• Anisha Sharma
• Sanjeev Ghosh

Communication Devices, wireless and web services have allowed mobile users to demand various kind of services on their devices anytime anywhere. Helping users obtain required information effectively is a measure of the quality of service. Predicting the next location of the mobile user as it moves through wireless network plays a key role in maintaining the context-aware services. Previous work done in this field was based on rule-based trajectory mining. For the better recommendation the trajectories are needed to be updated automatically as per the changes in the behavior of the user. This approach consists of a classification-based machine learning algorithm Support Vector Machine (SVM) with Radial Basis Function (RBF) kernel. It gives an accuracy of 6-10% more than traditional methodsof manually updating the system and a good precision stating the relevancy of the system.

Recommendation system, Data Mining, Artificial Intelligence, Location prediction,Machine Learning, Mobile Computing, Mobility Pattern, Classification.

"USERS’ NEXT LOCATION RECOMMENDATION USING DATA MINING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.277-281, June 2019, Available :http://www.jetir.org/papers/JETIR1906I70.pdf

"USERS’ NEXT LOCATION RECOMMENDATION USING DATA MINING ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp277-281, June 2019, Available at : http://www.jetir.org/papers/JETIR1906I70.pdf