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Beyond Sensors : A Rule-Based Approach for Cost-Effective Visitor Guidance

Title data

Neubig, Stefan ; Bečevová, Markéta ; Brosta, Fabian ; Loges, Ronja ; Hein, Andreas ; Keller, Robert ; Krcmar, Helmut:
Beyond Sensors : A Rule-Based Approach for Cost-Effective Visitor Guidance.
2024
Event: ENTER 24 , January 17 - 19, 2024 , Izmir, Turkey.
(Conference item: Conference , Speech )

Abstract in another language

Tourism is an important economic driver for numerous regions, at- tracting more than one billion visitors annually. While economically significant, excessive numbers of visitors lead to local overcrowding, which negatively im- pacts visitors’ experience and safety, and causes environmental harm. This paper proposes a practical approach to empowering destination management organiza- tions (DMOs) to manage tourist flows. We advocate for a rule-based approach that models visitor occupancy based on easily understandable influence factors like weather and date. As a central component, an ontology-guided knowledge graph ensures compatibility with diverse touristic data models and allows seam- less integration into existing infrastructures. By digitizing DMOs’ experiential knowledge, we facilitate the implementation of lean and cost-effective visitor guidance. We demonstrate our approach by implementing two applications for two different use cases. The results of our qualitative evaluation reveal the com- pelling potential for rule-based occupancy modeling approaches serving as a baseline for future visitor management systems.

Further data

Item Type: Conference item (Speech)
Refereed: Yes
Keywords: Overcrowding; Rule-Based Occupancy; Knowledge Graphs; Ontologies; Visitor Guidance; Recommender Systems
Institutions of the University: Faculties > Faculty of Law, Business and Economics > Department of Business Administration
Research Institutions
Research Institutions > Affiliated Institutes
Research Institutions > Affiliated Institutes > Branch Business and Information Systems Engineering of Fraunhofer FIT
Research Institutions > Affiliated Institutes > FIM Research Center for Information Management
Faculties
Faculties > Faculty of Law, Business and Economics
Result of work at the UBT: No
DDC Subjects: 000 Computer Science, information, general works > 004 Computer science
300 Social sciences > 330 Economics
Date Deposited: 28 Nov 2023 06:35
Last Modified: 19 Feb 2024 06:30
URI: https://eref.uni-bayreuth.de/id/eprint/87885