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

STS dataset was collected by a context-aware recommender system mobile app named as "South Tyrol Suggests". The app provides context-aware recommendations for attractions, events, public services, restaurants, and much more based on the rating preferences and personality factors of users.

Contextual variables includes 

• distance: far away, near by
• time available: half day, one day, more than one day
• temperature: burning, hot, warm, cool, cold, freezing
• crowdedness: crowded, not crowded, empty
• knowledge of surroundings: new to area, returning visitor, citizen of the area
• season: spring, summer, autumn, winter
• budget: budget traveler, price for quality, high spender
• daytime: morning, noon, afternoon, evening, night
• weather: clear sky, sunny, cloudy, rainy, thunderstorm, snowing
• companion: alone, with friends/colleagues, with family, with girlfriend/boyfriend, with children
• mood: happy, sad, active, lazy weekday: weekday, weekend
• travel goal: visiting friends, business, religion, health care, social event, education, scenic/landscape, hedonistic/fun, activity/sport
• means of transport: no transportation means, a bicycle, a car, public transport

More details can be found here:

Braunhofer, Matthias, Mehdi Elahi, and Francesco Ricci. "Techniques for cold-starting context-aware mobile recommender systems for tourism." Intelligenza Artificiale 8, no. 2 (2014): 129-143.