on contextual information.
The attraction selection is performed iteratively using a recommender system that works with synthetic coordinates and a module that checks the attraction selection. The attraction route building is based on a local search strategy with tabu, which allows to build a route among objects in an acceptable time. When considering the route both criteria based on estimates of time spent and distance traveled, and criteria related to the contextual situation of the tourist and the region are used.
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