Conceptual model of a GIS-based recommendation system for sustainable heritage routes formation
DOI:
https://doi.org/10.32347/2411-4049.2026.2.95-104Keywords:
spatial data, tourism planning, points of interest, multi-criteria evaluation, visitor management, personalizationAbstract
The purpose of the study is to substantiate a conceptual model of a GIS-based recommendation system for generating sustainable routes to cultural and natural heritage sites. The relevance of the research is determined by the need to move from recommending separate popular locations to constructing routes that consider user interests, spatial, temporal, thematic, recreational and environmental constraints. The methodology combines system analysis, conceptual modelling, a geographic information approach and multi-criteria evaluation. The article defines the input data of the system: the user profile, characteristics of heritage sites, spatial data, contextual parameters and sustainability criteria. The proposed model includes modules for the user profile, heritage site database, geographic information analysis, context processing, multi-criteria evaluation, route generation and recommendation explanation. The result is a conceptual scheme in which a route is interpreted as a managed information object that should correspond to user interests, spatial and temporal feasibility, thematic coherence and the principles of sustainable territorial use. The scientific novelty lies in integrating personalized preferences, GIS routing logic, thematic coherence of heritage sites and sustainability criteria into a single mechanism for route generation. The theoretical value consists in clarifying the structure of a GIS-based recommendation system for cultural and nature-based tourism. The practical value lies in the possibility of using the model as a basis for a software prototype, a heritage site database and a route ranking algorithm. Further research should focus on formalizing criterion weights, selecting spatial and contextual data sources, developing an experimental dataset and evaluating recommendation quality in real or simulated tourist scenarios.
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