Title :
What Cuisine Do You Like?: Improving Dining Preference Prediction through Physical Social Locations
Author :
She, Jun-Kuan ; Vassilovski, Anna ; Hon, A.
Author_Institution :
Dept. of Electron. & Comput. Eng., Hong Kong Univ. of Sci. & Technol., Hong Kong, China
Abstract :
Social behaviors such as dining preferences are inextricably linked with physical social locations (e.g., home, work, and hangout location), rather than just due to the personal interests/cultures and influences from social peers. With the uses of location-based services in online social networks over smart phones, such physical social locations are easily available as an effective alternative to infer dining preferences. Results show that the prediction of individual dining preferences using physical social locations outperforms the common approaches simply using social information from peers.
Keywords :
behavioural sciences computing; mobile computing; smart phones; social networking (online); social sciences computing; dining preference prediction; location-based services; online social networks; physical social locations; smart phones; social behaviors; Conferences; Inference algorithms; Prediction algorithms; Predictive models; Social network services; Training; Vectors; Social computing; inference; physical social locations;
Conference_Titel :
Green Computing and Communications (GreenCom), 2012 IEEE International Conference on
Conference_Location :
Besancon
Print_ISBN :
978-1-4673-5146-1
DOI :
10.1109/GreenCom.2012.72