D-007
A Point-of-interest Recommender System using Weather Data

◎Van Khanh Nguyen・Yu Suzuki・Satoshi Nakamura（Nara Inst. of Science and Tech.）

Point-of-interest (POI) recommender systems (TRS) provide a list of suitable venues for users using any source of information. However, there is not much attention to the impact of weather on user decision when travel. In this paper, by introducing an approach that utilizes the POI-weather-check-in relatedness, we provide appropriate recommendations for users. Our system classifies the POIs by finding the correlation pattern weather features and check-in distribution. The experimental results prove that the recommended POIs meet users demand, and the recommendation accuracy is significantly improved.