https://orcid.org/0000-0001-7922-715X
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ABSTRACT
In recent years, decision support systems (DSSs) have successfully deployed ontologies in their architecture. The result of such a use is information systems that assist users and organizations in semi-structured decision-making activities. Visitors from throughout Iran travel to different cities and regions every year, and they need help making their choices. Some of these tourists are unable to visit the beautiful areas of the destination city due to a lack of awareness. In this study, we design an ontology-based spatial DSS to find entertainment and tourism centers in Arak, Iran. The objective is to provide users with recommendations appropriate for the location, time, age group, type of activity, and other factors. In this model, the demands and concerns of tourists have been managed by creating a domain Web Ontology Language (OWL) for entertainment centers as a knowledge base in the Protégé environment. The developed web-based DSS operates on a client-server architecture using technologies such as Werkzeug and Flask. As a result, it makes it possible to ontology reasoning based on the HermiT engine to choose the right center and conduct a semantic search on classes related to the appropriate point of interest. The main distinction between the proposed methodology and the previous studies on spatial DSS is that criteria are object properties in an ontology. Therefore, decision support relies on real-time reasoning rather than transforming criteria into geospatial layers. The evaluation results confirmed efficient interaction with this system, purposeful information retrieval, and rapid decision-making process. The results also indicated that searching for a POI (point of interest) in the study area using the developed system is at least 30% more successful than a search engine or social media. Moreover, to overcome the cold start problem, the proposed technique might be utilized in conjunction with the POI recommender systems.
Disclosure statement
No potential conflict of interest was reported by the authors.
Data availability statement
The OWL ontology of this study is available on https://github.com/mhvahidnia/OntologyEntertainmentCenter. Other data of this research can be requested from the corresponding author via e-mail.
Additional information
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Notes on contributors
Mohammad H. Vahidnia
Mohammad H. Vahidnia has been an Assistant Professor at the Department of Remote Sensing and GIS, Faculty of Natural Resources and Environment, Science and Research Branch, Islamic Azad University, since 2017. He has directed numerous theses, conducted many research projects, and contributed to numerous journal papers. His research interests include Geo-computation and Artificial Intelligence, Ontology and Logic, Spatial DSS and Expert Systems, Data Structures and Algorithms, Volunteered Geographic Information (VGI), and Web-based and Mobile GIS.
Mojde Minaei
Mojde Minaei received the MSc. degree in Remote Sensing and GIS from Science and Research Branch, Islamic Azad University (IAU), Iran, in 2016. She is currently a PhD candidate at the Department of Remote Sensing and GIS, IAU, Iran. Her current research interests are Geo-computation, Spatial Decision Support Systems, and Spatial Statistics.
Saeed Behzadi
Saeed Behzadi is an Assistant Professor in Surveying Engineering Department of Shahid Rajaee Teacher Training University, Iran. He received his MS degree in Geospatial Information Science in 2008 and a Ph.D. degree in 2013. He has worked within the industry and academia in Iran since 2013. He teaches in the Department of Surveying Engineering and Civil Engineering in the area of GIS, Remote sensing, and Computer Science. His current research interest is Health GIS and Agent Based Modeling.