Towards a Hybrid Minimax Recommender for Free-Roaming Museum Visits
George Pavlidis ()
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George Pavlidis: University Campus at Kimmeria
A chapter in Strategic Innovative Marketing and Tourism, 2019, pp 11-19 from Springer
Abstract This paper presents a novel minimax hybrid recommender for free-roaming museum visits that is based on a new museum visit concept that was developed to capture the spatial, temporal and content-based dynamics during free-roaming museum visits. The complex hybrid recommender applies a minimax approach as it estimates an overall visitor dissatisfaction and aims its minimisation. As a result, it is able to develop optimal routes, as sequences of points of interest for each individual visitor. This hybrid recommender, still at its fine-tuning phase, has been tested in large scale simulations, using realistic data for visitors and exhibitions and has already shown to outperform the naive baseline recommender that relies on popularity.
Keywords: Recommender; Recommendation; Cultural heritage; Museum guide; Machine learning; Artificial intelligence (search for similar items in EconPapers)
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Persistent link: https://EconPapers.repec.org/RePEc:spr:prbchp:978-3-030-12453-3_2
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