gTravel: Weather-Aware POI Recommendation Engine for a Group of Tourists

Weather is a big factor in tourist decisions, and certain places or events aren't even recommended during dangerously bad weather. It is difficult to provide a better recommendation to a group of tourists in these circumstances. We propose gTravel, a weather assistant framework that predicts weather in specified points of interest for a group of tourists. We demonstrate how prior knowledge of climatic patterns at a POI, as well as prior insights into how visitors rank their destinations in a variety of weather conditions, can help improve choice reliability. According to our findings, the recommendations are significantly more valid, and the recommended remedy is more comfortable.