Abstract
The context prediction and especially the location prediction is an important feature for improving the performance of smart systems. Predicting the next location or context of the user make the system proactive, so the system will be capable to offer the suitable services to the user without his involving. In this paper, a new approach will be presented based on the combination of pattern technique and Bayesian network to predict the next location of the user. This approach was tested on real data set, our model was able to achieve 89% of the next location prediction accuracy.
Highlights
Nowadays, we are witnessing an exponential advancement of technology
An intelligent/smart system is based on the early idea of the ubiquitous computing [1]
An improved approach of user location prediction is presented based on the current context features that are considered important for the prediction
Summary
We are witnessing an exponential advancement of technology. From the advent of the computers to the advent of laptops and tablets, technology has become an integral part of our daily life. The evolution of computer networks and telecommunications marked the most important development enabling mobility and information sharing This allowed the emergence of new systems that combine ubiquity and intelligence. It is a machine that integrates a computer connected to the network that can collect and analyze data and communicate with other systems These systems are characterized by their ability to learn from historic of user behaviour, security and connectivity. Their capability to adapt to the recent data extracted from the environment. An improved approach of user location prediction is presented based on the current context features that are considered important for the prediction.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: International Journal of Advanced Computer Science and Applications
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
