Context-Aware Dataset: STS - South Tyrol Suggests IoT Mobile App Data

<strong>STS dataset </strong>was collected by a context-aware recommender system mobile app named as<strong> "South Tyrol Suggests"</strong>. The app provides <strong>context-aware recommendations</strong> for attractions, events, public services, restaurants, and much more based on the rating preferences and personality factors of users. <strong>Contextual</strong> <strong>variables</strong> includes <strong>distance:</strong> far away, near by <strong>time available:</strong> half day, one day, more than one day <strong>temperature:</strong> burning, hot, warm, cool, cold, freezing <strong>crowdedness:</strong> crowded, not crowded, empty <strong>knowledge of surroundings:</strong> new to area, returning visitor, citizen of the area <strong>season:</strong> spring, summer, autumn, winter <strong>budget:</strong> budget traveler, price for quality, high spender <strong>daytime:</strong> morning, noon, afternoon, evening, night <strong>weather:</strong> clear sky, sunny, cloudy, rainy, thunderstorm, snowing <strong>companion:</strong> alone, with friends/colleagues, with family, with girlfriend/boyfriend, with children <strong>mood:</strong> happy, sad, active, lazy weekday: weekday, weekend <strong>travel goal:</strong> visiting friends, business, religion, health care, social event, education, scenic/landscape, hedonistic/fun, activity/sport <strong>means of transport:</strong> no transportation means, a bicycle, a car, public transport More details can be found here: <em>Braunhofer, Matthias, Mehdi Elahi, and Francesco Ricci. "<strong>Techniques for cold-starting context-aware mobile recommender systems for tourism</strong>." Intelligenza Artificiale 8, no. 2 (2014): 129-143.</em>