Context prediction plays a vital role in an assistive ubiquitous environment. The environmental configuration in a ubiquitous environment is heavily dependent on the context of the events occurring in the environment. Current state of the art approaches utilize the user's history information for predicting the context of the events. When the user's history does not provide apposite contextual information for the observed activity/event at time t, the history based state of the art context prediction tech- niques fails to predict the appropriate future context. To overcome the gap of missing context information in the user's context history, we propose a Profile based Collaborative Context Prediction (PCCP) approach. PCCP is a predictive association rules based system which utilizes the history of similar users and collaborate among users of the ubiquitous environment. PCCP gener- ates rules at high level of abstraction, human readable and understandable that helps in avoiding the underline details. To evaluate the PCCP, a smart office is considered as an experimental environment. Experiments are carried out on indigenous multi user smart office data set. Our experiments showed significant level of accuracy in both environments. Due to the understandability of output and higher accuracy of PCCP, it can be extended to assist the user in a smart environment.
['Rashid Ahmad', 'Do-Hyeun Kim']
A collaboration based context prediction in smart office