Mining future spatiotemporal events and their sentiment from online news articles for location-aware recommendation system
Shen-Shyang Ho, Mike Lieberman, Pu Wang, Hanan Samet · 2012
The future-related information mining task for online web resources such as news articles and blogs has been getting more attention due to its potential usefulness in supporting individual's decision making in a world where massive new data are generated daily. Instead of building a data-driven model to predict the future, one extracts future events from these massive data with high probability that they occur at a future time and a specific geographic location. Such spatiotemporal future events can be utilized by a recommender system on a location-aware device to provide localized future event suggestions.