Multiple Tour Guide Recommendation for the Sharing Economy
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This work proposes a tour guide sharing system for real-time matching and recommending multiple guides to customers according to their knowledge, preferences, locations, times, and languages. A key feature of the proposed system is to share not personal things such as cars and accommodations necessary for traveling and staying, but individuals’ knowledge or emotions effectively and economically. Here, we aim to achieve both guide and user quality assurance through generated guide and user profiles by analyzing experience and reviews of guides or POIs. And we discuss a prototype for recommending guides and users based on spatio-temporal constraints and sharing preferences.
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