Thesis Type: Postgraduate
Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Computer Engineering, Turkey
Approval Date: 2014
Student: İLKCAN KELEŞ
Supervisor: İSMAİL HAKKI TOROSLUAbstract:
Due to the increasing use of mobile phones and their increasing capabilities, huge amount of usage and location data can be collected. Location prediction is an important task for mobile phone operators and smart city administrations to provide better services and recommendations. In this work, we have investigated several approaches for location prediction problem including clustering, classification and sequential pattern mining. We propose a sequence mining based approach for location prediction of mobile phone users as an appropriate solution. More specifically, we present a modified Apriori-based sequence mining algorithm for next location prediction, which involves use of multiple support thresholds for different levels of pattern generation. The proposed algorithm involves a new support definition as well. We have analyzed the behaviour of the algorithm under the change of threshold through experimental evaluation and the experiments indicate improvement in comparison to conventional Apriori-based algorithm.