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Articles

Computer Science > Artificial Intelligence

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By Ioannis Giannopoulos, Ioannis Papoutsis, Eleni Saka
| arXiv
arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs.
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Predicting the Unseen: Transductive Transfer Learning in Real Estate Price Prediction

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By Christopher Kmen, Gerhard Navratil, Ioannis Giannopoulos
| Wiley Online Library Verified
1 Introduction Apartment price modeling, particularly for newly built apartments, is a dynamic field with far-reaching implications not only for investors and urban planners but also for policymakers and citizens. Accurate property valuation models can inform economic decisions and influence investment strategies, real estate developments, and public policy on issues such as housing affordability and urban infrastructure.
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Decoding wayfinding: analyzing wayfinding processes in the outdoor environment

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By Negar Alinaghi, Ioannis Giannopoulos, Markus Kattenbeck, Martin Raubal
| Taylor & Francis Online
?Mathematical formulae have been encoded as MathML and are displayed in this HTML version using MathJax in order to improve their display. Uncheck the box to turn MathJax off. This feature requires Javascript. Click on a formula to zoom. Abstract Navigating complex environments is crucial for human life, yet understanding the cognitive processes involved in its wayfinding component remains challenging. One theoretical model that explains these processes is Downs and Stea’s four-step model.
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